an adaptive control of the wave in a towing tank

FACULTY OF ELECTRICAL AND CONTROL ENGINEERING

The author of the PhD dissertation: Marcin Arkadiusz Drzewiecki Scientific discipline: Automation, electronics and electrical engineering AN ADAPTIVE CONTROL OF THE WAVE IN A TOWING TANK

Supervisor: Jarosław Guziński, D.Sc, Assoc. Prof.

Auxiliary supervisor: Mohamed Amine Fnaiech, PhD

Gdańsk, year 2020

FACULTY OF ELECTRICAL AND CONTROL ENGINEERING

Summary of PhD dissertation in Polish: W rozprawie przedstawiono system służący do adaptacyjnego sterowania falami, który został wdrożony w basenie holowniczym znajdującym się w Centrum Techniki Okrętowej S.A. Fale są generowane w celu odtwarzania warunków środowiska morskiego podczas badań modelowych. Badania tego typu wykonywane są na modelach obiektów w pomniejszonej skali, w celu prognozowania właściwości obiektów rzeczywistych. Dokładne modelowanie warunków środowiska morskiego ma zasadnicze znaczenie dla zapewnienia bezpieczeństwa ludzi i niezawodności konstrukcji morskich i przybrzeżnych. Przeprowadzone badania wykazały, że dotychczasowe modele zjawisk hydromechanicznych związanych z generowaniem fal w basenie holowniczym CTO nie zapewniają wymaganej dokładności. Z tego powodu należało wdrożyć rozwiązanie automatyki, które umożliwi modelowanie warunków środowiska morskiego z wymaganą precyzją. W oparciu o przeprowadzone badania teoretyczne i eksperymentalne, opracowany został nowy system sterowania adaptacyjnego. Opracowane rozwiązanie zostało zrealizowane z wykorzystaniem systemu wbudowanego, wykorzystującego wysokowydajny mikrokontroler, komunikujący się z aplikacją komputerową. Wdrożone rozwiązanie zostało zweryfikowane eksperymentalnie i przyjęte przez CTO do generowania fal o oczekiwanym widmie z wymaganą dokładnością, przy niskich kosztach realizacji oraz w sposób przyjazny dla eksperymentatora, przy jednoczesnym pominięciu złożonych i nieadekwatnych modeli hydromechanicznych. W rozprawie rozważono również model wywoływacza fal z zaawansowanym wysokowydajnym napędem elektrycznym w miejsce aktualnie stosowanego napędu hydraulicznego. Ponadto, podczas prowadzonych badań opracowano urządzenie ultradźwiękowe do pomiaru profilu fali na powierzchni cieczy, wykorzystujące nowatorski sposób pomiaru profilu fali na powierzchni cieczy, które są przedmiotami Polskiego oraz Europejskiego zgłoszenia patentowego.

Summary of PhD dissertation in English: The dissertation presents the system for adaptive control of waves, implemented in the in the towing tank located in the Maritime Advanced Research Centre, CTO S.A. The waves are generated to model the environmental conditions during hydromechanical model tests. The tests are performed on scaled models to predict the properties of full scale objects. Therefore, accurate modelling of the environmental conditions is essential to secure the human safety and reliability of naval and offshore structures. The research carried out, showed that current models of hydromechanical phenomena related to wave generation in the towing tank do not provide the required accuracy. Therefore, it is expected to solve the problem through the automatic approach in order to model the environmental conditions with required accuracy. In scope of the dissertation, the new adaptive control system with a fuzzy-logic controller has been developed on the basis of the studied theory, established conception and the research carried out. Developed solution has been implemented using the embedded system with the high-performance microcontroller. The embedded system communicates with the computer application. The solution has been experimentally verified and accepted by the CTO to generate expected wave spectra with required accuracy at low realization costs and user-friendly manner with omission of complex and inapplicable hydromechanical models. Additionally, the model of the wave maker with an advanced and high performance electric drive, instead of the currently used hydraulic drive, has been successfully considered. Moreover, as part of the work performed, the method and the ultra-sound device for a wave profile measurement on the surface of liquid, have been developed. The method and the device developed are the subject of a Polish and an European patent application.

Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank

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TABLE OF CONTENTS

1. Introduction, Objectives and Aims of thesis ...............................................................................4

1.1. Introduction .................................................................................................................. 4

1.2. Thesis and Objectives.................................................................................................. 5

2. Theory ........................................................................................................................................7

2.1. Model of waves .................................................................................................................. 7

2.2. Wave maker theory ............................................................................................................ 8

3. Conception .................................................................................................................................9

3.1. Wave generating facilities .................................................................................................. 9

3.2. Wave control system ........................................................................................................ 10

3.4. Conclusions ..................................................................................................................... 10

4. Research ................................................................................................................................. 11

4.1. Introduction ...................................................................................................................... 11

4.2. Identification and modelling of actuators ......................................................................... 11

4.2.1. Linear model of the flap velocity module .................................................................. 12

4.2.2. Linear model of the flap position module ................................................................. 12

4.3. Implementation of model and design of controllers ......................................................... 13

4.4. The Transfer Function ...................................................................................................... 18

4.4.1. Linear Transfer Function .......................................................................................... 18

4.4.2. Secondary phenomena ............................................................................................ 20

4.4.3. Limited realization time of the spectra ...................................................................... 21

4.5. Discussion ........................................................................................................................ 23

5. Solution ................................................................................................................................... 23

5.1. Black-Box Adaptation System (BBAS) ............................................................................ 23

6. Implementation ........................................................................................................................ 25

7. Validation ................................................................................................................................. 26

7.1. Validation ......................................................................................................................... 26

8. Future development ................................................................................................................ 27

8.1. Electric drive conception .................................................................................................. 27

8.2. Implementation of model.................................................................................................. 27

8.3. Simulation of work ............................................................................................................ 28

8.4. Conclusion ....................................................................................................................... 30

9. Summary and conclusions ...................................................................................................... 30

Bibliography ................................................................................................................................. 33


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1. INTRODUCTION, OBJECTIVES AND AIMS OF THESIS

1.1. Introduction

An experiment is of paramount importance for the design and operation of naval and

offshore structures. Especially, due to the impact of survivability of these structures on human life

and safety. Two types of experiments are possible: on real objects and on reduced models. The

experiments carried out on the real objects are the most valuable but often impossible to be

implemented due to their complexity, costs or risks. Therefore, the physical model tests being

carried out in hydromechanics laboratories, occupy a privileged position when predicting the

properties of objects such as ships, oil rigs or wind turbines.

