Experimental Buoyancy Control for a Spherical Underwater ...

© 2015 Abdalla Eltigani Ibrahim, open access article. Distributed under the terms of Creative

Commons Attribution (CC BY) license 4.0.

Journal of Control, Robotics and Mechatronic Systems, Vol. 1 (1) 42-52, September, 2015

ISSN: 2379-7207, DOI: pending, Published online: www.unitedscholars.net/archive

Experimental Buoyancy Control for a Spherical

Underwater Robot Vehicle (URV)

Abdalla Eltigani Ibrahim

*1, Mohd Noh Karsiti

2, Irraivan Elamvazuthi

3

Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Perak, Malaysia

*Corresponding author: [email protected]

ABSTRACT

Recently, position control of URVs has been a challenge

due to the buoyancy forces, and high current load of

ocean.

In this paper, the shape of a spherical URV was

presented. The mathematical modeling of variable ballast

tank system and the forces affecting to the controller and

causing some disturbances were discussed by involving

the physical laws.

The URV system was simulated using fuzzy logic

controller and PID controller under downward and

upward vertical motion conditions and the analysis

results shown that both controllers give a good

performance but in term of fast response, the fuzzy logic

controller has produced a better result compared to the

PID controller.

In experimental setup, the prototype was tested and

verified for downward and upward trajectories and an

experimental comparison was carried out. These

promising limitations can be participated in underwater

activities such as, oil exploration, pipelines maintenance

and research explorations.

Keywords: Spherical URV, Buoyancy control, Variable

Ballast system, fuzzy logic control (FLC).

INTRODUCTION

Underwater Robot Vehicles (URVs) have greater

speed, endurance and depth capability. Their

applications in the subsea environment in many

works that difficult for human to do such as

constructing and repairing of subsea systems,

essentially in crude oil, pipelines, cable networks

and data collection for research purposes [1] and

[2]. However, URVs are available in various

designs depending on its application. Slender

shaped design like “a torpedo” is suitable for higher

speed activities, while boxed designs used for

simple directional movement. Thus, spherical

design has benefits of providing a uniform drag in

all directions of maneuvers, when compared with

other designs [3]. On the other hand, The URV

depth position control is based on the analysis of

buoyancy forces. When the URV moves laterally,

zero buoyancy should be maintained. Zero

buoyancy is the condition when the weight force is

equalized by the buoyancy force. Due to the

variations of seawater parameters (e.g. density,

temperature, pressure), different calculations are

often needed for the URV motion, and also for the

zero buoyancy condition. Accordingly, the good

design of URV depth position mechanism is

imperative to provide the balance and stability of

URV against the buoyancy forces.

Variable ballast tank actuator is more efficient in

terms of energy consumption when compared with

a thruster mechanism [4]. In this work, a variable

ballast tank (VBT) mechanism was proposed to

control the buoyancy of spherical URV and to be

used as vertical motion actuator.

1.0 LITERATURE REVIEW

1.1 Variable Ballast Mechanism

From the proposed variable ballast modules, can be

conclude that, the volume of ballast tank is fixed

and some empty space should be left. In case of the

amount of water in the ballast tank is not the

maximum range then the changes in the position of

center of mass of URV will change the pitch or roll

angle of the URV and these changes will disturbs

the stability of the URV that can leads to the

additional internal dynamic changes. This problem

is commonly faced by researchers and caused

Abdalla Eltigani Ibrahim et al, Journal of Control, Robotics and Mechatronic Systems, ISSN: 2379-7207, Vol. 1 (1), 42-52, 09, 2015 DOI: Pending.

43

technical effects in controlling system of the URV

[1].

1.1.1 Pump

Tube pumps based ballast tank mechanism is one of

the simpler and cheapest systems available. The

tube pumps are used to fill the ballast tank with

water or any liquid, in order to control the

buoyancy of the underwater vehicle.

Variable ballast for soft grounding of Autonomous

Underwater Vehicle (AUV) was developed in [4]

and [5]. In this designs, two tanks were used, one in

front and the other at the back of the URV. Then,

two pumps were used to deliver the sea water in or

out of the tanks. Since this mechanism used a fixed

volume of ballast system, the internal dynamic

occurs. Therefore, it is hard to create a controller in

order to stabilize this system.

