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International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, Volume 3, Issue 4, April 2013)

382

Heading Control of ROV ROSUB6000 using Non-linear

Model-aided PD approach R Ramesh

1,6, N Ramadass

2, D Sathianarayanan

3, N Vedachalam

4, G A Ramadass

5

1 (PG Student, Dept of ECE, College of Engineering, Anna University, Chennai, India,)

2 (Associate Professor, Dept of ECE, College of Engineering, Anna University, Chennai, India,)

3, 4, 5, 6 (Scientist, Submersibles & Gas Hydrates, National Institute of Ocean Technology, Chennai, India,)

Abstract— A non-linear model-aided PD approach for

implementing heading control algorithms in the 6000 m depth

rated Remotely Operated Vehicle (ROSUB 6000) has been

developed by National Institute of Ocean Technology, India is

presented in this paper. ROSUB 6000 is developed for

carrying out gas hydrate surveys, poly-metallic nodule

exploration, deep water interventions, bathymetric surveys

and salvage operations. A proper hydrodynamic model is

required in the design of efficient guidance, navigation and

control systems of ROV. Hydrodynamic modeling normally

involves determination of added mass and drags coefficients

from basic principles or scaled down models which are prone

to inaccuracies. The proposed methodology makes use of

vehicle onboard sensors and thrusters for identifying the

vehicle hydrodynamic model parameters. This method is best

suited for variable configuration ROV, where payload and

shape changes with the mission objective. Experiments have

been carried out to identify the hydrodynamic parameters in

heading degree of freedom (DOF). The values are

implemented in the model-based control algorithm aided by

PD control. The heading control loop is found to perform with

a heading maintenance with accuracy better than 2 deg. in the

test environment. The closed loop heading motion is found to

have a time constant of less than 30 seconds.

Keywords— Dynamic modeling, Hydrodynamic modeling,

ROV, ROV Cybernetics, Underwater heading control.

I. INTRODUCTION

The The uses of underwater robotic systems are immensely

useful in various ocean activities. Deep water ROVs such

as ROPOS, Jason, ISIS, UROV 7K, Victor and KAIKO

were developed for exploring ocean resources and carrying

out scientific studies [1].

Fig.1.View of ROSUB 6000 system deployed from ship

In line with these developments, National Institute of

Ocean Technology (NIOT) has developed a 6000 m depth

rated remotely operated underwater vehicle - ROSUB 6000

for carrying out subsea research activities and operations.

The ROV is equipped with two manipulators which can

handle a pay load of 150kg scientific sensor and mission

oriented systems. The system comprises Remotely

Operable Vehicle (ROV), Tether Management System

(TMS), Launching and Retrieval System (LARS), Ship

Systems, Control console, Instrumentation, Control and

Electrical system, Control and operational system [2-4].



383

The ROSUB system was tested up to maximum 5289m

depth in Central Indian Ocean Basin. Fig.1 shows the

overview of the ROSUB system.

The ROV and the TMS are docked together and launched

from the mother vessel using the LARS. A 7000 m of

electro-optic umbilical cable is housed in a hydraulic deck

storage winch and its operation is synchronized with the

LARS. The LARS handles the ROV-TMS system and

transfer the load to the umbilical cable it below the splash

zone. As the system reaches the desired depth, ROV is

undocked out of the TMS. The ROV is propelled by

thrusters and can be operated in any desired direction from

the pilot command from the ship. Manipulators are used to

carry out subsea intervention tasks. After the completion of

the subsea task, the ROV shall be docked back to the TMS

system and TMS-ROV is recovered back to the ship. The

major specification of the ROV in ROSUB 6000 is given

below in TABLE I.

