090417 dissertation ubaier

C O V E N T R Y

U N I V E R S I T Y

Faculty of Engineering and Computing

Department of Aerospace Engineering

BEng Aerospace Technology

388SYS Individual Project

UAVS Project 2009

Author: UBAIER AHMAD BHAT

Supervisor: DR. S M HARGRAVE

Submitted in partial fulfilment of the requirements for the Degree of Bachelor of

Aerospace Technology

2008 - 2009

“I have not failed. I've just found ten

thousand ways that won't work.”

--Thomas Alva Edison

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DECLARATION

The work described in this report is the result of my own investigations. All sections of the text and results that have been obtained from other work are fully referenced. The dissertation and the original work related to it have not been submitted to any institute for an academic award. I understand that cheating and plagiarism constitute a breach of University Regulations and will be dealt with accordingly.

Signed: Date:

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ABSTRACT

Bhat, U. 2009. UAV Project 2009, BEng Aerospace Technology Dissertation. Faculty of Engineering and Computing, Coventry University. Unmanned Arial Vehicles have seen an unprecedented growth in recent years in both military as well as civilian application domain. This has increased the interest and research in unmanned technology at academic level. Coventry University as also invested in technology related to development of UAVs like an autopilot and flight simulators. This report details the work done on implementation of an autopilot system on UAV and simulation of the aircraft. The approach used for this project was to get familiar with the autopilot system (Micropilot MP2028g) and install it onto an aircraft. The project also involved an attempt to simulate and analyse of the pitch dynamics of the aircraft model acquired. The autopilot was implemented on a test aircraft and was tested on ground but a flight test did not take place. Different packages for simulations and problems related to them were also investigated. Keywords: unmanned aerial vehicle, UAV, autopilots, flight simulation, modelling.

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CONTENTS

Declaration i Abstract ii Table of Contents iii Acknowledgements and Dedication v 1. INTRODUCTION 1 1.1 Aims and Objectives of the Project 1 1.2 Outline of the Report 1 1.3 Modifications to project aim. 2 2. LITERATURE REVIEW 3 2.1 Unmanned Arial Vehicles 3 2.1.1 Introduction 3 2.1.2 Types of UAVs 3 2.1.3 Components of a UAV System 5 2.1.4 Applications 6 2.2 Stability and Automation of UAVs 8 2.3 Dynamics of Flight 10 2.3.1 Introduction 10 2.3.2 Six Degrees of Freedom (6DOF) 10 2.3.3 Pitch dynamics and Longitudinal stability 10 2.4 Modelling and Simulations 12 2.4.1 Introduction 12 2.4.2 Modelling and Simulation Techniques 12 2.4.3 Applications 12 2.4.4 Problems 13 2.5 System Identification 14 3. UAV PLATFORM 15

3.1 INTRODUCTION 15 3.2 TEST PLANE 15 3.3 2009 UAV PLATFORM 18

4. THE AUTOPILOT 20 4.1 Introduction 20 4.2 Components 20 4.3 Installation 22

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4.4 Working and Configuration 23 4.5 Problems 23 5. FLIGHT SIMULATOR 25 5.1 Introduction 0 5.2 Merlin Flight Simulator 0 5.3 Flight Simulation Modals 0 5.4 Flight Tests 22 6. System Identification using AeroSim 0

7. Conclusion

8. Further Work and Recommendations 0

9. References 0

10. Bibliography 0

11. Appendixes 0 A Initial Documentation and Interim Report I B Test Results IX C Appendix Title

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ACKNOWLEDGEMENTS AND DEDICATIONS I would like to thank Dr. Stephen Hargrave for supervising the project and helping me throughout the course. I would also like to thank Mr. Basini, Mr. Fisher, Dr. Lambert and Mr. Thorley for their help for the project and the course. I would also like to thank fellow students Mohammad Bahrami, Arnaud Dupin, Thomas Gobeaut, Douglas Mackenzie and Kelvin Nelson. I would like to thank Allah for giving be strength and patience throughout the project and the course. I would also like to thank my family for their financial and emotional support. I would also like to dedicate this project to those innocent children who have been killed in UAV strikes worldwide and pray that the unmanned technology is not used for any inhumane activities.

CHAPTER 1: INTRODUCTION

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CHAPTER 1: INTRODUCTION 1.1 Aims and Objectives of the Report The report presents the details of the work done on implementation of MicroPilot MP2028g autopilot on the UAV platforms developed in the university. The report also presents the results of research into the modelling and simulation of the UAV. The main objectives set for the project were as follows:

1. Familiarisation and implementation of the MicroPilot 2028 2. Familiarisation with Merlin Flight Simulator and modelling and simulation of

the UAV. 3. System identification and generation of linearised model of the pitch dynamics

of the aircraft. 1.2 Outline of the Report Chapter 2: Literature Review: This chapter background information about UAVs and their applications, Automation of aircrafts, modelling and simulation of systems. Chapter 3: UAV platform This chapter gives details about the UAV platforms used for the project. Chapter 4: Autopilot In this chapter details about the MicroPilot MP2028g along with some information related to installations and setup. Chapter 5: Flight Simulation This chapter contains detailed information about Merlin Flight simulators and gives some details modelling and simulation of the aircraft. Chapter 6: System Identification This chapter contains some details about AeroSim Blockset. Chapter 7: Conclusion Chapter 8: Further Work and Recommendations References Bibliography Appendix A: This Appendix contains the initial documentation and the interim report of the project. Appendix B This Appendix contains the flight test and simulation results.

CHAPTER 1: INTRODUCTION

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1.3 Modifications to the project aims Initially it was planned to use Merlin Flight Simulator for simulation and modelling purpose but due to some reason, which are discussed later in the report, this was changed to AeroSim Blockset. This had a major effect on the aims that the project had initially set to in regards to simulations.

CHAPTER 2: LITERATURE REVIEW

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2.1 Unmanned Arial Vehicles 2.1.1 Introduction An Unmanned Arial Vehicles (or UAV), also known as a drone, is an aircraft without a human operator on board (MSN Encarta c. 2008). UAVs are different that guided missile or cruise missiles in that the air vehicle is designed to come back and be re-used. These are also different from normal remote controlled aircrafts in that they have a high technology control systems on board which means can operate out of line of sight and at altitudes where person on the ground cannot readily see them. These air vehicles still need a pilot or an operator who rather than being seated in the aircraft itself is located in a control centre normally referred to as a Ground Control Station. (UAVSA c. 2008). 2.1.2 Types of UAVs 2.1.2.1 Classification by Aircraft Configuration In general an aircraft is any flying machine/vehicle in all possible configuration be it fixed-wing, rotary-wing, a balloon or an airship and potentially any aircraft can be converted into an UAV with the right technology and control systems installed on board (Beggs 2009). Therefore one of the ways classifying different types of UAVs is by type of aircraft configuration. a) Fixed wing UAV These are the most common types of UAVs and are currently being used for wide range of applications. These can be of different sizes like the big Northrop Grumman Global Hawk with a wing span of 39.9m (Northrop Grumman 2007a) to the small backpack Casper form Becker Avionics with a wing span of just 2.5 m (Becker Avionics 2006). Some examples of different size and range fixed wing UAVs can be seen in figure 2.1a One of the reasons for the success of fixed wing UAVs is that these are quite stable and require simpler systems to control compared to other configurations.