In tube pump techniques the internal dynamic in

variable ballast tank changes the position of Centre

of mass and disturbs the stability of URV. In

addition to that, in this mechanism, the water flow

control is less accurate and flood time is longer.

1.1.2 Compressed Air

Systems using compressed air to control the water

flow in the ballast tanks are rare to find, because

equipment like magnetic valves and throttles are

complex and costly. Due to the difficulties in exact

valve and throttle control, this system is often used

for rough diving systems.

High pressure air compressor was used in [6], [7].

Compressed air is used to control the amount of

water in the ballast tank. To release the ballast tank,

the high pressure air from the compressor is used to

decrease the amount of water in the tank.

Alternatively, to increase the amount of water in the

tank, the air in the ballast tank will be released; so

water will enter the tank. If, at certain depth, the

water pressure is higher than air compressor, then

the buoyancy cannot be increased. If the URV does

not have vertical propeller, then it not be able to

move to surface. In this mechanism also, if the

water does not fully fill the ballast tank, then empty

space will exist. Hence, this condition causes

internal dynamic that is not easy to be controlled.

1.1.3 Movable Plate

Controlling the buoyancy of underwater vehicle by

movable plate was implemented in [1] and [8]. In

these techniques the piston tank driven by DC

motor contains a power screw attached to the

movable plate at one end and the other end of the

power screw is coupled with the gear mounted on

the DC motor. Therefore, when the DC motor

rotates in the clock-wise direction the power nut

moves outward which allows the blast tank to

create a suction pressure hence water enters inside

the ballast, by which the overall weight of the

system increase and the robot can submerge.

Similarly, when the DC motor rotates in the anti-

clock wise direction the power nut moves inward

which created injection pressure; therefore, the

water stored inside the ballast tank gets flushed out.

In this technique there is no an empty space to

cause internal dynamics when push water in or out

the ballast tank therefore, this system can easily be

controlled.

1.2 Spherical URV Design

There are many types of URVs that are proposed by

the designers and organizations around the world,

like; Dish Type Underwater Robot (DTUR) by

Harbin University in [9]. The control system

module mainly contains the host computer, the

interface driver board, the DC motor drives, stepper

motor drivers, wireless debug interface, depth

sensors, attitude sensors and image sensors. They

carried out some experiments on hydrodynamic

performances to validate the coefficients and make

sure the stability and performance.

A flat-shaped of Autonomous Underwater Vehicles

(AUV) was designed by University of Tokyo in

[10]. But AUV had some problems of an umbilical

cable that may become entangled with other

structures. A symmetric boxed shape underwater

robotic vehicle was designed in [11]. They used

6DOF technique to control the maneuvers in all

directions, but vehicle shape was slow with

underwater effects. A torpedo autonomous

underwater vehicle was designed in [12]. They used

propellers beside Variable ballast tank system to

control the buoyancy of the vehicle.

The sphere shape has many characteristics such as

small size, light weight, high maneuverability and


44

noiselessness. The spherical underwater vehicle

using the movable plate ballast tank technique was

proposed in [1]. They used fixed volume tank

beside the ballast tank to control the buoyancy of

vehicle as shown in Figure 1.

Fig. 1: Shape of Spherical URV and Its Parts

The variable ballast is located at the top of the hull

with the top side open to the water environment.

This design will allow the volume of the water in

the variable ballast to be controlled by the movable

plate while keeping the tank full, whereby

eliminating the concern for water movement that

may affect the overall stability of the URV.

Another design of a spherical URV using movable

plate tank with three independent thrusters for

horizontal movement was developed in [8].

This work puts forward a URV design which

proposed in [1]. Movable plate tank plays as

vertical motion actuator and to fix the problem of

internal dynamic. The URV contains two

waterproof cylinders. One is for ballast tank and

another one is for storage of electrical components

such as, controller, batteries, inertial measurement

and pressure sensors. The mechanism involves a

DC-motor driven piston tank which converts the

rotational motion of the motor to the linear motion

of the piston shaft such that suction and injection of

water flow is created. A dynamic model of variable

ballast tank depth control system will be formulated

base on this prototype design.