Table I

ROSUB 6000 SPECIFICATIONS

Diving depth 6000 m

Size (Lx H x W) 2.6 x 1.9 x 2 m

Mass 3780 kg in air (-20 kg in water)

Payload Up-to 150 kg

Propulsion Seven BLDC Electrical thrusters

Power 6.6. kV, 460 Hz

Cameras Color, Monochrome and still camera

Lights LED and Halogen lights

Speed 2 knots

Navigational

sensors

Inertial Navigational System aided

with Doppler Velocity Log, Depth

sensor and Underwater positioning

system

Fig.2.Electrical and control architecture of the ROSUB 6000 system

Fig.2 indicates the power and control system architecture of

the ROSUB system in the TMS, ROV and the ship. Ship

power at 415 V and 50 Hz is transformed into 6600 V and

460 Hz using a standard frequency converter and a step up

transformer. Electro-optical connectivity between the ship

and TMS is achieved by 7000 m umbilical cable. The

connectivity between TMS and ROV is realized by the

400m long electro-optic tether cable. Subsea power

converters are used in the TMS and the ROV, which

consist of step down transformer and rectifier to convert the

power into 24V and 300V DC for the subsystems. The

communication between ROV and ship control systems is

established using a single mode fiber optic telemetry

system with wave length of 1310nm in uplink and 1550nm

wave length in downlink [5].

II. ROV DYNAMICS

2.1 ROV Kinematics

The Euler angles were used to compute the vehicle body

fixed linear/angular velocities from the earth fixed linear

and angular velocities. The velocities are used for

calculating the net force acting on the ROV.



384

2.1.1 Linear Velocity Transformation

The vehicle’s flight path relative to the earth-fixed

coordinate system is given by a velocity transformation

equation (1) [6]:

(1)

Where J1 (η2) is a transformation matrix which is related

through the functions of the Euler angles. It is given by:

[

]

Where roll ( ), pitch ( ) and Yaw ( ).

2.1.2 Angular Velocity Transformation

The body -fixed angular velocity v2= [p q r]T and Euler rate

vector (2):

(2)

Where

[

⁄ ⁄

]

Where s. = sin (.), c. = cos (.) and t. = tan (.)

2.2 ROV Kinetics

The dynamic model of the ROV is developed with the

Newton–Euler formulation using laws of conservation of

linear and angular momentum. The equations of motion of

the vehicle are highly nonlinear and coupled due to

hydrodynamic forces which act on the vehicle. The

equations of motion of an underwater vehicle having six

degrees of freedom with respect to a body-fixed frame of

reference can be represented as mentioned in equation (3)

[6]:

(3)

Where

| | MRB and CRB(v) are the rigid body mass matrix and

centripetal matrix, respectively. MA and CA(v) are the

added mass matrix and the matrix, respectively. DL and

DQ|v| are the linear and quadratic drag matrices,

respectively. g( ) is the resultant vector of gravity and

buoyancy. The Coriolis and centripetal terms are negligible

due to low vehicle speed of ROV maneuvering.

Thus, Major forces acting on the vehicle are due to added

mass and damping forces, which are computed with respect

to body frame velocity and acceleration.

2.2.1 Approaches for Underwater Vehicle Dynamics

The motions of underwater vehicles exposed to ocean

currents are usually modeled in six degree of freedom

(DOF) by applying Newton’s second law [6].

The Linear hydrodynamic forces acting on the vehicle are

given by the equations (4) – (6):

[

] (4)

[

] (5)

[

] (6)

The angular hydrodynamic moments acting on the vehicle

are given by the equations (7) - (9):

( )

[ ] (7)

[ ] (8)

( )

[ ] (9)

where X, Y, Z, K, M and N are the forces and moments

acting on the vehicle in six degree of freedom. Even though

precise instrumentation are available for measuring linear

and angular changes[13] of the vehicle, the equations are

very sensitive to centre of gravity (Xg, Yg, Zg), mass with

added mass (m) and inertia due to mass and added mass

(Ix, Iy, Iz) parameters [8]. Accurate determination of these

parameters are a challenging and unsuitable for variable

configuration vehicles [7, 8].