Figure 2.1a Examples of some fixed wing UAVs (BBC

News 2009)


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b) Rotary-wing UAVs There has been a lot of development in rotary-wing UAVs in recent years. The manoeuvrability and the ability to maintain the aircraft in hovering of a Rotary wing UAVs or a helicopter UAV present several advantages for UAV applications. However, rotary-wing aircrafts are very unstable and therefore more difficult to control and require the application of reliable control laws. (Remub et al. 2007:111)

c) Airship UAVs A number of unmanned airship projects, both free-flying and tethered (aerostats), have been initiated to provide synergistic capabilities to those provided by unmanned aircraft, most notably extended persistence. There appears to be potential for synergy between airships and UAS that enhance capability or reduce cost in several mission applications including force protection, signals intelligence collection, communications relay and navigation enhancement. An airship UAV‟s most significant challenge appears to be limited mobility. (US OSD 2005:32) Example of some Airship UAVs can be seen in Figure 2.1c

Advanced Airship Flying Laboratory by American

Blimp Corporation Tethered Aerostat Radar System (TARS) by ILC

Dover

Figure 2.1c Types of UAVs (US OSD 2005)

Northrop Grumman MQ-8B Fire Scout is an

advanced rotary-wing UAV (Northrop Grumman 2007)

A-160 Hummingbird by Boeing/Frontier (US OSD 2005)

Figure 2.1b Examples of Rotary-wing UAVs.


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2.1.2.2 Classification by Autonomy Based on the autonomy of the flight control system the UAVs can be categorised into three main levels: Level 1: no autonomy on-board the aircraft. This will be more like a remote controlled aircraft (similar to a hobby plane). However different systems on-board the aircraft like sensors, cameras, GPS receivers and transmitters can be used to assist the on ground operator to fly the air craft out of sight. Level 2: semi-autonomous aircraft with autopilot on-board to keep the aircraft stable. Difficult tasks like landing and takeoff will still be carried out remotely by a human pilot Level 3: fully-autonomous aircraft with onboard flight management system that can manage the whole set operation (including takeoff and landing) once the mission is uploaded. These levels of autonomy are only related to the basic flying capabilities of the UAV like take off, landing, cruse, some navigation and not to any other autonomous function that a UAV might be required like tracking objects, object recognition, collision avoidance etc. Autonomy of the aircraft has been discussed in detail in the section 2.2. 2.1.3 Components of a UAV System A UAV system can be divided into three main components. These will be the UAV platform, the ground station and the payload (UAVSA c. 2008). These have been discussed individually below.

2.1.3.1 UAV Platform The UAV Platform itself will consist of the following components/systems: a) The airframe As mentioned earlier the airframe of a UAV can be of any configuration i.e. fixed-wing, rotary-wing etc. Like any conventional aircraft the airframe must have the required aerodynamic properties, be light weight and must be able to sustain the specified loads for the different application.

Fig. 2.1c Components of a UAV system.


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b) The propulsion system The type of propulsion system used within a UAV will depend on the type of aircraft and task requirements. c) Flight control System. The flight control system (FCS) is the most important system within the UAV. The system is connected to different types of sensors (gyroscopes, pressure sensors), navigations systems and avoidance systems. Complexity of the FCS again depends on the UAV application. 2.1.3.2 Payload The UAV may be required to carry different types of payloads. The most common payload is a camera or a optical sensing system. This is usually used by the operator on the ground station to see were the UAV is going or look at particular targets. Other payloads can be infrared cameras, radiation detectors, air sampling systems etc. Military UAVs may have munitions, radars, scanners etc. 2.1.3.3 Ground Control System or Station At the ground control station the operator controls or monitors the UAV. The ground station will therefore have avionics flight display, navigation systems, Position Mapping system, system health monitoring. The Ground Station will also have some kind of manual control devices like joysticks to control the aircraft. (UAVSA c. 2008) The Ground Control station will also have system to receive data from the UAV like video, photographs, etc depending on the onboard systems 2.1.4 Applications Unmanned Arial Vehicles (UAVs) have seen unprecedented levels of growth in military and civilian applications domains. UAV applications are usually referred to as 3D or D3, „dull, dirty and/or dangerous‟. The primary applications identified and used to date all involve putting the UAV and its payload in environments where the pilot in a manned operation might be significantly at risk of losing his life or dying of boredom. Currently the UAV applications are mostly defence related and main investments are driven by future military scenarios. Today the civilian UAV market is small compared to the military one. Significant civil markets for UAVs are still to emerge, with only limited niche applications being currently available. However, in the next 10-15 years, the expectations for the market growth of civil and commercial aerial robotics are very high. (Ollero and Manza 2007:3) There is also a cost justification for using UAVs. They can have longer operational duration: they can require less maintenance: they can be cheaper on fuel to operate: they can be operated remotely and sometimes autonomously carrying out the mission with the minimum of human intervention and supervision: and they can be deployed in a number of different terrains and are not always dependent on prepared


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runways. Some argue that the use of UAVs in the future will be a more responsible approach to certain airspace operations from an environmental, ecological and human risk perspective (UAVSA c. 2008). Below are some of the examples of UAV applications taken from UAVS website.

Aerial Policeman and Crowd Monitoring Aerial Reconnaissance Aerial Traffic and Security Watch Air to Air Missiles, Air to Ground Missiles, Anti-Tank Missiles Battlefield Management Crop Dusting, Crop Management Disaster damage estimation, Disaster effects management Fire Fighting Fishery Protection, Forestry Geophysical surveys Guided Shells Life raft Deployment Litter on beaches and in parks Maritime and Mountain Search and Rescue Mineral exploration Oil and Gas Exploration and Production Oil and gas pipeline Pollution Control and Air Sampling Search and Rescue Telecoms relay and signal coverage survey Waterways and shipping Wide Area Munitions Deployments


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2.2 Stability and Automation of UAVs Need for taking control out of the human hands and putting it under some sort of automatic control has been there since a long time in aviation history. The reason being that of itself, the path of any aircraft is never stable and aircrafts only neutral stability in heading. Without control, aircraft tend to fly in a constant turn. In order to fly a straight and level course continuously-controlling corrections must be made (McLean 1990). For the human pilot this can be very exhausting and therefore there is a need for some sort of automatic flight control system (AFCS). In an Unmanned the need for having some sort of stability devices and AFCS is therefore quite obvious because an operator on ground will not be able to provide the necessary control correction will be very difficult. As mentioned in the previous section UAV can be dived into different categories based on autonomy they have. This section will have a bit more detail into how stability and autonomy of UAVs. a) Stability of un-autonomous UAVs. An un-autonomous UAV can simply be called a remote control aircraft or a hobby plane. Some people will argue that such an aircraft cannot be categorised as a UAV as mentioned section 2.1. The stability of such an aircraft will depend more on the aerodynamic stability of the airframe. Such stability can be achieved by using conventional methods like using a dihedral wing for roll stability and positioning the centre of mass on front of aerodynamic centre for longitudinal stability (Kermode 2006). The ground operators will thus be responsible for manoeuvres and provide corrections from time to time. The problem in such an aircraft will be that the increase in aerodynamic stability will mean decrease in manoeuvrability. b) Stability of semi-autonomous UAVs In a semi-autonomous UAV the roll of operator is limited to manoeuvres lonely. Flying the aircraft will be more like playing a video game where the operator can move around using a joystick and does not have to worry about stabilising or providing any control corrections. An onboard computer or an autopilot will to this job. Apart from the aerodynamic stability methods mentioned in previous section following methods/devices

Aerodynamic Stability Augmentation System (SAS): This system makes use of the aerodynamic control surfaces like elevators, ailerons and rudders to provide improved handling qualities (McLean 1990:10). For example for the pitch stability will be achieved by applying elevator deflections proportional to the pitch rate which will provide additional damping. Example of such an autopilot system will be in Chapter 5. This type of systems will require gyroscopes to record the changes and provide feedback to the autopilot. Non-Aerodynamic Stability Augmentation Systems: Non-aerodynamic augmentation devices are used mostly for small and miniature UAVs. Such devices are used because adverse meteorological conditions generally affect smaller aircraft more strongly than they affect larger aircraft and there is no


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known way to create controlled aerodynamic forces sufficient to counteract the uncontrollable meteorological forces on miniature aircraft. Such systems can use devices like telescopic shafts with a mass pod or counter weight at the end. The telescoping shaft and mass pod are stowed in the rear of the aircraft. When deployed, they extend below the aircraft. (Langley Research Centre 2005) A similar example of such a system can be of the long rod or shaft that a funambulist uses while tightrope walking to balance himself.

c) Fully autonomous UAVs A fully autonomous UAV will have AFCS or autopilot that completely replaces the human operator in the control of the aircraft. Such AFCS will be capable of take off, landing, following a navigation path and depending on the specification able to perform non-aggressive and aggressive manoeuvres. The components and sensors with fully autonomous UAV will include gyroscopes, pressure sensors, GPS navigations system, collision avoidance system and electronic compass. The aircraft will uses similar methods of stability as mentioned earlier. Table 2.1 shows a list of commercially available systems autopilot system for UAVs.

