harware in the loop simulation uuv ieee

8/10/2019 Harware in the Loop Simulation UUV IEEE

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hardware architectures like: MIPS, PowerPC, SH-4, ARM,

StrongARM, xScale, and x86.

Real Time Framework: The Constellation consists of an

object oriented real time framework that provides capabilities

to interfacing and code generation from a model developed in

MATLAB/Simulink. The Constellation framework is

specified in [6]. The model could be converted in ANSI C++

programming language using all advantages of the objected

oriented programming and yet a high performance. The real

time capabilities are found in a middleware interface,

between the generated code and the real time environment.

The MATLABs real time workshop provides the necessary

elements to perform that relationship.

UUVs Dynamic: One of the first steps to realize an

appropriate simulation consists of the modeling of the

dynamic equations of the Hornet UUV, specified in [4] and

used in this work as a concept prove, due the fact that UUVs

model presents a simpler system of equations appropriate to

develop the necessary software interfaces to be used also by

others UUVs. The Fig. 1 presents the six degrees and the

respective derivatives used by a rigid body and its system of

coordinates in the Hornet UUVs model. Where: is the

linear movement relationship to the longitudinal axis; is thelinear movement relationship to the transversal axis; is the

linear movement relationship to the vertical axis; is the

angular or rotational movement over the axis; is the

angular or rotational movement over the axis and is the

angular or rotational movement over the axis.

The inputs of the system are defined by the following set of

forces: : force applied by lateral thruster, : force applied

by frontal thruster, : force applied by vertical thruster,

: external disturbs or interferences like water

current for instance, linear hydrodynamic drag

force as defined in (1), and studied by [16].

Where:

: Drag coefficient.

: Waters density.

: Projected area of drag.

: Velocity of the surface of drag.

The dynamic equations used to describe the vehicles

movement are developed in accordance with [14]. Taking the

sum of all forces in direction of the respective axis

(X, Y, Z), and solving its equations for acceleration,

presented, respectively, by (2), (3), and (4).

Where:

: Acceleration over X axis.

: Acceleration over Y axis.

: Acceleration over Z axis.

: Velocity over X axis.

: Velocity over Y axis.

: Angular velocity over Z axis.

: Linear hydrodynamic drag forceover the X axis.

: External disturbs over the X axis.

: Linear hydrodynamic drag force

over the Y axis.

: External disturbs over the Y axis.

: Linear hydrodynamic drag force

over the Z axis.

: External disturbs over the Z axis.

: Considering that there are not

disturbances.

: Vehicles mass.

: Vehicles weight in water

(Considering that the buoyancy

force is 0).

And taking the sum of the moments over the axis, it is

obtained the acceleration around that axis presented by (5):

Where:

: Angular acceleration over Z axis.

: Distance between the thrusters 1

(lateral thruster) and 2 (frontal

thruster): Sum of the moments over Z axis

(Considering that there are not

disturbance over Z axis).

: Moment of inertia over Z axis.

Fig. 1. Rigid body and its coordinate system.


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For the simulation purposes those movement equations

contains eight state variables, represented by the vector

and three inputs independently

controlled represented by presented by (6):

=

The transformation matrix presented in (7) is responsible to

convert the output states of the rigid body found in the plant

model into the coordinate values associated to a geographic

reference in the horizontal plan.

To obtain the coordinates in the vertical plan, it is sufficient

to calculate the superposition matrix of .

The Fig. 2 shows the block diagram used to represent the

depth controller. The vehicle receives a command with the

desired depth ( ), it verifies the current depth

( ) and apply an output to the thruster 3 ( ).

Analyzing (4), it is possible to see that the relationship

between the depth and the actuator responsible to adjust it (in

this case, the thruster 3) is simple and linear; therefore a PID

(Proportional-Derivative-Integral) controller is sufficient

[23].

Where:

: Command of depth used by the mission

planner;

: Current depth gathered by the navigation

system;

: Depth error;

: Vertical thruster output;

: Proportional gain;

: Integral gain;

: Derivative gain.

A PID controller is also provided to establish the velocity

control; the velocity is obtained directly from the thruster (T1)

instead the desired velocity produced by the mission planner

This approach is used to minimize problems of accuracy

due utilization of estimated values. The velocity and direction

controller work together where, depending of the current

directions value, it is possible to increase or decrease the

vehicles velocity.

To control the vehicles direction, it was used a slide-mode

control, presented by Fig. 3 and also used by [24], that allows

errors in its sliding layer with about +/- 3 degrees and sliding

function defined by (8).

The direction controller uses the following parameters:

: Direction angle used by the mission

planner;

: Current UUVs direction angle;

: Positive and negative limits used over thethruster output;

: Error gain;

: Error rate gain;

and : Horizontal thrusters output.

The direction controller uses the sliding function presented

by (8), to decrement the error and error rate down to zero.