Fundamentally, the model tests carried out at model scale, allow to predict the properties

of the naval and offshore, full scale objects, to improve the human safety and survivability of

constructions.

Moreover, from a scientific and research point of view, a particularly important feature of

physical model tests is the possibility of verification of the developed physical theories.

The naval and offshore objects, in their environmental conditions, are mostly affected by

the wind and waves. The influence of waves is usually of far higher importance, than the influence

of the wind, due to the amount of the wave energy as compared to the amount of the wind energy,

resulting from the difference in water and air density. This influence can result in many undesirable

phenomena, related to the objects, i.a.: flooding the deck, broaching of the propeller, dynamic

load of the hull and equipment and transported goods, manoeuvrability deterioration and

resistance increase. Mentioned phenomena can deteriorate facility’s economic performance and

be unbearable for people located on these objects or even be destructive for the object and

people.

Consequently, physical modelling of waves is an essential part of the process focus on

Modelling of Environmental Conditions (MEC), specific to the working area of the naval or offshore

object. The MEC process is carried out in hydromechanics laboratories worldwide, during model

tests, that are called seakeeping tests which are performed in a reduced scale on the models of

naval and offshore objects subjected to simulated marine conditions influence, i.a.: towed or free

running ships (Fig. 1.1), anchored structures like oil rigs or bottom-mounted structures like wind

turbines.


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Fig. 1.1. The example of seakeeping tests in a hydromechanics laboratory: free running model of a ship

For the needs of the seakeeping model tests, the waves are generated in a wave tanks

equipped with wave makers. The movements of the wave maker actuators, generate waves in

the wave tank. Two basic types of waves can be generated: regular and irregular. The regular

wave is induced by monoharmonic movement of the wave maker actuator. The irregular wave is

induced by multiharmonic movement of the wave maker actuator and is desired to contain the

expected harmonics of Energy Spectral Density (ESD) to reflect the real environmental conditions

in a model scale. The generated irregular waves are consistent with the States of Sea (SS) [2]

desired for seakeeping model tests scenarios.

Measurements carried out during the seakeeping model tests allow an experimental

determination of full scale object properties, in order to improve the human and construction safety

and sustainable development of naval architecture and offshore sectors.

1.2. Thesis and Objectives

The scientific objective of this doctoral dissertation is to solve the complex problem related

to the generation of the waves on the water surface in a wave tank with a required accuracy, for

the needs of the seakeeping model tests to improve survivability of naval and offshore

constructions and therefore human safety.

Waves on the water surface in wave tank are generated as a result of the oscillatory

movements of wave maker actuator. Unfortunately, there is no direct relationship between the

ESD of the generated wave and ESD of movements of the wave maker actuator. This is due to

hydromechanical phenomena, which complexity causes that hydromechanical models are not

sufficiently general and robust. Finally, in order to obtain ESD of generated waves, that reflects

the real environmental conditions with the required accuracy, it was necessary to manually and

iteratively apply corrections to the input signal of the wave maker.


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Moreover, the widely used technique of wave profile measurement was based on the

phenomenon of variable resistance or capacitance between two electrodes immersed into the

water, while the resistance or capacitance depends on the depth of immersion. This common

solution is a nuisance for the user, due to settlement that result in necessity of cleaning the

electrodes and adjusting the amplifier before each use. In addition the probes immersed into the

water were the source and receiver of hydromechanical disturbances, related to the measured

waves.

Each of the hitherto way of generating and measuring the wave was a time-consuming,

high-cost and non-automatic solution based on iteratively cycles of: preparation, generation,

measurement, analysis and correction.

In the scope of this doctoral dissertation newer types of regulation of plant has been

considered and the target one has been developed. The fuzzy-logic controller and the adaptation

module have been implemented to a high performance embedded system with an intuitive

computer application.

A new method and an ultra-sound device for a wave profile measurement have been

invented for the needs of the developed system. The method and the device have been applied

for a Polish patent [44] and, subsequently, for an European patent [45]. The method and device

are based on contactless ultrasonic measurements and thus, it is non-invasive and maintenance-

free.

The entire solution has been worked out and implemented in the hydromechanics

laboratory in the CTO S.A. Maritime Advanced Research Centre. However, both the adaptive

system and the ultra-sound device are a ready-made products that can be broadly implemented

to others hydromechanics laboratories.

The implementation of the objective of the dissertation, solved the significant scientific

and technical problem of MEC in hydromechanics laboratory during the model tests, carried out

for needs of naval and offshore industries.

The novelty and the main contribution of the doctoral dissertation are:

development of a new complete control system of the wave maker for a real towing tank;

development of the fuzzy-logic controller to control the velocity and the position of the wave maker flap;

development of the non-invasive, contactless, and maintenance-free ultra-sound system for

measurement of the wave profile;

development of the robust and sufficiently general method of adaptive wave control based on

the wave spectrum-feedback;

consideration of modern and advanced electric drive of the wave maker.

The thesis of the doctoral dissertation is formulated as follows:

“It is possible to control the energy spectral density of the generated irregular waves, in

an automatic manner with omission of complex and often inapplicable and not robust

hydromechanical models, with use of the adaptive controller.”


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Whereby “the pragmatic attitude that an adaptive controller is a controller with adjustable

parameters and a mechanism for adjusting the parameters” [K. J. Åström and B. Wittenmark,

2013, p. 1], was taken.

The obtained results validated this assumption and brought a number of additional

benefits described along the dissertation.

2. THEORY

2.1. Model of waves

The waves generated in the wave tank, model the SS in a reduced scale. It is done to

reflect the marine conditions to which the real object will be subjected. The SS are selected

according to statistical data for the sea area for which the tested object is dedicated. The

specifying SS with significant waveheight Hs and modal period Tp are presented in Tab. 2.1 [2].

The Hs is an average of ⅓ of highest waves, while the Tp, widely called peak period, corresponds

to highest value of the ESD. For the needs of the model tests, Hs and Tp are precisely determined,

according to statistical data, obtained from meteorological office, depending on sea area

considered.