Table 2.1 List of Commercially Available Autopilots (UAS Research 2008)

Company Autopilot Models Used on website

A Level Aerosystems (Russia) Autopilot A Level Aerosystems, Russia www.zala.aero

BAE Systems (USA) MIAG NSU

RQ-2A/B Pioneer (Pioneer Inc., USA) BQM-74 (Northrop Grumman, USA) CL327 (Bombardier, Canada) Mirach100/5E (Galileo Avionica, Italy)

www.baesystems.com

Curtiss Wright - Vista Controls Corp (USA)

Vista Controls IMMC

Global Hawk (Northrop Grumman, USA) www.cwfc.com

Mavionics (Germany) Autopilot I Autopilot II

Cabure, Yagua (Nostromo, Argentina) Yarara (Nostromo, Argentina)

www.mavionics.de

MicroPilot (Canada) MP2028

Scarab (SCR, Spain) X-Vision (SCR, Spain) Boomerang (BlueBird Aero, Israel) Blueye (BlueBird Aero, Israel) ALBA (INTA, Spain) Casper (Becker Avionics, Israel)

www.micropilot.com

Rockwell Collins, Inc (USA) G-311 Sky-X (Aliena Aeronautica, Italy) www.rockwellcollins.com

Selex Sensors & AS (UK) Selex FCS Phoenix (BAE Systems, UK) www.selex-sas.com

weControl (Switzerland) wePILOT 1000 wePILOT 2000 wePILOT4RMAX

Scorpio (EADS, France) Copter I (SurveyCopter, France) APID (CybAero, Sweden) DRAC (EADS, France) DVF 2000 (SurveyCopter, France) Skeldar (Saab, Sweden) Tracker (EADS, France) RMAX (Yamaha, Japan)

www.wecontrol.ch


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2.3 Dynamics of Flight 2.3.1 Introduction In the previous section it was said that the reason why Autonomous Flight Control Systems were used in aircrafts was to keep the aircraft stable and under control. This section is gives some background information about to flight dynamics as it is directly related to control an stability of a aircraft and thus links up with the discussion about the autonomous flight controls 2.3.2 Six Degrees of Freedom (6DOF) An aircraft has got six degrees of freedom in other words it can move in three directions along three axes (up/down, forward, backward, lift, right) and rotate in three directions around the three axis (pitch, roll and yaw).Figure 2.3a shows the 6DOF in a body axis system and also shows the conventional nomenclature for different forces, velocities and moments.

Figure 2.3a Six degrees of freedom of an aircraft in body axis system

(McLean 1990:17) Stability or the lack of it is a property of an equilibrium state. The equilibrium is stable if, when the body is slightly disturbed in any of its degrees of freedom, it returns ultimately to its initial state. An aircraft which may be stable with respect to one degree of freedom but unstable with respect to another (Etkin 1996). Therefore based on the inherent stability of the aircraft and AFCS does not to control all the degrees of freedom. And for this reason autopilots used on an aircrafts can be one-axis, two-axis or three axis. 2.3.3 Pitch dynamics and Longitudinal Stability One of the aims set for the project was to look into pitch control of the UAV and therefore it is important to give some brief background to pitch dynamics. The pitch of the aircraft is controlled by the elevators. Any deflection on the elevator will change the pitch of the aircraft. The aircraft usually oscillates at this point before


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settling on the new pitch angle. The change in pitch can also be induced by activation of high lift devices like flaps, movement of centre of gravity or external forces and turbulence. There are types of oscillation around the longitudinal axis. a) Short Period Pitching Oscillations

The short period pitching oscillations is a damped oscillation about the pitch axis. Whenever the aircraft is disturbed from its pitch equilibrium the mode is excited ad manifested itself as an oscillation in which the principal variables are pitch rate and angle of attack. Typically the frequency of the mode is 0.5 to 2 Hz. In manned aircraft, this is in the region of a human pilot natural frequency, therefore it is essential that the short period mode should be well damped, otherwise severe handling problems can arise (NFTC 2007:22). For computer controlling a UAV will usually be capable to handle a higher frequency but it still needs to be damped as it will damage the onboard systems or payload. It is the short period oscillation which recovers the angle of attack to its trim value, and this happens sufficiently quickly that the speed remains substantially constant.

b) Long Period Pitch Oscillations The long period pitch oscillations, also known as phugoid oscillations, is the most commonly seen as a lightly damped low frequency oscillation in speed, which couples with height. Whenever the aircraft is disturbed from trim speed, the mode manifests itself as a sinusoidal oscillation in which the principal variables are pitch attitude and speed changes. A significant feature of the mode is the angle of attack remains substantially constant throughout. Thus the change in pitch attitude gives a corresponding change in flight path angle, and hence the height excursions. The period is long, typically in the band of 40 to 100 seconds, and the damping mainly due to the rate of change of drag of the aircraft whit speed change. I is possible to deduce that the period of the mode is determined most entirely by the datum speed, and a good approximation is that the period is seconds is equal to 0.25 of the true airspeed in knots (NFTC 2007:23). Since the phugoid mode has such a low frequency, it poses an undemanding task, and an AFCS can control the mode even when it is unstable. The phugoid manifests itself as a trimming problem, which, although not regarded as hazardous when poorly damped however it will hinder the UAV applications like taking images, sensing or tracking a target.


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2.4 Modelling and Simulation 2.4.1 Introduction Modelling and simulations are one of the most important parts of any control system design and integration. This section gives some background information about modelling and simulation and how it can be used for UAV systems. 2.4.2 Modelling and Simulation techniques In order to understand the behaviour of a system, mathematical models are needed. These models are equations which describe the relationship between the inputs and output of a system. The basis for any mathematical model is provided by the fundamental physical laws that govern the behaviour of that system (Bolton 2003:185). For an aircraft the basis of the model will be the relationship between different Newton‟s Laws and Aerodynamic laws that define the motion of an aircraft. As said in the previous section an aircraft has got six degrees of freedom. This makes the mathematical model of the aircraft very complex and will take a lot of time and effort to put all the relationships together. It is therefore important to set of conditions and assumptions which will define the boundary of the system. For example with the mathematical modelling of the aircraft a simpler model can be made by considering only three degrees of freedom or even just two degrees of freedom. This would make the equations much simpler. Another important thing to know in modelling is that the equations will include different constant values or coefficients which are set for the physical system. These coefficients are needed to be determined for the model to represent the true system. For example with an simple spring mass model it is important to know the spring coefficient and the mass for the model to truly represent the system. For an aircraft these can be different aerodynamic coefficient like lift coefficient, drag coefficient etc. These coefficients may be determined by doing measurements and calculations on the actual system, by experimentation or even by simulations that used a different set of data. For an aircraft this might mean doing wind tunnel tests or CFD tests. Simulation is the process in which a range of inputs are put through the mathematical model and the outputs would show the behaviour of the system. Once the model has been verified it can be used for designing the controller and for predicting the actual model. Modelling and simulations are usually done with aid of computer packages. Table 2.4a lists some of the modelling tools that are available for aerospace applications. 2.3.3 Applications As mentioned in the beginning modelling and simulations are a very important part of control system designs. These can also be used to investigation behaviour of systems for optimisation or proving a new concept without risking a real system.


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Table 2. List of Flight Modelling and Simulation tools Package Description Merlin Flight Simulator Commercially available flight simulator which

enables the user to configure their own aircraft models for simulation.