Where:

: Slide mode function;

: It is a bi-dimensional array with the controllersgains;

: It is a bi-dimensional array that contains the

controllers error and error rate

Hardware In the Loop Simulation Environment: The

Fig. 4 shows a general overview of the HILS architecture

used to assist the development and construction of a semi-

autonomous underwater vehicle. It contains the main

components:

Embedded Hardware: It represents a clone of part of

the hardware used to produce the UUV. The inputs

consists of the forces generated by the environment

(like current, pressure, buoyancy, etc) and the forces

generated by the thrusters; World Model: It consists the model used to represent

the physical world or, more precisely, a very close

representation of where the UUV will operate;

Control Parameters: They are the main and auxiliary

variables used to operate adequately the control

Fig. 2. Block Diagram of the PID depth controller..

Fig. 3. Block Diagram of the slide-mode direction controller.


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algorithms used by the UUV (For example: initial

velocity, initial acceleration, Initial position, erroradjusts for directions, maximum pressure allowed,

etc);

Sensors and Actuators: They represent the components

that allow the inputs and outputs of the system,

respectively. They could be real components

(hardware like compass, inclinometers, temperature

sensors, pressure sensors) or virtual (represented by

input/output files, for instance).

Data Logger: This component is responsible to register

all operations that are using this infra-structure, either

through a partial or total simulation. Only using the log

files and registers produced by this component is

possible to evaluate if a control algorithm is adequate

for the UUV and its environment of operation.

The following steps are necessary to generate a useful code

compatible with the proposal of hardware in the loop

architecture, based in an initial UUV's conceptual model.

To prepare the UUV's control model in Simulink

environment: It consists in the utilization of the

Simulink tool box and its control blocks (like S-

Functions, PID block, Plant block, etc). OBS: Before

the next step, it is important to eliminate any algebraic

loop in the model (algebraic loops occur when an input

port with direct feed through is driven by the output of

the same block, either directly, or by a feedback path

through other blocks which have direct feed through); To convert the prepared UUV's control model in a

suitable software component compatible with the real

time framework adopted. There is a special tool

developed to achieve that objective where is possible

to specify event handlers, allows priority specification

and concurrent code;

To prepare the target environment and to configure

its real time operating system to establish all

necessary connections;

To configure the real time framework to operate

either with the operating system in target machine or

with a simulation environment (environment with the

same interfaces but not considering time restrictions);

To establish connection between the target machine

and the Matlab/Simulink environment using the

middleware provided by Constellation tools;

Trough the Data Logger component and tools like the

Matlab's shell, WindView or Stethoscope, see [17]; is

possible to evaluate and even update values of

monitored variables or statuses in run time to achieve

the timers and specified control conditions;

All generated firmware's code is in ANSI C++ not

allowing the utilization of templates (generic

programming) or even dynamic memory allocation

(temporally to avoid problems with garbage

collection, for instance).

III. RESULTS

The dynamic model and its respective control algorithm,

published in [4], were successfully reproduced in

Matlab/Simulink environment, without any behavioral loss,

even after the elimination of undesired algebraic loops.

The hardware in the loop environment and the UUV's

controller was embedded in a hardware developed in PC104

standard, using x86 architecture, the same configuration

presented by the UUV in development. Virtual sensors and

virtual actuators (like compass, inclinometers, depth's

sensors, thrusters, etc) also had its embedded and real time

representation stored directly into the target's file system.

For all graphs generated, the following procedure was

executed:

All sensors have their values recorded in files. The code generated for the controller reads the value

of those files (sensor values) and, after the necessary

calculus, generates the actuation signals for the UUV's

thrusters.

The actuation signals were also recorded in files, used

later as input for the dynamic simulator. They contain

information about velocity control, direction control,

and depth control.

To compare the results obtained with the implemented

HILS (identified by the label: "Reproduced") against

the adopted bibliographic material (identified by the

label: "Source").

The Fig. 5 shows a direction graph of the path traversed by

the UUV from the start point (point: X=0 and Y=0) in

direction to the point indicated by the beacon (point: X=35

and Y=35). The trajectory performed by the UUV in HILS

environment is similar and compatible with the results

presented by [4].

Fig. 4. Overview of the HILS used to assist the development of UUV.


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more detailed study could be performed to improve that

knowledge area.

ACKNOWLEDGMENT

To our families and friends for encouraging the crowd

standing and successful completion of this work; To FINEP

than through one of its research funds, the CT-PETRO,

allowed some of the funding of this work; To CNPq

(National Council for Scientific and Technological

Development Conselho Nacional de Desenvolvimento

Cientfico e Tecnolgico), for having awarded the scholarship

to complete this Master in Science work, and finally to the

University of So Paulo and their collaborators - who

introduced the graduate program in Mechanical Engineer,

innovating in the environment of academic teaching.

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