As an alternate method to the classical approach,

researchers at the US Navy’s David Taylor Model Basin

(DTMB) followed a more practical approach [9]. This

approach is presently adopted by the industry for the design

of control systems for under water vehicles [10, 11]. Most

modern studies of marine vehicle dynamics are done using

DTMB equations [12]. DTMB equations represent a finite-

dimensional approximation of the infinite-dimensional

hydrodynamics. The approach is followed by neglecting

off-diagonal entries, coupled terms, tether dynamics in the

6 DOF equations [13]. These simplifications are

empirically justified under the operating conditions



385

characterized by slow velocities and modest attitude

changes typical of this class of work class under water

vehicles [14].

III. NEED FOR DYNAMIC PLANT MODEL

The design of motion control algorithm for under water

vehicles is aimed in attaining high performance in terms of

precision, agility and optimization of the thruster action.

Many different control methods have been proposed to

handle the uncertainties accounting hydrodynamic

parameters and external disturbances [10, 13, and 15]. The

aim of the control strategy is to develop a nominal vehicle

model and an estimate of the dynamic equation parameters

required for both control and state estimation purposes

[16]. Performance improvements in Guidance, Navigation

and Control (GNC) in the ROSUB 6000 system is required

to execute tasks such as high precision hovering in

proximity of the sea bed. This requirement motivated a

deeper investigation in the methodologies for

hydrodynamic modeling and identification of vehicle

parameters.

3.1 Estimation of Hydrodynamic Parametrs Conventional

Methods

Conventional hydrodynamic derivative identification

methods involves towing tanks trials of the vehicle itself in

Planar Motion Mechanism (PMM) or using scaled down

model of the vehicle. PMM methods [6] are costly and time

consuming. Moreover, they are not suitable for variable

configuration vehicles where the experiment needs to be

repeated after any modification for payloads. Scaled down

models test methods involve estimating the hydrodynamic

coefficients of the scaled down model using free decay

pendulum motion tests and the hydrodynamic parameters

are identified by analyzing the time history of motion [15,

17]. By applying laws of similitude, hydrodynamic

parameters of the scaled model can be scaled up to predict

the corresponding values for full scale vehicle. During the

tests the model has to move multiple times faster than the

real vehicle [18]. This poses practical difficulties in

handling the system while carrying out the pendulum decay

tests. Added mass is analytically computed using strip

theory [19] and are prone to inaccuracies as they involve

more engineering judgments. Silvestre et al [20] analyzed

the two afore said conventional methods and they estimated

an error in the estimate of some of the hydrodynamic

parameters up to 50%.

3.2 Proposed Vehicle Fly-Test

Proposed practical approach consists of two steps,

a. Estimation of vehicle drag coefficients by constant

speed tests for a range of velocities.

b. Estimation of moment of inertia due to added

mass by subjecting the vehicle to sinusoidal motion

with reasonable acceleration.

Based on the reported experimental studies of

underwater vehicle dynamics and control [21, 22], ROSUB

6000 vehicle model is optimized based on the following

assumptions,

Vehicle body fixed frame is coincident with the

rigid body Centre of Mass.

Vehicle body fixed frame aligns with principal

axes of inertia.

Vehicle has top-bottom, port-starboard and fore-

aft symmetries.

Vehicle is moving with moderately slow velocities

and undergoing modest attitude changes [6].

By means of the assumptions, off diagonal entries,

coupling terms, tether dynamics are eliminated. The

decoupled equations of motion for the ROV moving

through a fluid in the body frame are written as [11, 13].

These form the basis of DTMB equations (10):

| |

(10)

Where i correspond to each DOF, Ti (t) is the net control

force, mi is the effective mass which includes vehicle mass

and added mass, dQ and dL terms are quadratic and linear

components of hydrodynamic drags, bi is the buoyancy.

Force, velocity and acceleration are measured with respect

to the body frame. The simplified assumptions gives rise to

simple decoupled, single degree of freedom non-linear

dynamical plant model for thruster actuated low speed

maneuvering ROV. By simplifying the equations of

motion, we consider the single degree of freedom motion,



386

motion where the rigid body is only moving in one

direction at a time. We assume that the motion in the other

five DOF is negligible [15, 19].