X-plane This is a flight simulator package which enables users to configure their own aircrafts. This program can run on and PC

JSB Sim This is another flight simulator package with user definable aircrafts. It‟s an open source software and therefore will enable to the user to make changes and even change the working of the simularions

YS Sim This is another flight simulator package with user definable aircrafts. It‟s an open source software and therefore will enable to the user to make changes and even change the working of the simularions

Matlab This is a very powerful mathematical computational package which is widely used for modelling and control related applications

Simulink Part of Matlab this package enables modelling a system with the help of gui blocks

AeroSim Blockset This package working using Simulink and is designed for aerospace applications and modelling.

Aerospace Blockset This package working using Simulink and is designed for aerospace applications.

2.3.4 Problems with modelling A model is defined by assumptions about the real system and therefore can never be hundred percent accurate. These assumptions can also include the different coefficients used for the modelling and without the right values the model will be way off form the real system. In order to get more accurate results a more complex model will be required. The problems in doing so will be that a complex model will require more computation and might cause delay when used in control systems.


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2.5 System Identification and control 2.5.1 Introduction System Identification is the a method of developing a model from a real system in which tests are used to determine the response from the system to some input, e.g. a step input and then finding a model that fits the response (Bolton 2003:240). 2.5.2 System Identification tools Different software packages can be used for system identification some of these are listed in Table 2.5a

These tools can be used to analysis the outputs for the system on step-response plots, bode plots and root locus plots.

Table 2a. List of System Identification Software packages Package Description Matlab A very powerful computational tool with may system

identification functions Simulink Part of Matlab this package enables modelling a

system with the help of gui blocks System Identification Toolbox This is a Matlab/Simulink model used for system

identification SIDPAC This is a Simulink block set used specifically for

aircraft system identification.

CHAPTER 3: UAV PLATFORM

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CHAPTER 3: UAV PLATFORM 3.1 Introduction There were two UAV platforms that were planned to be used for this project. One was built as a test plane for 2008 UAV built projects and the second one was to be built for the 2009 UAV projects. The second one was to be constructed with the help of other students working on other aspects of UAV project. 3.2 Test Plane The test plane is a high wing Clipped Wing Taylorcraft ARF model aircraft. The aircraft had been chosen for its stability and enough space for the payload (Castle 2008:37). The test plane had been flown by the 2008 UAV Project students using remote control and therefore aim was to use the test plane for the testing of autopilot and initial modelling for 2009 UAV projects as well.

Figure 3.2a Top Gun Clipped Wing Taylorcraft from Hanger-

9 (Hanger-9 2008)

3.2.1 The Airframe The dimensions of the airframe are given in the table below.

Table: Speciation of the Test Plane Wing span 1.07 m Wing Area 0.428 m2 Length 1.485 m Weight 6 kg approx 3.2.2 Propulsion Unit and Speed Controller The aircraft uses a „AXi 5330/18 Gold Line‟ electric motor with radial mounted propeller holder (see figure 3.2b). The motor uses two FlightPower EON28 11.1 LiPo batteries. The output is controlled through a Jeti ADVANCE 90 plus controller.


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Figure 3.2b (Model Motors 2006)

Table 3.2a

AXi 5330/18 Gold Line

Specification (Model Motors 2006)

No. of cells max 32 max. 10s Li-Poly

RPM/V 259 RMP/V

Max. efficiency 90%

Max. efficiency current 25 - 60 A (>85%)

No load current / 10 V 2 A

Current capacity 75 A/60 s

Internal Resistance 32 mΩ

Dimensions (Diameter x Length) 63 x 64 mm

Shaft diameter 8 mm

Weight with cables 652 g


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3.2.3 Control system The aircraft is manually controlled by PCM9X ii Transmitter via RS10DS. The aircraft has got four servos which control the ailerons, elevators and rudder.

JR PCM9X ii Transmitter JR RS10DS Receiver

Figure: Manual control unit

The aircraft is autonomously controlled by MicroPilot MP2028g autopilot. Details about the autopilot are given in Chapter 4. 3.2.4 Power supplies The aircraft has got separate power supply autopilot, servos and the motor. 3.2.5 Work done on test plane The test plane had been assemble by the 2008 Project students but there were some of the tasks required to make the aircraft airworthy

Installation of remote control receiver, autopilot and other systems.

Measurement of the aircraft for modelling and simulation.

Table 3.2a Jeti ADVANCE 90 plus controller Specifications

(Jeti 2005) Dimensions: 65 x 55 x 17 mm

Weight: 75/90 g Continuous current: 90 A Accu NiXX / LiXX: 14-32 / 5-10

Voltage 15 – 42 V

Figure: 3.2c Jeti Advance 90 plus speed controller.


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3.3 UAV 2009 Platform 3.3.1 The Airframe Figure 3.3a below show the dimensions for the aircraft. The aircraft was still under construction at the time of this report being written.


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Figure 3.3a Pheonix 09 UAV designed by M. E .Bahrami

Figure 3.3b UAV fuselage under construction.

3.3.2 Propulsion Unit and Speed Controller Same as the test plane. See section 3.2.2 3.3.3 Control system Same as the test plane. See section 3.2.3 3.3.4 Power Supply Same as the test plane. See section 3.2.4 3.3.5 Other components A extra servo will be used to unlock and drop the flaps.

CHAPTER 4: AUTOPILOT

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CHAPTER 4 AUTOPILOT 4.1 Introduction The autopilot used for the UAV is a MicroPilot MP2028g. The autopilot is capable of flying the UAV fully autonomously. The autopilot uses gyroscope, air pressure and GPS as senses for inertia, speed, altitude and position to control the aircraft. During the project the autopilot been tested on ground but a flight test could not be achieved. 4.2 Components The MicroPilot MP2028g autopilot system consists of the following components.

Table 4a: List of components for autopilot system Component Description

MP2028g CORE

Figure 4.2a (MicroPilot 2004)

This is the main autopilot board and all the other components are connected to it.

MP2028g AGL


Above Ground Level (AGL) is an ultrasonic altimeter that provides altitude information to an altitude of about 4.88m above the ground. It is required for autonomous takeoff and landing.


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MP-Servo board


The Servo board distributes the servo signal to each servo

MP-ANT


This is the GPS antenna which connects to the CORE board. The antenna is mounted on a 10cm x 10cm copper board.

Radio Modems and MP-COM board

Figure 4.2a

The radio modem connects to the ground station computer and communicates with the autopilot via the COM board.

Faraday Cage

Figure 4.2a

The Faraday cage had been designed by 2008 UAV Project Students to shield the CORE board from any external interference especially from the motor.


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Software The software is used to communicate with the autopilot from the ground station. MicroPilot Horizon: This software provides a GUI for configuring the autopilot and setting up flight path. Microsoft HyperTerminal: The HyperTerminal can be used to communicate with the autopilot. It uses a commend line interference but will enable to configure more setting and acquire flight data.

4.3 Installation The autopilot components were installed on the control board. In this section only the important points to be remembered while installing the MP2028g are mentioned. Full details of installing MP2028g can be found MicroPilot Autopilot Manual and Installation DVD. a) Control Board All the autopilot components are installed on a single board. The layout of the control board for the test aircraft is shown in figure 4.3a

Figure 4.3a: Autopilot Board for Test Plane.

b) Servo Board


23

The servo board was connected to the servos for normal setting. This means that only servos for ailerons, elevators, rudder and throttle were connected. Figure 4.3b below shows which pins are supposed to be connected to which servo.

Figure 4.3b: Servo Board

4.4 Configuration The autopilot was configured using the MicroPilot Horizon software. It was configured for Normal settings and under a fake GPS lock. The autopilot was then tested on ground for basic servo responses. 4.5 Problems with the autopilot There were some issues with configuration the autopilot a) Communication Problem The autopilot should be able to communicate with the ground station either by using MicroPilot Horizon or by using Microsoft HyperTerminal. The autopilot was able to communicate with the Horizon software properly most of the time but it did freeze the computer while configuring the Rudder setting couple of times. This behaviour however only happened while using the personal laptop and did not occur when universities laptop was used. This might have happened have happened due to the former being too slow. The main communication problem occurred when HyperTerminal was used to communicate with the autopilot. The HyperTerminal only communicated once and for other attempts showed nonsense values on the screen as shown in figure 4.5. The communication using HyperTerminal is very important to get the flight data for any further investigation. Most importantly the data is very important for analysis for selection of proper gains.