Tab. 2.1. Significant Waveheights and Modal Periods corresponding to the Sea States in the North Atlantic and North Pacific [2]

SS North Atlantic North Pacific

- Hs [m] Tp [s] Hs [m] Tp [s]

0-1 0..0.10 - 0..0.10 -

2 0.10..0.50 3.3..12.8 0.10..0.50 3.0..15.0

3 0.50..1.25 5.0…14.8 0.50..1.25 5.2..15.5

4 1.25..2.50 6.1..15.2 1.25..2.50 5.9..15.5

5 2.50..4.00 8.3..15.5 2.50..4.00 7.2..16.5

6 4.00..6.00 9.8..16.2 4.00..6.00 9.3..16.5

7 6.00..9.00 11.8..18.5 6.00..9.00 10.0..17.2

8 9.00..14.00 14.2..18.6 9.00..14.00 13.0..18.4

>8 >14.00 18.0..23.7 >14.00 20

The ESD according to modelled SS is calculated using the spectral formulations

calculated as a functions of the harmonic frequency f. It can be done in terms of the statistically

defined parameters of the waves – Hs and Tp. The formulations and cases reflected therein, have

been described by the Specialist Committee of the ITTC organisation [3]. Required accuracy of

physical modelling allows discrepancies between nominal and measured Hs and Tp within ±5%

[4], [32].


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Mostly, two spectra formulations are used for seakeeping model tests: Pierson-Moskowitz

and JONSWAP [2]. The examples of spectra: Pierson-Moskowitz and JONSWAP (γ=3.3),

calculated for 8th SS in North Atlantic (Tab. 2.1.) for model scale equal to 1:30, are shown in

Fig. 2.1 and Fig. 2.2, respectively.

Fig. 2.1. Pierson-Moskowitz Spectrum for 8th State of Sea in North Atlantic for Model Scale equal to 1:30 – the full scale values of Hs=9 m

and Tp=14.2 s scaled into the model scale values of Hs=30 cm and Tp=2.593 s

Fig. 2.2. JONSWAP (γ=3.3) Spectrum for 8th State of Sea in North Atlantic for Model Scale equal to 1:30 – the full scale values of Hs=9 m

and Tp=14.2 s scaled into the model scale values of Hs=30 cm and Tp=2.593 s

2.2. Wave maker theory

Linear Wave Maker Theory (LWMT) was formulated by Havelock [5] and Biésel and

Suquet [6]. This theory defines a relationship between the waves generated on water surface in

wave tank and the oscillatory movements of wave maker actuator. The LWMT states that the

amplitude of generated wave A11 in far field is depend on: wave maker stroke S(z), depth of water

h, height of articulation of the wave maker actuator h0 and wave number k as it shown in general

formulation (2.1) [6]. The far field is understood as test section of wave tank, where amplitudes of

initial disturbances are reduced below one percent of A11. That reduction is obtained at the

distance from the wave maker actuator at least x=3h [6].

�� = 2��

��

�� sinh��ℎ (2.1)

Nonlinear Wave Maker Theory (NWMT) was developed to extend the accuracy of the

wave generation in a 2D Wave Flumes [7]-[11] and for numerical simulation of nonlinear waves

[12]-[20]. However, mentioned studies do not exhausted all phenomena which occurs while wave

generation and propagation in the towing tank equipped with flap-type wave maker considered.

The LWMT covers the process of generating the linear components of waves in the wave

tanks, including the towing tanks. The NWMT covers the process of generating the nonlinear

1/Tp 1/Tp


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components in a 2D wave flumes and numerical simulations. However, the nonlinear component

resulting from the wave maker actuator construction has been theoretically derived [21]. Except

the wave maker theories, the further nonlinear processes and secondary phenomena, can affect

the wave generation and propagation in the wave tank considered. During the laboratory

experiments the numerous processes and phenomena can be observed, i.a.: disintegration of

wave profile, wave damping and wave reflections from the beach and from the structural elements

of the wave tank. This affects the propagation and transformation of the generated waves. The

synthesis of hydromechanical models of these processes and phenomena is too complex, not

robust and not general enough for application.

Nonetheless, for the model tests carried out in the wave tank considered, accurately

modelling of environmental conditions in scope of waving is required. Thus, correct handling of

all these processes and phenomena is vital for proper realization of the MEC.

3. CONCEPTION

3.1. Wave generating facilities

The considered towing tank is of the 270 m length, 12 m width and 6 m depth. There are

three sections along the towing tank: the wave maker section, the test section and the beach

section. The longitudinal profile of the towing tank is presented in Fig. 3.1. It is equipped with the

facilities submerged in water: flap-type wave maker, straighteners, side wave absorbers, rubble-

mound beach. The wave profiles are generated and formed in the wave maker section, to

propagate along the test section at the desired parameters. Ultimately the waves are damped in

the beach section.

Fig. 3.1. Longitudinal profile of the deepwater towing tank equipped with a flap-type wave maker 1,

straighteners 2, side absorbers 3 and rubble-mound beach 4


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3.2. Wave control system

The plant consists of wave generating facilities presented in subsection 3.1. Hitherto

control system, described in [30], [35] and [22], allowed to control the flap movements. However,

it did not use the wave maker theory, discussed in section 2.2 and it did not compensate the

hydromechanical phenomena discussed there. Actually, it was a flap-control system, not a wave

control system. The wave signal was being calculated outside the control system and then

corrected using experience of the wave designer and wave maker operator to predict the control

signal adequate for expected wave. Moreover, this solution causes the necessity to make

corrections manually to compensate the hydromechanical phenomena. This solution was time-

consuming and employee-involving and had to be replaced by the automation system that

allowed for:

control of the flap movements due to the wave maker theory,

automatic compensation the effects of hydromechanical phenomena.

3.4. Conclusions

The experimental and simulation research had to be carried out in order to develop the

control system that reduced the costs of model tests and improved the accuracy of modelling of

environmental conditions.

Firstly, the control system had to be developed to provide the required control of the flap

movements and apply the wave maker theory, presented and discussed in section 2.2. Then, the

automatic compensation of hydromechanical phenomena had to be developed, to provide the

accurate control of the waves.

The numerous hydromechanical phenomena in general in a towing tank, arises from the

processes not covered by the wave maker theory. The particularly considered towing tank is a

physical hydromechanical object located in a hydromechanics laboratory in the CTO S.A. It is

equipped with facilities presented in section 3.1. From the wave propagation point of view, the

facilities improve the properties of the towing tank on the one hand, but each of the facility is the

individual plant, that generates the specific disturbances, on the other hand. Moreover, the

facilities are not ideal but physical – the straighteners, side absorbers and rubble-mound beach

reduce the transverse waves and reflections in the towing tank only to a certain extent. Actually,

the towing tank and the facilities interact together with the nonlinear waves, that model physical

nonlinear environmental conditions. As a result there are the interactions and phenomena with

the elusive or inapplicable model. Despite this, it was necessary to capture the effects of those

interactions and phenomena in an automatic way.