This paper presents the non-linear model-aided PD

algorithm implemented for automatic heading control of

the ROSUB 6000 vehicle. Experimental identification of a

finite-dimensional dynamical plant model has been carried

out. Experiments were performed to identify the de-

coupled single degree of freedom plant dynamic model in

the heading DOF. The identified vehicle parameters were

used in PD control algorithm for achieving a high

performance closed loop heading control.

IV. ROSUB 6000 ROV

The ROSUB 6000 ROV is a fully actuated vehicle

equipped with seven Brushless Direct Current (BLDC)

motor thrusters with the vehicle freedom in all the six

degrees. Two thrusters each are used for longitudinal and

lateral position control, three thrusters for vertical and two

thrusters for forward and reverse functions. The thrusters

with 214 kgf thrust are driven by BLDC motors and they

feature light weight and high efficiency of operation.

Fig. 3 ROSUB with temporary buoyancy and dimensions (side view)

The BLDC motors are operated by power electronics

controller housed in pressure rated enclosure. The motor

controllers are driven from a 300V DC in ROV. The

thrusters are full ocean depth rated, oil filled and pressure

compensated. The dimensions of the ROV with temporary

buoyancy packs are shown in Fig. 3 and 4.

Fig. 4 ROSUB with temporary buoyancy and dimensions (top view)

4.1 ROV Controller

The National Instruments cFP-2220 controller is an

industrial 400 MHz processor runs with VxWorks real time

operating system (RTOS) for intelligent distributed

applications [23]. The Controller runs with NI LabVIEW

Real-Time software module for control, data logging, and

signal processing. The controller is suitable for applications

requiring industrial-grade reliability, stand-alone data

logging, analog processes, PID control loops, actuating

field devices, perform real-time analysis and simulation,

log data, and communicate over serial and/or Ethernet

ports. A RS-232 serial port and Ethernet ports are used to

interface with external systems. The analog Input and

output module NI-cFP-AIO-610 consists of four analog

inputs and four analog outputs. Four analog (voltage or

current) input channels has ranges up to ± 30 V or ± 20mA.

Four analog voltage outputs with ±10 V range with 12-bit

resolution and 1.4 kHz hardware update rate [24]. Two

analog output modules are interfaced with thruster

controllers to control its speed.

A Photonic Inertial Navigation System (PHINS) is used in

ROV aided Doppler velocity log, depth sensor and acoustic

positioning system. The PHINS is interfaced with ROV

real time controller with the sampling rate of 50ms. The

PHINS provides earth reference linear velocities, positions

and Euler angles for vehicle navigation. Body frame

heading velocity is calculated by differentiating of heading

angle after low pass filtering. It is transformed to body

frame velocity [6] using Euler angles. The details of the

sensors used in ROSUB system is given below TABLE II.



387

Table II

SENSOR USED IN ROSUB 6000 SYSTEM

Vehicle data Sensor Accuracy Update

rate

Depth Para scientific 0.01% 1 Hz

XYZ velocity RDI 600kHz 0.3 % 1 Hz

Roll, Pitch

Heading PHINS 0.01deg 20 Hz

4.2 IDENTIFICATION OF VEHICLE PARAMETERS

4.2.1 Thruster Characteristics

The non-linear thruster characteristics are identified by

experiments at in-house test facility [25, 26]. Thruster is

mounted in a suitably designed fixture with a provision to

measure the thrust generated in water. Thruster control

command is applied from -5V to +5VDC and the thrust

produced in either direction are recorded. Fig. 5 shows the

thruster characteristics are identified using 8015B thruster.

The non-linear thruster behavior is recorded and a lookup

table is generated and implemented in the ROV on-board

real time controller. The experiments were done with the

assumption that the advance velocity Va of the fluid [19]

through the thruster is negligible even though the condition

departs from an unbounded open water body.

Fig. 5. Indentified performance characteristics of ROSUB thruster.

4.2.2 Test Facility and Constraints

Experiments were carried out in in-house test facility which

involves a tank of dimensions 15m (L) x 9m (W) x 7m (D)

and equipped with an overhead crane of 3000 kg.