24

Figure 4.5a Screenshots of the HyperTerminal data. Top: The data on the HyperTerminal screen when a proper connection was estabilished. Above: The HyperTerminal data showing nonsense

values.

b) Battery problem: The autopilot seems to drain the batteries in a very short period of time and this delayed configuring it. However with the new batteries this did not seem to be a problem. The autopilot had some issues with the AGL unit in the 2008 UAV project. However the AGL seem to respond properly during the ground tests showing the right distance from ground. It might be possible that the interference from the motor would have affected the AGL unit in the past.

CHAPTER 5: FLIGHT SIMULATION

25

CHAPTER 5: FLIGHT SIMULATION 5.1 Introduction The UAV was planned to be simulated using Merlin Flight Simulator present at Coventry University‟s Aerospace Lab. The objective behind doing so was to understand the stability of the aircraft so that the proper gains for the MicroPilot MP2028g can be determined without risking the UAV in a real flight test. In order to do this it was important to understand the working of Merlin Simulator1 and its own Arthur Autopilot. 5.2 Merlin Flight Simulator 5.2.1 Simulator Choice There were two flight simulators available for the simulations, Merlin‟s MP520 and MP521. Some of the options available on the two can be seen in Table 5.2a.

Table 5.2a Merlin Flight Simulators present at Coventry University.

Merlin MP520 Merlin MP521

Aircraft Config. Software Excalibur I Excalibur I

Excalibur II (beta) Aircraft Systems

Autopilot Arthur Flight Controls Systems

Motion base actuators Electric Hydraulic

Because no autopilot was present on MP520 it was initially decided to use MP521 for the simulations. However MP520 could still be used if the autopilot was not needed for the particular flight and if the model was not for Excalibur II format. 5.2.2 Aircraft Config Software There were two aircraft configuration software available with MP521, the Excalibur I (Ex-I) and Excalibur II (Ex-II). Excalibur I is a stable version and also works on MP520. However the aircraft model designed using Excalibur I is very simple and it does not provide options for advance design like multiple section wing, horizontal and vertical panels. MP521 had beta version of Excalibur II. This version does provide advance configuration. During the initial stage of the project Ex-II was used to configure


26

aircraft models but due to some problem the models did not work or were unstable. These issues were reported to Merlin. Another problem with Ex-II was that it could not be installed on any other computer which meant that the aircraft needed to be configured in lab only. Therefore it was decided to use Ex-II only and keep the models simple. 5.2.3 Autopilot The MP521 simulator has software autopilot installed on it called Arthur. Arthur is a 4-axis (roll, pitch, yaw and altitude) autopilot which means it can be used for fixed wing as well as rotary wing aircrafts. The cockpit controller deflections (from. pitch and roll stick, Yaw pedals and throttle lever) are mixed with autopilot servo deflection to provide closed-loop control. (Merlin Products 2007) 5.2.3.1 Control Modes Arthur provides control using five modes. Figure 5.2a shows the Control Panel inside the simulator cockpit to control the autopilot. It also shows the backend for Arthur which shows the current status of the autopilot and can also be used to set gains for the different modes 1.) Stability Augmentation System (SAS) Modes

The stability augmentation seeks to provide handling qualities in roll, pitch and yaw by providing additional damping. For example for the pitch stability this is achieved by applying a control surface deflection proportional to the pitch rate. It is important to engage the SAS Modes before any other autopilot modes can be used.

2.) Autopilot (AP) Modes

The AP modes maintain a particular flight parameter. For example for the Altitude (ATT) mode the autopilot will maintain the aircraft at a specific pitch altitude. ATT mode will either maintain the current altitude when the mode is engaged or will move the altitude set in command mode. There are three modes available under AP mode: a) Altitude (ATT) mode b) Wing Leveller (WNG LVL) mode c) Turn Co-Coordinator (TC) mode


27

Figure 5.2a Merlin Flight simulator Autopilot: The Flight Control Panel and Arthur backend.

3) Command (CMD) Modes

The CMD modes are used to set the demands for AP mode. For example the Altitude hold mode will be used to set the required altitude and vertical speed. The ATT autopilot mode will then try to maintain this altitude. There are three modes available under CMD mode a) Heading Hold (HDG) Mode b) Altitude Hold (ALT) Mode c) Speed Hold (IAS) Mode These modes can be engaged only if the related AP modes are engaged first.

4) Navigation (NAV) Mode

Arthur includes two navigation modes for tracking VOR beacons and instrument landing systems. These modes were not required for this project.


28

Control Mixing It is important that the aircraft model has got External Controls enabled on the system settings of Excalibur in order for autopilot to engage (see figure 5.2b). 5.3 Flight Simulation Models In order to understand the working of the flight simulator and Arthur autopilot a pre-built stable model of Cessna172 was used. The plan was to modify this model convert it into the Test Plane model and UAV model. One of the issues with the configuring the models were the simulator could not run small models and therefore the models were scaled up. Another issue was that Excalibur only as combustion engines as power plant which means that the total mass of the aircraft will reduce once the consumption of fuel. One way to overcome this was to use a value of zero for SFC. 5.4 Test Flights The aim of the flight testes was to look into the longitudinal stability of the aircraft. This meant analysis of the natural short-period oscillations and long-period (or Phugoid) oscillations damping of the aircraft and how the autopilot will assist in further damping. The tests were done to find the open loop response and close loop response i.e when the autopilot was engaged. 5.4.1 Open Loop and Close Loop Response Test In order to get the open loop response of the aircraft different types of signals were manually inputted using the control stick. The closed loop response flight tests were similar to the open loop test the only difference being that the autopilot was switched on for these tests. One of the main problems encountered during the tests was that a perfect and repeatable input could not be inputted manually. Another problem for these tests was that as these were done quite earlier stage in the project getting used to the flight simulator took some time. 5.4.2 Comparison test These testers were done in the last stages of the project using Merlin Simulator in order to see how the different modes available within the autopilot will affect the stability if flight. For this three flights were conducted. The Cessna 172 model was used.

Figure 5.2b The external Controls settings must be checked on the

Systems settings on the Excalibur editor for autopilot to function.


29

a) Autopilot off: For the first test took place in autopilot off. The flight test procedure is given below

b) Autopilot on SAS Pitch mode. For this test the autopilot was left on in stability augmentation mode

c) Autopilot on in ATT mode. For this test the autopilot was set in ATT mode. The flight test procedure is given below

The results for these tests are discussed in next section. 5.5 Results and Analysis 5.5.1 Open Loop and Close Loop Response Analysis As mentioned section 5.4 these tests were done in the earlier stage of the project. The full list of test and results can be found in Appendix B. There was a major problem with these tests because proper input signals could not be generated and because of the unfamiliarity with the M521 keeping the aircraft in a straight path was found to be very difficult.

Time (min) Action Comment 00:00 Fly from 609.6m (2000ft) with IAS

129.64 km/h (70 kt)

02:15 Pull stick back for 45 sec Aircraft stalls 03:00 Release stick Wait for aircraft to settle 11:30 Stop. Save as fly1


129.64 km/h (70 kt) SAS mode engaged

02:30 Pull stick back for 45 sec Aircraft stalls 03:15 Release stick Wait for aircraft to settle 11:45 Stop. Save as fly2


129.64 km/h (70 kt) ATT mode engaged

02:15 Pull stick back for 45 sec 03:00 Release stick Wait for aircraft settle 11:30 Stop. Save as fly3


30

Figure : Pitch response for a impulse elevator deflection

5.5.2 Comparison test analysis. Figure 5.5.2a ,5.5.2b and 5.5.2c show the results from the comparison test in No Autopilot Mode, SAS Pitch Mode and AP ATT Mode respectively. The differences between the three are quite clear from these plots.