Designed control system had to be developed and implemented using a user-friendly

computer system and subsequently validated.


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4. RESEARCH

4.1. Introduction

The research is related to the physical object – the towing tank equipped with the wave

maker and other wave generating facilities, introduced in the section 3.1. The research technique

combines the model simulation of work together with the experimental research performed on the

object. The model simulation has been carried out in the Scilab/Xcos software. It has been

performed for the model of object, experimentally identified and modelled in the section 4.2. The

experimental research includes the measurements and analyses performed on the basis of the

theoretical formulation derived in accordance with the section 2.2. The research has been carried

out in accordance with the descriptions detailed successively in the current chapter. The results

have been finally discussed in the section 4.5.

4.2. Identification and modelling of actuators

The wave maker consists of two modules of actuators:

electrohydraulic servo valve and stroke piston – the flap velocity module;

variable displacement electropump stroking mechanism and double-acting

hydraulic cylinder with flap immersed in water – the flap position module.

The flap velocity module, consisting of the electrohydraulic servo valve and the stroke

piston, is presented in Fig. 4.1. The flap position module, consisting of the variable displacement

electropump stroking mechanism and double-acting hydraulic cylinder, is presented in Fig. 4.2.

Fig. 4.1. The module of the servo valve with stroke piston controls the velocity of wave maker flap

Fig. 4.2. The module of the variable displacement electropump stroking mechanism and double-

acting hydraulic cylinder controls the position of wave maker flap


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4.2.1. Linear model of the flap velocity module

The input and output signals of the flap velocity module were measured. The measured

signals allow to derive the frequency response of the flap velocity module. It has been presented

in Fig. 4.3. The plots had been drawn with asymptotes of the basic element – an integral term

[40], to derive the parameters of the linear model. The kI1 is the gain factor of the integral term.

Fig. 4.3. Bode plot of the flap velocity module – measurement (red diamonds) and asymptotes of the linear

model (green lines)

Based on the derived parameters of the integral term [40], the linear model of the flap

velocity module has been identified as (4.1) with kI1=10.15.

�1�� = � !

" (4.1)

The electrohydraulic servo valve is proportional [37]. The stroke piston, according to the

working principle [39] was expected to be an integrator. Thus, identified model is justified and

compatible with the physical object.

4.2.2. Linear model of the flap position module

The input and output signals of the flap velocity module were measured. The measured

signals allow to derive the frequency response of the flap position module. It has been presented


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in Fig. 4.4. The plots had been drawn with asymptotes of the basic element – an integral real term

with inertia [40], to derive the parameters of the linear model. The kI2 is the gain factor of the

integral real term. The TI2 is the time constant due to the inertia of the element.

Fig. 4.4. Bode plot of the flap position module – measurement (red diamonds) and asymptotes of the linear

model (green lines)

Based on the derived parameters of the integral real term with inertia [40], the linear

model of the flap velocity module has been identified as (4.2) with kI2=2.48 and TI2=0.15 s.

�2�� = � #

"�"∙% #�� (4.2)

The cylinder is coupled with the wave maker flap submerged in water. The double-acting

hydraulic cylinder, according to the working principle [39], was expected to be an integrator.

Further, the flap submerged in water was expected to be origin of inertia due to the significant

mass of the flap and water [39]. Thus, identified model is justified and compatible with the physical

object.

4.3. Implementation of model and design of controllers

The model derived in accordance with section 4.2, was implemented into the Scilab/Xcos

simulation environment. It allowed to perform the simulation tests necessary to design the most


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reliable wave maker controller. The fuzzy-logic controller of the Mamdani type with the flap-

position feedback and flap-velocity feedback was considered. It was chosen as the target one

due to the prime robustness, greatest stiffness, finest stability and satisfying step-response

parameters, investigated along the dissertation.

The fuzzy-logic controller FLS of the flap velocity and flap position, has been considered.

This type of controller is successfully applied for improving the control performance of various

types of objects, including the electrohydraulic actuators [41]-[43].

The FLS applied to the wave maker actuators has been established with two inputs and

one output. The structure uses the flap velocity signal AX1 and the flap position signal AX2. The

structural diagram of the proposed control system is shown in Fig. 4.5. The first FLS input is the

flap position error FPE, calculated as the difference between the reference flap position signal

AX2r and measured flap position signal AX2. The second FLS input is the flap velocity error FVE,

calculated as the difference between the reference flap velocity signal taken as FPE and the

measured flap velocity signal AX1. The FLS output is the S signal, given to the input of flap velocity

module (I1), that acts the flap position module (I2) to move the flap. The scaling of the input and

output signals is implemented in hardware with use of the signal matching circuits. The scaling

parameters were selected to match the range of the FLS process variables with the thresholds of

the sensors and actuators.

Fig. 4.5. Structural diagram of the flap velocity and flap position fuzzy-logic control system

The following fuzzy sets for input variable FVE have been formulated: Negative Fast NF,

Negative Medium NM, Zero ZO, Positive Medium PM, Positive Fast PF.

Afterward, the following fuzzy sets for input variable FPE have been formulated: Negative Large

NL, Negative Medium NM, Zero ZO, Positive Medium PM, Positive Large PL.

Wherefore, the following fuzzy sets for output variable S have been formulated: Positive Large

PL, Positive Large PL, Zero ZO, Positive Medium PM, Negative Large NL, Negative Medium NM.

The membership functions of the fuzzy sets: mu(FPE), mu(FVE), mu(S), determine the

grade of membership with a fuzzy set formulated for given variable: FPE, FVE or S, respectively.

Flap position moduleFlap velocity moduleFlap velocity and flap position

fuzzy-logic controller


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The Λ-, Γ- and L-type membership functions of fuzzy set have been formulated in

accordance with [27]. The singleton-type membership functions of fuzzy set have been formulated

in accordance with [28].

The membership functions of the input variables – FVE and FPE – are graphically

presented in Fig. 4.6 and Fig. 4.7, respectively.

Fig. 4.6. Graph of the membership functions: Λ-type, Γ-type and L-type, determined to grade the

membership mu of the FVE input variable with the fuzzy sets: NF, NM, ZO, PM, PF

Fig. 4.7. Graph of the membership functions: Λ-type, Γ-type and L-type, determined to grade the

membership mu of the FPE input variable with the fuzzy sets: NL, NM, ZO, PM, PL

The membership functions of the output variable S are graphically presented in Fig. 4.8.