1.3 URV Control

The control system of URVs has been reviewed in

several works but nonlinearity of the URV system

becomes a challenge for the researchers to develop

a good controller.

1.3.1 Input-output feedback control

A simple controller can be designed by linearizing

the model of URV by using Taylor series

expansion. This method linearizes the nonlinear

model about steady condition or the equilibrium

point and then if the linearized model is

controllable, a linear feedback controller law can be

designed based upon this linearized model. The

controller of underwater glider was designed in

[13]. In this controller, a nonlinear underwater

glider was modeled for a steady glide path.

Therefore, the linearized model was controllable

and then the linear controller was designed. A

Linear Quadratic Regulator (LQR) was applied by

way of a standard linear optimal control design

method to control an underwater glider based on

the linearized model. Input-output feedback

linearization control for buoyancy control of a

spherical URV which utilizes movable plate in

place of actuator was presented in [14] and [15].

They analyzed the stability of the equilibrium point

using Lyapunov Direct Method (LDM). Full-State

feedback control laws were developed by using the

linear Quadratic Regulator (LQR) and PP (pole

plate) techniques and the observer developed by the

Kalman-Bucy filtering theory.

1.3.2 Neural network

Neural network based-time sliding mode control

was designed in [16]. This controller used to

control a 6 Degree of Freedom (6DOF)

Autonomous Underwater Vehicle (AUV). This type

of control was used with an intelligent neural

network method to dive a variable mass underwater

vehicle in. They discovered that, this technique was

effective at particular region of system behavior

and control structure. An intelligent neural network

method for diving Sliding mode control (SMC) is a

type of variable complicated structure control

which is a combination of subsystem in which each

of it has a fixed control structure and effective at


45

particular region of system behavior.

An intelligent neural network method for diving of

a variable mass underwater vehicle is presented in

[17] and [18]. However, in many cases, the

traditional controllers like PID, Feedback and

neural network controller can be implemented in

any application and perform tasks, but not able to

achieve high accurate buoyancy control for these

reasons; delay in system response, requires high

processing time, difficult to accurately determine

the hydrodynamics, and complex, and sometimes

not practical. In submarine headway control, the

depth and pitch dynamics are highly coupled.

Therefore, the modern controllers, like Fuzzy Logic

Controller (FLC) can be used.

1.3.3 Fuzzy Logic Controller (FLC)

Fuzzy logic control (FLC) is well suited and mainly

applied to nonlinear systems to avoid the local

minima which can cause a vehicle to become

immobilized behind obstacles [19]. Fuzzy logic

controller was applied to motion control of an

Autonomous Underwater Vehicle (AUV) to

command the pump to pump amount of water in the

ballast tank in order to control the buoyancy of the

URV in [20]. Fuzzy logic controller to control the

path following of underwater robotic vehicle was

implemented in [21]. Dynamics of the propulsion

system was regarded by using of both the affine

model of the propeller and the propellers

configuration matrix to determine of thrust

allocation. It makes the algorithms simple and

useful for practical usage.

3.0 SYSTEM MODELING

Knowing the properties of the system such as linear,

nonlinear and stable or not stable are very

necessary to design the controller. In this work the

final dynamic modeling was designed depending on

specified motions equations of URV [1].

V = �̇� (1)

a = V̇ = ΔW

(ms+ma+ΔW

g)

−signal(v)CD Afb ρw V2

2(ms+ma+ΔW

g)

(2)

∆W =ρw g Avb Pm

Km Kgc (Wbs + ∆W + ρw g Avb Z −∆W Avb Pa

ρw g Vin−∆W)

(3)

The prototype’s parameters used to control the

vehicle are listed in Table 1 below.