The following were the constraints in carrying out the

parameter identification requirements in the vehicle,

a. As the fluid is bounded, boundary induced effects such

as refracted waves were observed.

b. Mass of the actual vehicle is 3700 kg. Due to handling

limitations, the syntactic foam was replaced with

make-shift buoyancy thus reducing the vehicle weight

to 2600 kg.

c. Parameter identification could be done only for the

heading DOF due to the limitation in the tank

dimensions.

d. When the thruster characteristics identification is done,

the operation of the thrusters sets the tank water in

motion and thus resulted in advance velocity for

thruster blades [19].

4.2.3 Plant Parameter Identification for Heading DOF

The moment acting in heading DOF is given the equation

(11) [16]:

| | (11)

Where I - Mass moment of inertia due to vehicle and added

mass; v - heading velocity and T - torque.

Parameter identification involves determining the following

parameters for the heading DOF.

a. Moment of inertia due to Added mass.

b. Linear component (DL) and quadratic component (DQ)

of drag force.

To realize this,

1. Constant control command inputs are given to lateral

thrusters of the ROV to identify hydrodynamics drag

parameters.

2. Sinusoidal command is given to lateral thrusters to

identify the Moment of inertia due to Added mass.

-150

-100

-50

0

50

100

150

200

-6 -4 -2 0 2 4 6

Th

rust

(kgf)

Control Voltage (V)



388

V. TESTING AND DETERMINATION OF PLANT

PARAMETERS

5.1 Drag Parameters Identification using Constant Velocity

test

The test was conducted to identifying the drag parameters

of the vehicle in the heading DOF. Constant speed

commands are given to the lateral thrusters of the vehicle

and the steady state heading velocity responses is logged.

The control signal corresponding to the required thrust is

taken from the identified thruster characteristics. The

torque required to move the vehicle at the specific heading

velocity is the energy required to overcome the drag forces

at that specific velocity. The torque recorded is the sum of

linear drag DL and quadratic drag DQ forces. Fig. 6 shows

the steady state angular velocity recorded when a control

command of 1.55 V is given to both the lateral thrusters.

This experiment is repeated for various values of torque

and the corresponding steady state heading velocities are

noted in TABLE III.

The logged data of heading velocity and torque due to the

drag are plotted as shown in Fig. 7 and curve fitting is

carried out. The curve generated value for DL and DQ are

used in the control algorithm for heading DOF.

Fig. 6 Velocity profile recorded when 1.55V control command is applied

to lateral thrusters.

Table III

HEADING ANGULAR VELOCITIES VS TORQUE

Control command

in V

Heading velocity

in rad/sec Torque in Nm

1.04 0.10 42.1

1.33 0.14 84.3

1.55 0.17 126.4

1.68 0.20 168.6

1.94 0.23 210.7

Fig. 7 Heading velocity versus torque in heading DOF

5.2 Determination of Added Mass Parameters

Due to the handling limitations, syntactic foam of ROV is

replaced with temporary buoyancy packs. Required

buoyancy correction was carried out before conducting the

test. ROV vehicle mass was measured using a load cell

with 0.02% accuracy. The mass of ROV is found to be

2604 kg. Fig. 8 shows the ROV with temporary buoyancy

is showed.

0.00

0.04

0.08

0.12

0.16

0.20

1200 1250 1300 1350

Hea

din

g ve

loci

ty (

rad

/s)

Time in seconds

y = 3532x2 + 132.37x

0.0

50.0

100.0

150.0

200.0

250.0

0.00 0.05 0.10 0.15 0.20 0.25

Torq

ue

in N

m

headingvelocity in rad/sec



389

Fig. 8 ROV is being launched in tank with temporary buoyancy

The test was conducted to identify the added mass of the

vehicle in the heading degree of freedom. The added

mass/moment of inertia of underwater vehicles operating

below the water surface is independent of wave excitation

amplitude and frequencies [6, 19]. A sinusoidal control

command (with peak torque corresponding to specific

steady state heading velocity) is given to the lateral

thrusters of ROV and the heading velocity of the vehicle is

recorded. Fig.9 shows a sinusoidal control command with

1/40 Hz frequency given to the lateral thrusters with the

amplitude of given command signal corresponding to

+1.55V to -2.2 V in the forward and reverse directions

respectively.