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Fig. 4.8. Graph of the membership functions singleton-type, determined to grade the membership mu of

the S output variable with the fuzzy sets: PL, PM, ZO, NM, NL

The Mamdani fuzzy inference system has been established with a rule base presented

in the Tab. 4.1. The FLS was intended to real-time computing in the embedded system applied

to the wave maker. Thus, the calculations had to be simple and fast. Consequently, the output

membership function and all the operations, were selected to be a plain addition or multiplication,

as follows. The fuzzy implication of the values of membership with the fuzzy sets is performed in

accordance with the algebraic product method. The aggregation of the active rules is performed

in accordance with the algebraic sum method. The defuzzification is performed in accordance

with the output membership function shown in the Fig. 4.8 and with the centre of gravity (CoG)

method [27].

Tab. 4.1. Table of the rules base of the fuzzy inference system

FVE FPE NL NM ZO PM PL

PF PM PM PM PL PL

PM PM PM PM PM PL

ZO NM NM ZO PM PM

NM NL NM NM NM NM

NF NL NL NM NM NM

The simulation of work has been run and the output control surface of the modelled fuzzy-

controller has been plotted as shown in Fig. 4.9.


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Fig. 4.9. Output control surface of the fuzzy-logic controller considered

The stability of the proposed system has been examined in the Lyapunov sense. It has

been done using the procedure of state variable trajectory tracking, that is recommended for

fuzzy-control systems [27], [29]. According to this procedure, a system is stable, if the state

variables tend to the origin from any start state on the phase plan. The examination in Xcos/Scilab

environment has been carried out for the closed-loop system presented in Fig. 4.5. The origin for

the system considered is coordinated as (0.5;0.5). The trajectories have been tracked for given

initial states of FPE and FVE on the phase plan as presented in Fig. 4.10. According to the results

presented in Fig. 4.10, the state variables tend to the origin from all given initial states – thus the

proposed system is stable in Lyapunov sense.

Fig. 4.10. Trajectories for given initial states of FPE and FVE on the phase plane – simulation in

Xcos/Scilab


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Finally, the quality of regulation has been verified for the model of the closed loop-system

with the established fuzzy-logic controller, under the parameters of step response: rise time tn,

setting time tN, settling time tR, overshoot D, oscillating d/D.

The step response is shown in Fig. 4.11. It has been registered for the model of closed-

loop system (Fig. 4.5) with AX2r given as input signal and AX2 given as output signal scaled to

launch the step of 1 m stroke of the flap X2.

Fig. 4.11. Step response of the closed-loop system with fuzzy-logic controller considered – simulation in

Xcos/Scilab

The current model has been chosen as the most reliable due to fine time-parameters of

the step response and acceptable overshoot with oscillating. The fuzzy-logic controller has been

intended for implementation to the real plant.

4.4. The Transfer Function

4.4.1. Linear Transfer Function

The Linear Transfer Function has been investigated under the regular waves generated

with the desired heights of the 5 cm and 10 cm. The desired heights have been generated with

the basic harmonic frequencies from 0.3 Hz to 1.2 Hz with increment of 0.1 Hz. The results of

theoretical calculation for linear model have been compared with the results of the experiment.

Consequently, the theoretical model has been reduced with a factor equal to 0.8. The dropped

amount 0.2 reflects the flow damping that arises from frictions in straighteners and the pressure

drops in slots between the wave maker flap and the towing tank walls [21]. The LTF reduced and

validated for the wave maker considered is shown in Fig. 4.12 and Fig. 4.13. In the Fig. 4.12 it

can be seen that the waves of very low steepness meets the reduced linear model – highly for

tN=0.61 s

tn=0.38 s

0.9

0.1

D=0.19

d=0.3 ּDּ <0.02

tR=1.84 s


19

harmonics within 1 Hz and less for harmonics exceeding 1 Hz, while steepness increase. In the

Fig. 4.13 it can be seen that the waves of moderate steepness meets the reduced linear model

mostly for harmonics within 1 Hz while the discrepancies increase rapidly with increasing

frequency and resulting steepness.

Fig. 4.12. Linear Transfer Function for regular waves of 5 cm height

Fig. 4.13. Linear Transfer Function for regular waves of 10 cm height

As proven in the experiment performed, the reduced linear model is applicable in terms

of linear theory for the towing tank with the wave maker considered, within the regular waves of

low steepness. According to the experimental research carried out in another hydromechanics

laboratory [31], LTF was applicable for regular waves while it was not sufficient for irregular waves

due to lack of the linearity.

The seakeeping model tests, predominantly requires the generation of the irregular

waves with at least moderate steepness. Mostly, the spectral formulations of Pierson-Moskowitz

or JONSWAP are applied [2]. Furthermore, the spectra are applied with limited realization time.

The investigation has been carried out for the mentioned spectra.

The selected results of the experiment performed for the Pierson-Moskowitz spectra and

for the JONSWAP (γ=3.3) spectra, are presented in Fig. 4.14 and 4.15, respectively. It can be

seen, that ETF does not meet the reduced LTF. Moreover, the ETF is not homogeneous for the

spectra of generated and investigated waves.

Fig. 4.14. Empirical Transfer Function for irregular

waves of Pierson-Moskowitz spectrum with desired Hs at Tp=1.667 Hz (red lines) versus reduced Linear Transfer Function (black line)

Fig. 4.15. Empirical Transfer Function for irregular

waves of JONSWAP (γ=3.3) spectrum with desired Hs at Tp=1.667 Hz (red lines) versus reduced Linear Transfer Function (black line)


20

The ETF shapes presented in Fig. 4.14 and Fig. 4.15 seem to be random. To some

extent, the ETF shapes may arise from disturbing the LTF by nonlinear interactions and

secondary phenomena. Besides, the limited realization time, had been suspected to influence the

ETF. To develop the improvement concept, in-depth research had to be performed. All of the

mentioned factors had to be investigated. It has been done in accordance with the descriptions

in the following subsections.

4.4.2. Secondary phenomena

Among the secondary phenomena, observed during the seakeeping model tests, the

following stand out: the wave reflections from the rubble-mound beach, the wave damping along

the towing tank and the breaking and disintegration of wave profile. It can affect the wave profile

and consequently the parameters of the irregular waves. Therefore, the secondary phenomena

had to be experimentally investigated to evaluate this impact.