Table 1 System Parameters

Parameters Sym Value

Atmospheric pressure of

water surface

Pa 1 amt

Density of water Pw 998 kg/m³

Gravitational acceleration g 9.81 m/s²

Transmission ratio of worm

gear and power screw

Kgc 81.64×10³

Coefficient of worm gear

and power screw downward

Kml 0.046×10¯³

Coefficient of worm gear

and power screw upward

Kmu 0.1122×10¯³

Power by dc motor Pm_

max

48 watt

Diameter of variable ballast

tank (VBT)

Dvb 0.13 m

Volume of water inside

(VBT)

kg 0.266 kg

Added mass (ballast

weight) of URV

Ma 8.222 Kg

Diameter of URV Dfb 0.26 m

Projected area of URV Afb 0.053091 m²

Weight of electronic

devices

kg 0.17 kg

Weight of empty ballast

tank with DC motor

kg 0.774

4.0 SIMULATION SETUP

4.1 Fuzzy Logic Controller

In Simulation, Fuzzy Logic Controller is used to

control the depth position of URV as is shown in

figure 2.

Fig. 2: FLC to Control the Depth Position of the URV

4.1.1 Fuzzification

This unit transforms the non-fuzzy input variable

measurements into the fuzzy set variable that is a

clearly defined boundary, without a crisp. For the

fuzzy logic controller, two inputs were used to


46

control the buoyancy of URV, water pressure

(URV’s pressure) and error (error reading).

The input water pressure is defined by linguistic

variables such as high (H), medium (M), normal

(N), medium low (ML), low (L). The input error is

defined by linguistic variables such as large

positive (LP), positive (P), zero (Z), negative (N),

large negative (LN), and characterized by

memberships.

The memberships are curves that define how each

point in the input space is mapped to a membership

value between 0 and 1. The membership functions

Gaussian is implemented for input variables. The

shape is generally less important than the number

of curves and their placement. Five curves are

mapped for each input and output variables in order

to cover the required range as are listed in Figure 3

and 4.

Fig. 3: Fuzzy membership functions of water input (pressure)

Fig. 4: Fuzzy Membership Functions of Input (Error)

The membership functions change gradually from

one state to the next. Table 2 shows the weights of

input membership functions.

Table 2 Weights of the Input Membership Functions

Input Range Function

𝒆

L [0 12.5 25] Gaussian

ML [0 25 50] Gaussian

M [25 50 75] Gaussian

MH [50 75 100] Gaussian

H [75 87.5 100] Gaussian

p

LN [-1 -0.7 -0.4] Gaussian

N [-1 -0.4 0.4] Gaussian

Z [-0.6 0 0.6] Gaussian

P [-0.4 0.4 1] Gaussian

LP [0.4 0.7 1] Gaussian

4.1.2 Decision Making

Fuzzy inference process is realized by the Mamdani

method which can be expressed as a highly non-

linear functional relation using small number of

fuzzy rules. It provides higher performance and

accuracy to non-linear dynamic systems under

various operating conditions.

The output variables of FLC are defined by

linguistic variables such as close fast (CF), close

slow (CS), no change (NC), open slow (OS), open

fast (OF), and characterized by memberships as is

shown in figure 5.

The FLC strategy can be defined from this

equation:

Y = 𝑝 − 𝑒 (4)

Y is output of FLC

p is FLC’s input (pressure)

e is the FLC’s input (error)

The memberships are curves that define how each

point in the output space is mapped to a

membership value between 0 and 1, and triangular

and trapezoidal memberships are used for output

variables.


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Fig. 5. Fuzzy membership function of output

Table 3 shows the weights of output membership

functions.

Table 3 The Weights of the Output Membership Functions

Output Range Function

Movable

Pump

(Y)

CF [-1 -1 -0.8 -0.4] Trapezoidal

CS [-0.8 -0.4 0] Triangular

NC [-0.4 0 0.4] Triangular

OS [0 0.4 0.8] Triangular

OF [0.4 0.8 1 1] Trapezoidal

In this application, the symmetry of the positive and

negative half-waves of the ac variables is used. The

task of this variable would be to switch between

two rule tables at every zero-axis crossing of the

reference.

Table 4 Decision Table for Fuzzy Logic Control Rules

p

LN N Z p LP

𝒆

L CF CF CS CS NC

ML CF CS CS NC NC

M CS CS NC NC OS

MH CS NC NC OS OF

H NC NC OS OF OF

Fig. 6. Control surface of fuzzy controllers

4.1.3 Defuzzification

Fuzzy system is used to control the depth position

of URV depending on the operator. Mamdani

method is used as the inference engine and the

output of the fuzzy system is then used as the time

reference for the DC motor to operate the pump.