Fig.9. Sinusoidal control command applied to lateral thrusters

This corresponds to 102.9 Nm torque required to attain a

steady state heading velocity of 0.17 rad/s. But the

measured peak sinusoidal angular velocity is 0.12 rad/s.

(shown in fig10). The measured heading velocity is less

than the velocity recorded during the steady state velocity

test. This indicates that the vehicle requires more torque to

overcome the Inertia due to mass and added mass of

vehicle.

Fig.10. Heading velocity recorded when 1/40 sine signal command

(1.55V) is given to lateral thrusters

To achieve the commanded velocity profile, a thrust

component equal to mass moment of inertia (I) multiplied

by angular acceleration (α) is to be added to the sinusoidal

velocity (thrust) command. Torque difference between the

thrust required for steady state velocity and sinusoidal

velocity for obtaining the specific heading velocity is due

to moment of inertia. The amplitude control command is

increased until the peak heading velocity reaches to the

same velocity when steady state test was carried out. Fig.

11 shows that, a sinusoidal control command with 1/40 Hz

frequency is given to the lateral thrusters with the

amplitude of given signal corresponds to +2.00V to -2.51V

in the forward and reverse directions and corresponding to

126.42 Nm torque.

Fig.11. Sinusoidal control command applied to lateral thrusters

-2.50

-1.50

-0.50

0.50

1.50

1944 1994 2044

Co

ntr

ol

vo

ltag

e in

V

Time in Seconds

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

1944 1994 2044

Hea

din

g v

elo

city

in r

ad/s

Time in Seconds

-2.50

-1.50

-0.50

0.50

1.50

2.50

2300 2320 2340 2360 2380 2400

Con

trol

volt

age

in V

Time in seconds



390

Peak heading velocity of 0.17rad/s is obtained when a

torque of 227.56Nm is applied and the same can be seen

from fig.12.

Fig.12. Heading velocity recorded when 1/40sine signal command (2.00V)

is given to lateral thrusters

The measured peak sinusoidal angular velocity is 0.17rad/s.

The torque difference is 101.36 Nm from steady state

velocity test and Sinusoidal test for attained velocity of

0.17 rad/s. The torque is product of the moment of inertia

(due to vehicle mass and added inertia) and angular

acceleration. Peak heading acceleration is recorded (0.02

rad/s2) during this test as shown in Fig. 13. The mass

moment of inertia due to added mass is found to be 2708.1

kg m2.

Fig.13. Angular acceleration logged when 1/40Hz sine signal applied with

2.00V amplitude.

The following TABLE IV shows that the experimental

results of the Plant parameters computed from the steady

state velocity test and transient velocity test.

Table IV ROV PLANT PARAMETERS

Drag parameters Mass moment of inertia (kg

m2)

DQ DL

3532 132 5057

VI. DESIGN AND IMPLEMENTATION OF HEADING

CONTROL

Generally, PD and PID controls are used in ROV control

[11]. An ROV is a hydro dynamically damped system and

stability is required for smooth maneuvering in low speeds

and hence PD controller is chosen. Identified vehicle

parameters are used in the above equation and closed loop

control is implemented for the heading DOF. PHINS does

not generally provide angular rates but provides earth

reference velocity and Euler angles. From the available

data, body frame angular velocity is computed using

angular transformation [6] for heading control.

6.1 Heading Control Loop Implementation with Vehicle-

Model and PD Control

ROV closed loop control equation for heading is given by

the equation (12):

| |

(12)

Where, v is the heading velocity (rad/sec) with respect to

body frame. The equations involve proportional and

derivative components in addition to the model driven

moments. The heading control loop algorithm is

implemented using LabVIEW as shown in fig.14. The

control algorithm is based on PD control supplemented by

vehicle dynamic model. The output of the vehicle dynamic

model is the sum of the drag force based on the vehicle

body frame velocity and the added mass. The output of the

proportional control is based on the difference in offset

between the set and the actual vehicle heading.