The investigation has been performed under the regular waves generated with the

desired height of 10 cm and basic frequencies desired from 0.3 Hz to 1.2 Hz with increment of

0.1 Hz.

The reflection coefficient for the rubble-mound beach R, damping coefficient in the test

section D and spectrum spread coefficient averaged for the test section s, are shown –

respectively – in Fig. 4.16, Fig. 4.17 and Fig. 4.18.

Fig. 4.16. Reflection coefficient versus wave

frequencies in the test section for the rubble-mound beach

Fig. 4.17. Damping coefficient versus wave

frequencies in the test section in the towing tank


21

Fig. 4.18. The spectrum spread coefficient versus wave frequencies in the test section of the towing tank

Summarizing the performed investigation of the secondary phenomena, their impact on

the wave profile generation and propagation is related to the frequency of the harmonics. The

investigated phenomena: reflections, damping and spectrum spread, almost do not influence the

harmonics within the frequency of 0.7 Hz – it is visible in the results in Fig. 4.16, Fig. 4.17 and

Fig. 4.18, respectively. However, as the harmonic frequency increases, this impact increases.

According to the mentioned results, the harmonics of 0.8 Hz is moderately affected by the

damping and spectrum spread deterioration, while the harmonics of frequency higher than 0.9 Hz

are highly affected to be damped and deteriorated under the spectrum spread along the test

section of the towing tank.

The results could justify the ETF shapes at the harmonics exceeding the frequency of

0.7 Hz, although the ETF investigated there are inconsistent with the LTF also in scope of the

harmonics within 0.7 Hz (Fig. 4.14 and Fig. 4.15). Accordingly it was assumed that other factor

also affect wave generation or propagation along the towing tank. Consequently, the limitation of

the realization time influence on the realization of wave spectrum, has been investigated in the

following subsection.

4.4.3. Limited realization time of the spectra

The spectra of the irregular waves, are realized in time using the Random Phase Method.

It is a deterministic technique of wave signal generation, that allows to realize the spectrum in the

realization time Tr, according to the expectations. Limited length of the towing tank and expected

reasonable number of measuring runs with model towed along, enforces the limitation of Tr to

applying it as equal to 128 s. On the other hand, the limitation of Tr, causes the increase of Δf

and, consequently, inferior discretization of the control signal [23].

The impact of the limited realization time of the spectra has been investigated. It has been

evaluated under comparison of results obtained for the measured waves of the identity desired

Pierson-Moskowitz spectra with Hs=15.0 cm and Tp=1.667 s, realized in two different realization


22

times Tr of 128 s and 1024 s. The values of the Tp and Hs have been determined from the spectra

of measured signals, shown in Fig. 4.19 and 4.20.

Fig. 4.19. The Pierson-Moskowitz spectrum of

desired Hs=15.0 cm and Tp=1.667 s for the realization time of 128 s – reference (red

continuous lines) and measured (black bars)

Fig. 4.20. The Pierson-Moskowitz spectrum of

desired Hs=15.0 cm and Tp=1.667 s for the realization time of 1024 s – reference (red

continuous lines) and measured (black bars)

The desired values of the Tp and Hs have been compared with the results of the

measurement in the Tab. 4.2. The values with the N and M superscripts are the desired and

measured, respectively. The δTp and δHs mean the relative differences between desired and

measured values of the Tp and Hs.

Tab. 4.2. Summary of the examination results – realization of RA for two given Tr

Tr HsN Tp

N HsM Tp

M δHs δTp Fig. no.

s cm s cm % % % -

128 15.0 1.667 12.8 1.602 -14.7 -3.9 4.120

1024 15.0 1.667 14.5 1.738 -3.3 4.3 4.121

In the Tab. 4.2 it can be seen that the spectrum generated in Tr of 128 s does not meet

the 5% required accuracy of the Hs value [4], [32]. The values of ESD shown in Fig. 4.19 are

noticeably low and the shape of the spectrum is distorted. Meanwhile, the spectrum generated in

the Tr of 1024 s, meets the required accuracy of the Tp and Hs and the values of ESD shown in

the Fig. 4.19 is of the more identity with the desired.

The results justifies the ETF shapes presented above in Fig. 4.14 and Fig. 4.15 for the

irregular waves generated with the realization time limited to 128 s. Apparently the limitation of

the Tr results that the required accuracy of realization of spectrum is not met. On the other hand

the Tr has to be sensible limited. Increasing the Tr from 128 s to 1024 s, would increase of time-

consumption and cost of the seakeeping model test eight-fold, due to increased number of

measuring runs with model towed along the towing tank. Consequently, the limitation of the

realization time is indispensable to realize the seakeeping model tests in reasonable time and

with acceptable costs.


23

4.5. Discussion

The flap movements control system was considered in a few structures and algorithms

with the position-feedback and velocity-feedback, along the dissertation. Among the controllers

established and according to the research carried out there, the fuzzy-logic controller has been

chosen as the most reliable controller. The controller chosen, allows to obtain the best quality of

regulation due to stability and the most reliable step response parameters, presented in section

4.3.

For the reliable control of the flap movements parameters: the velocity and position,

according to the conception discussed in section 3.2, the fuzzy-logic controller established, had

to be implemented and validated.

The ETF determined for irregular waves, significantly differs from the LTF calculated and

validated for regular waves as investigated in the subsection 4.4.1. However, the nonlinear

component does not occur in the spectra of the irregular waves as investigated along the

dissertation. The observed differences between ETF and LTF result from the secondary

phenomena for the harmonics of frequencies exceeding 0.7 Hz as investigated in the subsection

4.4.2 and from the limited realization time for the harmonics of entire frequencies as investigated

in the subsection 4.4.3. Besides, the differences in the ETF and LTF, presented in Fig. 4.14 and

Fig. 4.15, seem to be nondeterministic.

Even advanced control theories to date [33],[34], do not handle the effects of limited

realization time as investigated along the dissertation for the multi-segmented flap-type wave

maker with a force-based absorption.

For the automatic compensation of the undesirable effects mentioned, according to

conception discussed in section 3.2, the solution in form of the adaptive wave spectrum controller

and the non-invasive system for measuring the wave profile, essential for implementation the

wave spectrum-feedback, had to be developed, implemented and validated.

The thesis of the doctoral dissertation assumed that this solution is applicable, as will be

proven below.