Figure 5.5.2a: Results for the flight without Autopilot.

0 10 20 30 40 50 60 70 80 90 100-30

-20

-10

0

10

20

30

X: 33

Y: -9.31

X: 43

Y: 20.9

X: 28

Y: -28.61

X: 61

Y: 17.15

Elv Angle

Pitch Angle


31

Figure 5.5.2b : Aircraft flight in SAS Autopilot mode.

Figure 5.5.2c : Aircraft flight in ATT Autopilot mode.


32

Without the autopilot the elevator deflection looks almost like a square signal which is maintained at a constant value till the control stick is released. Comparing this with the SAS Pitch mode plot, it is possible to see deflections even when the control stick has been held in set position. This is even more visible in the third test when the ATT mode was engaged on the autopilot. Another difference between the three is the amplitude and frequency of oscillations in altitude plot of the three tests. The values for these are given in table 5.5a

Table 5.5a : Results analysis of comparison flight

Figure 5.5.2d . Cmparison Test analyis

Control Stick Pulled

Amp1

No. of osc t1

Frequency ω (rad/s) T (sec)

Fly 1 50.5367 3.020134 14.9 0.42169 45

Fly 2 80.8 2.472527 18.2 0.34523 45

Fly 3 48.7 3.020134 14.9 0.42169 45

Control Stick Released

Amp2

No. of osc t2

Frequency ω (rad/s) Ts (sec)

Fly 1 48.6 11 21.1 0.297781 232.1

Fly 2 49.6 10 21 0.299199 210

Fly 3 4.3 5 22.6 0.278017 113

5.6 Conclusion There wasn‟t much analysis done one the data from the flight simulations because most of these test were done on C172 model in order to get used to the simulator and for the actual UAVs the data would be quite different. The results were however recorded and some examples can be seen in the Appindix B. This was done at an early stage of the project and it was found that the input signals were making the aircraft unstable. It was also for that the data was difficult to analyse as the results were not the perfect step responses which were shown on text books. At that point it was thought that may be a different package could be used to simulated to have more control over the simulation.

CHAPTER 6: SYSTEM IDENTIFICATION

33

CHAPTER 6: SYSTEM IDENTIFICATION 6.1 Introduction In order to get more controlled modelling and simulation different options for system identification tool were researched. Based on the research done U-Dynamics AeroSim Block set seemed to be a good option to use for both simulation and system identification. 6.2 Reasons for choosing AeroSim Blockset The AeroSim seemed to be a very attractive package for modelling and simulation part of the project for the following reasons:

AeroSim offered a wide range of complete aircraft models for Simple upto 6DOF Aircraft models (U-dynamics 2008)

AeroSim could be used on any PC with Matlab/Simulink installed on it. (U-dynamics 2008). This was very attractive as it meant the data can be analysed straight after the simulation was done.

AeroSim offered Visual output to FlightGear Flight Simulator and Microsoft Flight to simulator. (U-dynamics 2008) The block also included an Cessna 172 model for FlightGear demo. This seemed to be a good feature as same model had been tested on Merlin Flight Simulator.

From the research done and looking into different journal articles and conference papers it was found that AeroSim blockset was used for many similar projects.

The blockset was free for Academic and Educational purposes. (U-dynamics 2008)

Based on the above features offered by AeroSim blockset decision to move the simulations from MP521 to AeroSim for system identification was taken. 6.2 Aircraft model configuration problem with AeroSim This was the main problem with using the blockset. The aircraft configuration model for AeroSim was very complex compared to the models used previously. It required the many aerodynamic coefficients which were not used for any of the previous models and therefore were not know. For example the Lift coefficient as a sum of many other coefficients as shown in the equation below.

To determine the coefficients required much deeper understanding of aircraft aerodynamics. The other problem was that to derive these coefficients manually would take a lot of time and would therefore shift the whole aim of the project.


34

The block model for the Cessna 172 was completed even the aircraft configuration was not complete. Figure 6.2a and Figure 6.2b

Figure 6.2a Simulink model designed for C172 using AeroSim Blockset.

Figure 6.2b Response for running the Simulink model


35

6.3 DDATCOM software package Research was done to find some kind of computational tool to derive the coefficient. A software package called DDATCOM was found to be used in some projects that could give these aerodynamic coefficients. Data compendium (DATCOM) had been developed by United States Air Force (USAF) and contained a large collection of information containing of classical aerodynamics and analysis and experimental data. (Jung and Tsiotras 2007). DDATCOM or DigitalDATCOM is an computer database of this information and uses it on to the aircraft model to determine the aerodynamic coefficients. 6.3.1 DATCOM modelling DATCOM used a different set of perimeter for aircraft configuration. In particular it required coordinates for the shape of the aircraft. In order to do so measurements were taken from C172 photograph. This can be seen in figure 6.3a.

After taken the measurements data was put into the DDATCOM aircraft configuration file. Based on this data DDATCOM produced a 3d model of the aircraft as sheen in figure 6.3b. Despite the 3d model looking alright there were some problems within the configuration which caused error and the results for the model could not be accrued. The screen shot of the output file are shown in figure 6.3c

Figure 6.3a: Measurement taken from Cessna 172 photograph (EuroControl, c. 2009) for

DDATCOM.


36

Figure 6.3b: DATCom model for Cessna 172

Figure 6.3c Output file from DDATCOM

It wasn‟t possible to resolve these errors in the due time. DDATCOM did plot some graphs which can be found in Appindix B.


37

6.4 Flight Gear simulation problem The AeroSim blockset contained an example of a C172 model that would simulate in Flight gear package, see figure 6.4a. The problem was that the C172 model was actually in flight gear and therefore could not be used for any other analysis. Also problems were encountered while trying to use this example. Example can be seen in 6.4b.

Figrue 6.4a C172 model simulation in Flight Gear

Figure 6.4b Error while trying to run Flight gear with AeroSim.


38

6.5 Conclusion As can be seen from the previous sections the experience with using the AeroSim did not go very well and no system identification analysis was done unfortunately. The models and configuration files can be found in the CD attached with this report.

CHAPTER 7: CONCLUSION

39

CHAPTER 7: CONCLUSION The aim of this project was to implement and understand the working of MP2028 and to model and simulate the aircraft and the autopilot. Even though the project did not go as planned the following can be listed as the achievements or the positive points of the project.

Better understanding of aircraft control systems.

Familiarisation and implementation of the MP2028g autopilot

Better understanding of working of Merlin Flight simulator

Knowledge of different packages available for simulation. However there are some things that the project did not achieve.

The simulations did not work as planned specially with AeroSim Blockset. This also ended up in lack of analysis.

A linearised model of the pitch dynamics was not designed.

A real flight test did not take place and therefore no real data could be acquired for further analysis.

The move to use AeroSim Blockset made the simulation side of the project more complicated. Also not getting to fly the test plane according to plan was also a de-motivation. If flown the data from the aircraft would have been good for comparison for simulations and broadened the analysis. There was a very useful knowledge gained during the project though and therefore if the project was run again the use of AeroSim Blockset will still be considered but this time he models would be designed specifically for the blockset rather than adapting or converting the models for other packages.

CHAPTER 8: FURTHER WORK AND RECOMMENDATIONS

40

CHAPTER 8: FURTHER WORK AND RECOMMENDATIONS There is a lot of potential work for continuing and improving all aspects of this project. The autopilot has been used in a real flight till now and therefore the full potential of the autopilot has not been tested till date. Therefore there is still some work that can be done in this area. As seen in the report the major problems were related to simulations. It would be recommended to install Matlab/Simulink on the Merlin Simulators. This can be used for more controlled simulations and analysis of aircraft models. It might be possible to integrate the models with AeroSim Blockset. All the open source and freeware software like DDATCOM, Flight Gear, and AeroSim has been included in the project and would help further work related to a similar project.