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

2300 2350 2400

Hea

din

g V

elo

city

(ra

d/s

)

Time in seconds

-0.05

-0.03

-0.01

0.01

0.03

0.05

2300 2350 2400

An

gu

lar

Acc

eler

atio

n(r

ad/s

2)

Time in seconds



391

The output of the derivative control is based on the change

in the vehicle velocity.

PD Controller

+

-

+

Inertial

Navigation

System

Input command

ROV

Thrust

allocation

Control

output

Velocity

transformation

Surge, Sway & Heave

Roll, Pitch & Heading

ROV

Dynamics

+

Fig.14. ROV heading control algorithm

6.2 PD Control Tuning and Testing

The damping ratio for a closed loop system is shown in the

equation (13) [11]:

√ (13)

Where, m is the mass of the vehicle, kp is the proportional

constant, kd is the derivative constant and ς is the damping

ratio of closed loop system. The Kp and Kd are tuned based

on the trial error methods [27] so as to obtain the optimal

system response. The values of Kp and Kd are driven based

on the classical rule for linear closed loop systems.The

value of damping ratio is chosen to 0.7 which corresponds

to an under-damped system [6, 19]. With the vehicle-model

algorithm in the operation, the algorithm is tuned for a

range of proportional and derivative constants. The

proportional and the derivative constants are thus found to

be as follows, Kp = 100; Kd = 710.

6.3 Control Algorithm Performance Results

The ROV was at a heading 90 deg and the heading set

point is given as 200 deg. The response of the algorithm for

attaining the set value is recorded and shown in fig. 15.

The ROV heading algorithm is tested for its performance at

different set points. Fig. 16 shows the heading loop

response when predetermined heading command was

given. The vehicle is kept at a constant heading of 120 deg

and displaced to 100 deg. manually. The system response is

shown in Fig.17.

Fig. 15 Heading tracking with given set command

Fig. 16 Heading loop response when it reaches 120 deg from 20 deg

Fig. 17 Heading keeping when external disturbance occur

1.00

1.50

2.00

2.50

3.00

3.50

4.00

1170 1220 1270H

ead

ing i

n r

ad

Time in Seconds

heading in rad

heading set in rad

15

35

55

75

95

115

135

2700 2750 2800

Hea

din

g i

n d

eg

time in seconds

90

100

110

120

130

2900 2950 3000 3050 3100

Hea

din

g i

n d

eg

Time in seconds

Heading keeping at 120 deg

Manual

distr ubance Heading

control



392

It can be seen that for tests that the system had a response

time of 25 and 26 seconds for a disturbance in angles of

100 and 80 deg respectively. The corresponding time

constant is calculated [19] to be 20 and 22 seconds. The

results are found to comply with Nomoto model tests [19]

where in the time constant of 25 seconds was observed for

under water vehicles [16].

VII. CONCLUSION

ROV vehicle parameters are identified for heading degree

of freedom using steady state velocity and transient state

velocity test. Non-linear model based PD approach

algorithm was implemented with identified vehicle

parameters and the heading control functionality was

tested. Heading keeping is tested when external disturbance

introduced in the vehicle. Response of the heading control

is satisfactory maintaining heading with in ± 0.6 degree.

Heading control of ROV will be further tested and

optimized with the actual syntactic foam buoyancy in the

unbounded medium. Parameter identification of surge,

sway, heave, roll and pitch will be identified similarly.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the support extended

by the Ministry of Earth Science, Government of India, in

funding this research. The authors also wish to thank the

members of Submersibles & Gas Hydrates group for their

contribution and support. Authors wish to thank Prof. N

Kumaravel, Head of ECE dept and Dr. P Sakthivel,

associate professor for their encouragement and support.

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international journal of emerging technology and …...international journal of emerging technology...

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