5. SOLUTION

5.1. Black-Box Adaptation System (BBAS)

The solution in form of the adaptive control system with a Black-Box model has been

proposed as a recommendation arising from the research carried out in Chapter 4. The Black-

Box approach has been proposed due to the lack of the satisfactory hydromechanical models to

compensate the differences in ETF to the LTF investigated in the subsection 4.4.1. Moreover,


24

there are no satisfactory models to compensate the impact of the disintegration and random

breakdown into adjacent frequencies in consequence of the deterioration of the spectrum spread,

investigated in the subsection 4.4.2. Furthermore, even if the deterministic model would be

developed with certain accuracy, it would be inapplicable due to limited Tr necessary to be

applied. It results in the generated wave profile is out of the control theory due to deterioration of

the frequency resolution, discussed and investigated in the subsection 4.4.3. Therefore, due to

the lack of the robust and sufficiently general model, the well-known and widely discussed

adaptation systems, such as the Model-Reference Adaptation System MRAS [25], [26] were

inapplicable.

The proposed system combines the prediction of the feedforward signal, the control of

the flap movement parameters and finally the adaptive control of the wave spectrum with a wave

spectrum-feedback.

The control system – Black-Box Adaptation System (BBAS) with structural diagram

presented in Fig. 5.1 – consists of the frequency-domain part and the time-domain part. The

frequency-domain part includes the Prediction Mechanism (PM), that uses known amplitude

characteristic of the closed-loop system and LTF, derived from LWMT. It allows to calculate the

predicted feedforward control signal processed into proportional controller (P), that is scheduled

with adjustment mechanism (AM). The time-domain part includes the fuzzy-logic controller (FLS)

of the electrohydraulic servo valve (I1) and hydraulic cylinder (I2) with Black-Box model of the

towing tank (BB). Both parts: the frequency-domain and time-domain are conjugated with the

Fast Fourier Transform blocks: forward (FFT) and backward (IFFT). The BBAS acquires the

desired wave spectrum HWr(ω) and processes the spectrum in PM and P, subsequently, into the

spectrum of the control signal AX2r(ω). The AX2r(ω) is translated into its time-domain equivalent

signal AX2r(t), that is processed to the input of FLS. The FLS controls the parameters of the wave

maker flap movements: the velocity AX1(t) with the flap velocity-feedback from I1 and the position

AX2(t) with the flap position-feedback from I2. The flap movements generate the waves HW(t) in

the BB. The AM calculates the correction function C(ω) for the HWr(ω) acquired at the input of

the BBAS and for the HW(t) translated into its frequency domain equivalent HW(ω) acquired with

the wave spectrum-feedback from BB. The C(ω) is calculated as the ratio of the desired HWr(ω),

divided by the measured HW(ω). It allows to compensate the impact of the secondary phenomena

and to limit realization time to obtain the spectrum of the desired accuracy.

The BBAS approach is expected to solve the problem of the lack of satisfactory

hydromechanical models [24] and limited realization time. It is expected to solve through the wave

spectrum-feedback and adaptive compensation of the effects of all phenomena, that occur while

the wave generation and propagation.


25

Fig. 5.1. Structural diagram of the proposed Black-Box Adaptation System – the frequency-domain part:

prediction mechanism PM and proportional controller P with adjustment mechanism AM, conjugated via

the FFT and IFFT blocks with the time-domain part: fuzzy-logic controller FLS that controls

electrohydraulic servo valve I1 and hydraulic cylinder I2 with Black-Box model of the towing tank BB [23]

6. IMPLEMENTATION

The solution presented in Chapter 5, has been implemented into embedded system

merged with a personal computer application. Implementation of the control algorithm into the

personal computer application as well as the embedded system has been realized using .NET

environment and C# programming language. The embedded system with a Graphical User

Interface (GUI), communicates with the personal computer application. It also communicates with

the wave non-invasive measuring system and with the wave maker sensors and actuators to

acquire the feedback signals.

The solution has been implemented into consistent and user-friendly computer system,

that allows for remote control and monitoring of the wave maker. The way of implementing the

solution greatly reduces the costs due to limited time-consumption and employee-involvement.

Moreover, it allows to improve and streamline operations due to standardization of processes

realized in accordance with the internal procedures of the CTO S.A. [46]-[48] developed by the

Author of the dissertation.

In the next step, the system has been launched and validated under the generation of

waves with required accuracy of ESD, described in section 2.1, due to automatic compensation

the undesirable effects, discussed in section 4.5. It has been performed in accordance with

descriptions in the following chapter.

Flap position module

Flap velocity module

Fuzzy-logic controller Prediction mechanism

Black-Box model

Adjustment mechanism

Proportional controller

Desired wave spectrum

frequency-domain time-domain


26

7. VALIDATION

7.1. Validation

Following the verification carried out in the last section, the operating area has been

described at the ultimate parameters of the wave profiles. The ultimate parameters of the wave

profiles have been chosen as meeting the required accuracy. The operating area described on

the ultimate parameters of the wave profiles of Pierson-Moskowitz spectra, is presented in

Fig. 7.1. The same operating area circumscribed on the ultimate parameters of the wave profiles

of JONSWAP spectra, is presented in Fig. 7.2.

Fig. 7.1. The BBAS operating area circumscribed at the parameters of wave profiles of the Pierson-

Moskowitz spectra modelled with the required accuracy

Fig. 7.2. The BBAS operating area circumscribed at the parameters of wave profiles of the JONSWAP

spectra modelled with the required accuracy

The results presented above indicate that the operating area is limited around. The left

side of the area is limited due to range of motion of the wave maker flap between the mechanical

buffers. The right side of the area is limited due to the wave breaking exceeding the maximum


27

steepness of the wave. The peak of the characteristic is flaten due to the inertia of the wave maker

flap and hydrodynamic loads, as indicated in [36] and analysed in the further subsection 8.2.3.

Nonetheless, the BBAS operating area validated and presented above meets the present and

future expected needs of the CTO S.A. under the seakeeping model tests.

The BBAS has been intended to finely and convenient control of the process of modelling

of the environmental conditions in the towing tank. The validated solution has been successfully

used to conduct of numerous seakeeping model tests for needs of the research and industrial

projects, included navy vessels, special purposes vessels, passenger vessels, container vessels,

gas carriers as well as fishing vessels.