When the variable ballast system receives the

buoyancy adjustment command from the operator,

the controller calculates the required ambient

pressure of the URV position and then sends the

pulse width modulation (PWM) signals to the

driver of the DC motor.

5.0 EXPERIMENTAL SETUP

In experimental studies the buoyancy control

technique was used to control the depth position of

the vehicle. The microcontroller, relays, DC motor,

variable ballast tank and pressure sensor were

installed inside URV as shown in Figure 7.

Fig. 7: Block diagram of Experimental Setup


48

5.1 Controller

The Arduino board is an open source

microcontroller development platform based on the

Atmega 328 [22]. The Arduino microcontroller

board which is selected for this research has the

specifications as listed in Table 5.

Table 5 Specifications of Arduino Due Board

Microcontroller Arduino UNO

Operating Voltage 3.3V

Input Voltage

(recommended)

5-12V

Input Voltage (limits) 5-16V

Digital I/O Pins 12 (of which 6 provide

PWM output)

Analog Input Pins 12

DC Current for 3.3V Pin 800 mA

DC Current for 5V Pin 800 mA

Clock Speed 84 MHz

In this study, fuzzy logic controller was designed

and developed in an Arduino UNO board. The

software agent Arduino Due 32-bit open source

software and MATLAB 2013a were used to control

the non-linear buoyancy control of the URV.

Fuzzy rules which are downloaded in the Arduino,

adaptively determine the critical depth points for

ballast adjustment based on a key parameter of the

URV dynamic model.

5.2 Relays

Relays play an important role in the field of modern

electrical engineering and become an essential part

of modern power systems. Relay is an

electrically operated switch, which can be used to

control a circuit by a low-power signal (with

complete electrical isolation between control and

controlled circuits), or where several circuits must

be controlled by one signal. The relay’s

specifications are listed in Table 6.

Table 6 Specifications of the System’s Relay

Operating Voltage (vcc) 3 V

Max Working Current 35mA

Size 5*2.6cm

DC Output ( Max) 30 VDC / 10A

AC Output (Max) 250 VAC / 10A

Fig. 8: URV’s Relays Connections

In this system, the output of the Arduino board is

connected to three relays in order to control the

direction and time running of the DC motor as is

shown in Figure 8.

5.3 DC motor

DC motor is an electro-mechanic machine which is

used to convert electrical power to mechanical

torque and there are many types of DC motor it

depends on the function of each one. In this work a

DC motor is used as mechanical generator to fill or

empty the ballast tank in order to control the

buoyancy of the vehicle. The Specifications of the

DC motor are listed in table 7;

Table 7 DC motor Specifications

Operating Voltage 12 VDC

operating temperature (-40 to +85) °C.

consumption power 50 W

weight (0.23) kg

5.4 Variable Ballast Tank

The variable ballast tank plays as URV’s buoyancy

controller, hence when it filled by water the

buoyancy force will be less than weight force

therefore, the URV will move in downward vertical

motion. When the tank empty from water the

buoyancy force will be greater than weight force

Therefore, the URV will move in upward vertical

motion.

http://en.wikipedia.org/wiki/Electric

http://en.wikipedia.org/wiki/Switch


49

5.5 Pressure Sensor

A high sensitive integrated digital pressure sensor

(MS5803-05BA) was used to measure the control

signals of URV as is shown in Figure 9. Table 8

contains the selected Pressure sensor’s

specifications.

Table 8 Pressure Sensor’s Specifications

Integrated digital pressure

sensor

MS5803-05BA

Operating Voltage (1.8 to 3.6) VDC

Operating current 1 μA

Standby current 0.15 μA

Operating range (0 - 6) bar

Clock 24 bit - 20 MHz

Operating temperature (-40 to +85) °C.