REFERENCES

41

REFERENCES

BBC News (2009) Robot planes take to the skies [online] available from <news.bbc.co.uk/2/hi/technology/7938522.stm> [12 March 2009]

Becker Avionics (2006) Casper 250 Manual [online] Becker Avionics. Available from <http://www.beckerusa.com/products/images/pdfs/Becker%20Casper%20250%20Manual.pdf> [28 Oct 2008]

Beggs, B. (2009) „BAE Systems: Tornado to Typhoon & UAV‟. Royal Aeronautical Society Lecture delivered on 21 January 2009 at Coventry University Techno Centre

Castle, R. (2008) UAV Built Project 2008. Unpublished dissertation. Coventry University.

Etkin, B. & Reid, L. D. (1996) 3rd edn. Dynamics of Flight. USA: John Wiley & Sons, Inc.

EuroControl (c. 2009) Aircraft Performance Database V2.0 [online] available from <http://elearning.ians.lu/aircraftperformance/Default.aspx> [31 Jan 2009]

Hanger9 (2009) Clipped Wing Taylorcraft ARF (HAN1850): Hangar 9 [online] available from <http://www.hangar-9.com/Products/Default.aspx?ProdID=HAN1850> [March 2009]

Jeti (2005) Jeti Model ADVANCE 90 plus [online] available from <http://www.jetimodel.cz/eng/hlavnien.htm> [Dec 2008]

Kermode, A.C. (2006) 11th edn. ed. by Barnard, R.H. & Philpott, D.R. Machanics of Flight. Harlow: Pearson Education Limited

McLean, D. (1990) ed. by Grimble, M.J. Automatic Flight Control Systems. UK: Prentice Hall International Ltd.

Merlin Products (2007) Arthur Autopilot User Manual, UK: Merlin Products. MicroPilot (2004) MicroPilot Installation Video [DVD] Canada: MicroPilot Model Motors (2006) AXI 5330/18 GOLD LINE [online] available from

<http://www.modelmotors.cz/index.php?page=61&product=5330&serie=18&line=GOLD> [12 Dec 2008]

MSN Encarta (2008) Unmanned Aerial Vehicle [online] available from <http://encarta.msn.com/encyclopedia_701610394/Unmanned_Aerial_Vehicle.html> [27 Oct 2008]

Northrop Grumman (2007a) RQ-4 Block 20 Global Hawk [online] available from <http://www.is.northropgrumman.com/systems/ghrq4b.html> [14 March 2009]

Northrop Grumman (2007b) MQ-8B Army Fire Scout [online] available from <http://www.is.northropgrumman.com/systems/mq8bfirescout_army_gallery.html> [14 March 2009]

Ollero, A; Manza I (2007) 'Introduction' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 1

Raptis, I. A. ; Valavanis, K. P. (2007) 'Airplane Basic Equations of Motion and Open-Loop Dynamics.' In Advances in Unmanned Arial Vehicles. ed. by Valavanis, K. P. The Netherlands: Springer: 49

Remub, V. ; Deeg, C. ; Musial, M. ; Hommel, G. ; Cuesta, F. ; Ollero, A. (2007) 'Autonomous Helicopters.' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 111

UAS Research (2008) „UAS Yearbook 2008/2009‟ [online] USA: University of North Dakota. Available from < http://www.uasresearch.org/home/default.asp?L1=15&a=86> [11 Nov 2008]

REFERENCES

42

UAVSA or Unmanned Aerial Vehicle Systems Association (2008) Unmanned Aerial Vehicle Systems Association What is a UAV? [online] available from <http://www.uavs.org/index.php?page=what_is> [27 Oct 2008]

US OSD (2005) ‘Unmanned Aircraft Systems Roadmap 2005-2030’ [online] USA: Office of Secretary of Defence. Available from <www.fas.org/irp/program/collect/uav_roadmap2005.pdf> [03 Mar 2009]

Jung, D. ; Tsiotras, P. (2007) 'Modeling and Hardware-in-the-Loop Simulation for Small Unmanned Arial Vehicle.' Proceedings from AIAA Infotech@Aerospace 2007 Conference held May 7-10 2007 in California. AIAA 2007-2768, Available from <www.ae.gatech.edu/people/ptsiotra/Papers/infotech07b.pdf> [03 Feb 2009]

BIBLIOGRAPHY

43

BIBLIOGRAPHY Beggs, B. (2009) „BAE Systems: Tornado to Typhoon & UAV‟. Royal Aeronautical

Society Lecture delivered on 21 January 2009 at Coventry University Techno Centre

Etkin, B. & Reid, L. D. (1996) 3rd edn. Dynamics of Flight. USA: John Wiley & Sons, Inc.

Garnell, P. & East, D.J. (1977) Guided Weapon Control Systems. UK: Pergamon Press

Jeti (2005) Jeti Model ADVANCE 90 plus [online] available from <http://www.jetimodel.cz/eng/hlavnien.htm> [Dec 2008]

Jung, D. ; Tsiotras, P. (2007) 'Modeling and Hardware-in-the-Loop Simulation for Small Unmanned Arial Vehicle.' Proceedings from AIAA Infotech@Aerospace 2007 Conference held May 7-10 2007 in California. AIAA 2007-2768, Available from <www.ae.gatech.edu/people/ptsiotra/Papers/infotech07b.pdf> [03 Feb 2009]

Kermode, A.C. (2006) 11th edn. ed. by Barnard, R.H. & Philpott, D.R. Machanics of Flight. Harlow: Pearson Education Limited

Manai, M. ; Desbiens, A. (2005) 'Identification of a UAV and Design of a Hardware-in-the-Loop System for Nonlinear Control Purpose' Proceedings from AIAA Guidance, Navigation, and Control Conference and Exhibit held Aug 5-18 2007 in California. AIAA-2005-6483, Available from <w3.gel.ulaval.ca/~desbiens/publications/IdentificationUAVHardwareInTheLoop.pdf > [19 Feb 2009]

MSN Encarta (2008) Unmanned Aerial Vehicle [online] available from <http://encarta.msn.com/encyclopedia_701610394/Unmanned_Aerial_Vehicle.html> [27 Oct 2008]

NFTC or National Flying Laboratory Center (2007) Flight Laboratory Course for Coventry University. Unpublished booklet. UK: Cranfield University.

Ogata, K. (2002) 4th edn. Modern Control Engineering. USA: Prentice-Hall, Inc. Raptis, I. A. ; Valavanis, K. P. (2007) 'Airplane Basic Equations of Motion and

Open-Loop Dynamics.' In Advances in Unmanned Arial Vehicles. ed. by Valavanis, K. P. The Netherlands: Springer: 49

Remub, V. ; Deeg, C. ; Musial, M. ; Hommel, G. ; Cuesta, F. ; Ollero, A. (2007) 'Autonomous Helicopters.' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 111

UAVSA or Unmanned Aerial Vehicle Systems Association (2008) Unmanned Aerial Vehicle Systems Association What is a UAV? [online] available from <http://www.uavs.org/index.php?page=what_is> [27 Oct 2008]

US OSD (2005) „Unmanned Aircraft Systems Roadmap 2005-2030‟ [online] USA: Office of Secretary of Defence. Available from <www.fas.org/irp/program/collect/uav_roadmap2005.pdf> [03 Mar 2009]

UAS Research (2008) „UAS Yearbook 2008/2009‟ [online] USA: University of North Dakota. Available from < http://www.uasresearch.org/home/default.asp?L1=15&a=86> [11 Nov 2008]

APPENDIX: A

I

APPENDIX A

INITIAL DOCUMENTATION AND INTERIM REPORT

APPENDIX: A

II

Student Surname:

(Family Name)

Bhat

Student Forename:

(Given Name)

Ubaier Ahmad

Course: B.Eng Aerospace Technology

Project Supervisor: Dr. Stephen Hargrave

Project Title: "UAV Stability analysis and gyro stabilisation"

Background: The university is planning to enter the European Students

Competition on Unmanned Aircraft Systems 2009 (ESCO-UAS). The competition requires design and implement an unmanned

aircraft systems that would be able to perform different tasks which include reconnaissance, Pylon Race, Spot Landing etc...