Underwater depth 100 m

Fig. 9: URV’s Pressure Sensor MS5803-05BA

In this study one pressure sensor was used to sense

the pressure inside variable ballast tank, and outside

URV. Digital signals (+3 volts) are sent to the

controller to make comparisons with its logical

program and sends signal to the specific relay to

connect the main power supply to the DC motor in

order to run the motor on clockwise to fill the

ballast tank or to run the DC motor on

anticlockwise to empty the ballast tank from water

as is depicted in Figure 10.

Fig. 10: Final Fabricated Prototype

Fig. 11: URV in Real-Time Experiment

6.0 RESULTS AND DISCUSSION

6.1 Simulation Results

Fuzzy Logic Controller is used to control the

buoyancy of URV. PID is involved to be compared

with FLC to examine the controller response.


50

6.1.1 Open loop Response

A URV system without a controller has been

simulated using MATLAB Simulink as shown in

Figure 12 (a). The results show the simulated

response which is extremely stable but not

controllable. Therefore, a fuzzy logic control as a

feedback controller must be applied in order to

control the system.

(a)

(b)

Time (Secs) (c)

Fig. 12: A URV open loop response

6.1.2 Fuzzy logic control (FLC) Response

The system model in MATLAB/SIMULINK

platform is shown in Figure 13. The simulation

results show the capabilities of the proposed

controller scheme to maintain the output of the

URV in steady state operation conditions without

errors, as shown in Figure 13.

Fig. 13. Fuzzy logic control system response

6.1.3 FLC VS PID

Figure 14 shows the response of proposed

controller based fuzzy logic control and PID

controller. As seen FLC shows very fast response

with acceptable deviation from the reference

compared to PID controller.

Fig. 14: FLC Response Compare to PID Controller

6.3 Comparison Simulation with Experimental

Results

Fig. 15. Comparison between Simulation and experimental

Vertical Motion (Downward) of URV

Change in

weight

Velocity

FLC

Reference

Reference

Depth

Position

Experimental

Simulation

PID

FLC

Reference


51

Fig. 16: Comparison between Simulation and experimental

Vertical Motion (Upward) of URV

Figure 15 and 16 show the comparisons between

real-time setup and simulation setup for downward

and upward vertical velocity. The test was

implemented 24 times in 1 meter underwater depth.

For downward trajectory, the origin position of

URV is at 0 meter from surface, then by applying

positive voltage to DC motor to fill the tank by

water the weight of URV can be increased and URV

can descended from surface by certain velocity.

When the voltage is reset to zero, the URV still

moves with a velocity.

For upward trajectory, by applying negative voltage

to the DC motor to empty the tank the weight can

be decreased and URV can moved up to surface of

a certain velocity.

In comparison results the horizontal effects caused

some difficulties in vertical control of URV and the

differences between experimental curve and

simulation curve clearly can be seen.

7.0 CONCLUSION & RECOMMENDATIONS

This research presents a new control scheme of

VBT system aims to find the solution for buoyancy

control of an underwater vehicle. The study

investigates previous research works in the same

field and adapts the essential elements to combat

the problem. It can be concluded that by using the

proposed spherical URV with variable ballast tank

system the problem can be solved.

The proposed method is based on experimentally

validated techniques, therefore, the URV system

was simulated under different operating conditions

based on fuzzy logic controller and PID controller

and analysis results show that both controllers

relatively gave good performance but in term of

fast response, the fuzzy logic controller produced a

better result as compared to the PID controller.

The performance of the system was tested and

verified in different conditions for downward and

upward trajectories and can be emphasis that, by

using the proposed URV with mentioned

specifications and variable ballast tank system the

studied problem can be solved. The design of the

URV’s hull can be affected by the water pressure

load, therefore, in this research the prototype was

designed well for 5 meter underwater depth.

Moreover, A 8.22 kg of weight can be move up and

down in full controllable motion by consumption

power 48 watt for 17 seconds only, without any

friction loss power or overheat in the DC motor.

These promising limitations can be participated in

underwater activities such as oil exploration,

pipelines maintenance and underwater research

explorations.

Simulation and experimental results are very close.

But there are small differences in the values. These

differences are caused by horizontal effects during

the URV’s task. Therefore, for the future work,

another modern controller could be involved.

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