Aims & Scope: The aim of this project is to study and implement a MicroPilot

autopilot which will be used to control the UAV developed by other members of the team. The project will also involve

simulation and analysis of the pitch dynamics of the aircraft model acquired from the Merlin Flight Simulator. This analysis

will be used to design a pitch controller that could be implemented to the Merlin Flight Simulator autopilot so that a

more realistic behaviour of the MicroPilot autopilot could be simulated.

Student Activities &

Output

1. Background reading and introduction to aircraft control

systems and autopilot. 2. Familiarisation with MicroPilot autopilot and Merlin Flight

Simulator. 3. Implement and test the autopilot along with other

systems to be used in UAV. 4. Generate a linearised model of the pitch dynamics of the

aircraft using the flight simulator (system identification). 5. Analyse and design a pitch controller based on the linear

model within Matlab. 6. Write a formal technical report.

Student's signature:

Date:

Supervisor's signature:

Date:

APPENDIX: A

III

GANTT CHART

Ubaier Bhat: UAV Project

40 41 42 43 44 45 46 47 48 49 50 51 52 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

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Academic Deadlines

Project brief submission

Interim progress report

Completed of all practical work

Submission of final report

Project deadlines

Background studies 1 1 1 1

Familiarisation with MicroPilot autopilot and Merlin Flight Simulator. 1 1 1 1

Prepare the Test aircraft 1 1 1 1

Design the Universal control module for both UAVs 1 1 1 1

Installation of FMS and configuration into the designed UAVs 1 1 1

Testing of the UAV 1 1 1

Flight and final reports 1 1 1 1

April MayOctober November December January February March

APPENDIX: A

IV

RISK ASSESSMENT FORM

Name of Student: …Ubaier Ahmad Bhat ……………………. Supervisor Name: …Dr. S Hargrave……………………………….

Student Signature: ……………………………………………………. Supervisor Signature: ………………………………………………

Location of Project: …ALG09……………………………………………….. Date: ……03/11/2008…………………………………………………..

PROCESS/ACTIVITY HAZARDS PERSONS AT RISK ACTION TAKEN

Assembling/Dissembling Autopilot

and related equipment

Electrostatic shock Me Work on electrostatic mat.

Using the Flight simulator Possibility to get hurt if the motion is

on

Me Work with motion off and in presence

of Lab Technicians

Flying the UAV Possibility to get hit by the aircraft. Me other people around the area Only fly in a open space and make

sure that manual override is working

Please return a copy of this form, signed and dated, to Dr. R.J. Rider, Q132, after the project specification has been agreed and before any practical work commences.

Further copies of this form may be obtained from Web location: http://web1.eng.coventry.ac.uk/se_projects

http://web1.eng.coventry.ac.uk/se_projects

http://web1.eng.coventry.ac.uk/se_projects

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COVENTRY UNIVERSITY Faculty of Engineering & Computing

INDIVIDUAL PROJECT PROJECTS FACILITY REQUIREMENTS FORM

Student __Ubaier Bhat___________________________ Supervisor __Dr. S. Hargrave____________________

Course __B.Eng Aerospace Technology_____________ Assistant Supervisor ___________________________

Provisional Title ___UAV Stability analysis and gyro stabilisation_____________________________________

________________________________________________________________________________________________

Project Location __Aerospace Laboratory ALG09___________ (e.g. Laboratory in which your project is primarily based)

Facilities Required: Please indicate the labs, instrumentation, computers, equipment, etc. you expect to use during your project. Also list any specific technician and workshop support, and large revenue expenditure you anticipate. This information will help the support staff. (Continue on the back of the form if required.) Resource Requirements: All resources are based in Aerospace Laboratory (ALG09) Merlin 521 Flight Simulator, UAV control system, UAV building material. Access to Electronics Laboratory (JAG19) will be needed to assemble some of the components.

Student signature________________________ Supervisor signature______________________ Form to be completed by the student. Two copies to be submitted through the Faculty coursework hand-in system. See module deadlines for latest submission date.

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VI

Interim Report

1 Overview

This interim report presents details of my project progress to date. The work on UAV

project started in Week 6 (2008/2009 Academic year) and the progress has been

continuously monitored through weekly meeting with the project supervisor. There

are some minor changes to the original project plan and approach but these do not

affect the overall project progress. These have been discussed in the following

sections

2 Approach

I have divided the project into three main areas:

a) Setting up and testing the autopilot in the test aircraft.

b) Design/analysis of a comparable model to simulate the autopilot.

c) Integrating the autopilot on to the aircraft designed by rest of the UAV team.

3 Results

3.1 Test aircraft Setup

The autopilot was successfully installed on the test aircraft. The aircraft

actuators/servos did response as expected to the setup commands from the

base station.

The test aircraft could not be fully tested because of lack of power supply.

New batteries have been ordered and aircraft will be ready to fly by Week 21.

Apart from studying the manufactures manual for the autopilot I have tried to

gain some knowledge of how PID controls work which is used within the

autopilot.

3.2 System Identification and Modelling

The initial idea was to use the Merlin Flight Simulator for identifying an

autopilot model which would be used to simulate the autopilot for the UAV. I have

tried the following methods to find the system response of the Merlin Flight

simulator’s autopilot:

Method 1: My first method to get the system response was to fly a Cessna

model in the Flight simulator and manually input a step or sine signal. The

problems with this method were that

a) It was difficult to sharp and continuous input.

b) The experiment could not be repeated as it was difficult to get the aircraft

into same conditions.

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VII

c) The aircraft either stabilised very quickly which meant that no short period

oscillations could be logged and the phugoidal oscillations also damped

quickly or the aircraft became unstable and crashed.

Method 2: To overcome the problems in Method 1 I decided use the autopilot

to fly and control the aircraft. In order to get the step response I would let the

autopilot to stabilise the aircraft at the fixed altitude disengage the altitude

hold change the demanded altitude the reengage the autopilot altitude

hold mode. This method gave a better response and the input/output responses

could be seen more clearly. However there were still some problems with this

approach.

a) The experiments could not be repeated because it was difficult to get the

aircraft to be in the same initial condition.

b) It was not possible to remove the effects of the aircrafts on stability from

the autopilots effect from the input/output responses.

To overcome these difficulties the best solution would be to reprogram some

to the modules within the Flight Simulator and to integrate Matlab or similar

software for better system identification. This however is beyond the scope of

my project and will require a greater understanding of electronics and

programming.

From my research I have found a Simulink block (AeroSim) set which could

be used instead of the Merlin Flight Simulator to model the autopilot design.

Advantages of using this blockset are that the simulation can be run from any

PC with Matlab installed on it and blockset also gives more control on how

simulations would be work. No practical work has been done using the

AeroSim till now but the initial models should be ready by Week 22.

Along side the tests and experiments that are mentioned above I have also

gained a better understanding of control systems. I have also looked at

different system identification tools.

3.3 UAV integration

The general dimensions of the autopilot components have been measured.

The some initial arrangements for the Universal Control Module have been

thought about but these can only be finalised after the maximum space

available for the module of both UAVs is received. The construction of the

module will start in by week 21.

4 Summery

I have gained a better understanding of how I will work through rest of the project. I

have also improved my theoretical knowledge of control systems. One of the main

changes on the project is not to use the Flight Simulator responses for developing my

simulation model. However I will still use the Flight Simulator to demonstrate the

results. There has been some delay with flying and testing the model aircraft due to

lack of adequate power supply. However after the new batteries are received the

progress will be accelerated to achieve the targets and deadlines.

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APPENDIX B

FLIGHT TEST

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DATCom plots for Cessna 172 model

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090417 dissertation ubaier

Documents

uav project

dynamics of flight

uav system

unmanned technology

flight tests

flight simulators

flight simulation modals

project aim