8. FUTURE DEVELOPMENT

8.1. Electric drive conception

Presently, most of the wave makers worldwide are equipped with the hydraulic and

electric driving mechanisms – 43.2% and 51.3%, respectively [1]. In line with the general trend of

increasing the use of electric motors, the new implementations of the wave makers are based on

the electric drives. Among the advantages of electric driven wave makers over hydraulic driven

wave makers, the following can be mentioned:

immediate ability to work without the need for time-consuming heating of the hydraulic oil,

easier maintenance without the need for condition monitoring and periodic change of the

hydraulic oil and elements of the hydraulic installation,

more advanced control of the drives themselves using modern methods and communication

interfaces.

Due to development of the electric drive techniques in recent years [38] and mentioned

advantages, it was purposeful to consider the implementation of an electric drive for the wave

maker in CTO S.A. towing tank. For needs of the current conception and in accordance with the

description in the following sections, the models of drive, transmission and actuator have been

derived and the simulation of work has been carried out. Finally, the system with the electric drive

has been compared with the system with the hydraulic drive under quality of regulation criterion.

8.2. Implementation of model

The model has been implemented in C to the Dev-C++ integrated development

environment. It has been done in accordance with the diagram presented in Fig. 8.1. The PMSM

model with FOC has been considered as follows. The PMSM has been considered as powered

from PWM inverter (INV.) with an impulse period of 0.157 ms and a DC power source of voltage

uDC=1.72 [p.u.].


28

The parameters of the id PI and iq PI controllers have been experimentally tuned as:

Kp=1,Ti=10 and Kp=10,Ti=10 – respectively. The parameters were chosen to obtain the minimum

torque oscillations on the motor shaft with satisfactory system dynamics.

The flap velocity and flap position fuzzy-logic control system FLS has been implemented

in accordance with description in section 4.3. The PMSM rotor velocity ωr is taken instead of

hitherto flap velocity signal. The PMSM rotor position θr is taken instead of hitherto flap position

signal. The ωr and θr are measured using an encoder E.

The FLS output value had to be translated with a scaling factor SF into the reference

current vector on q-axis. The SF has been experimentally chosen as equal to 4.0 to obtain

satisfactory dynamics of the system with an electromagnetic torque not exceeding of 300% of the

rated value at the peak. The simulation results of the implementation and tuning are presented in

section 8.3.

Fig. 8.1. Structural diagram of the flap velocity and flap position fuzzy-logic control system with the electric

drive with FOC type of control method and PMSM type of electric motor powered from the PWM inverter

8.3. Simulation of work

The work of the model implemented in subsection 8.2, has been simulated. The results

are presented in Fig. 8.2. The steps of reference stroke AX2r are given in 0.1 s, 2.5 s and 6.0 s

to test the response of the tuned system. The steps of the thrust torque TR are given in 5.4 s,

5.6 s and 5.8 s to test the system robustness for distortions that may originate from the reflected

waves. The AX2 is the measured flap stroke. The TR is the flap thrust torque reduced to the PMSM

shaft. The W is the shaft velocity of the PMSM. The Te is the electromagnetic torque of the PMSM.

The usd and usq are the stator voltages on d-axis and q-axis of the PMSM, respectively. The isd

and isq are the current vectors on d-axis and q-axis of the PMSM, respectively.

The simulation has confirmed that the system provides the required dynamics and

robustness while the measured values do not exceed the permissible values.


29

Fig. 8.2. Simulation of work of the synthesized model with electric drive


30

The quality of regulation of the fuzzy-logic system with electric drive has been checked

under the parameters of step response. It has been registered for the closed-loop system with

AX2r given as input signal and AX2 given as output signal scaled to launch the step of 1 m stroke

of the flap X2. Thus, the value of the steps are equivalent for two compared systems: the system

with electric drive and the system with hydraulic drive. The step response is shown in Fig. 8.3.

Fig. 8.3. Step response of the closed-loop synthesized model with electric drive – stroke values: desired

(black line) and measured (red line)

8.4. Conclusion

The fuzzy-logic control system of the wave maker flap with the electric drive has been

modelled and simulated. In accordance with the simulation, the system is satisfactorily dynamic

and robust. In accordance with the step response, the system with the electric drive in relation to

system with the hydraulic drive, ensures shorter settling time tR with significantly less overshoot

D and without oscillating d/D. The rise time tn and setting time tN are longer but satisfactory.

The satisfactory results of simulation and numerous advantages of electric drive, testify

that the implementation of the simulated fuzzy-logic system with the electric drive, should be

considered as future solution.

9. SUMMARY AND CONCLUSIONS

The dissertation describes the complete cycle of research and development process,

realized to improve the existing product: the flap-type wave maker in a model basin; and, finally,

to improve the existing service: the seakeeping model tests carried out in hydromechanics

laboratory. The demand to be supplied – the high-performance hydromechanics experiments

realization to improve the maritime safety – was identified. The problem to be solved – the

accurate modelling of waves specific to the type of sea and to the state of sea in a model scale –

tR=1.31 s

tn=0.84 s

0.9

0.1

D=0.02

<0.02

tN=1.41 s


31

was formulated. The available resources – the facilities and the techniques – were

conceptualized. The right research to be accomplished – the experiments and simulations carried

out on the facilities and models – were realized and analysed. The solution hypothesized to

develop and implement – the BBAS approach to modelling of the maritime environment conditions

in a model scale with required accuracy – was fulfilled. Finally, the solution was validated. The

future development conception – the use of high-performance electric drive – was considered and

modelled with a great results.

The greatest achievements of the doctoral dissertation are:

improvement of an existing product – the flap-type wave maker – through a

development of a new complete control system with a wave spectrum-feedback

(BBAS) for a real towing tank in the hydromechanics laboratory;

improvement of an existing service – significant facilitate the seakeeping model

tests – provided to the maritime industry to improve the maritime safety;

development of the fuzzy-logic controller to control the velocity and the position

of the wave maker flap, ready-made for broad distribution within BBAS to

hydromechanics laboratories;

development of the non-invasive, contactless, and maintenance-free ultra-sound

system for measurement of the wave profile, applied for a patent and ready-made

to broad distribution for a wave profile measurements;

improvement of the Quality Management System of the Maritime Advanced

Research Centre, CTO S.A.

The significant achievement of the doctoral dissertation is the supply of the complete

control system that allow to model the environmental conditions with high accuracy in a time-

efficient, low-cost, user-friendly and an automatic manner. It greatly contributes to perform the

seakeeping model tests in the Maritime Advanced Research Centre, CTO S.A. It allows to

determine accurately the properties of the naval and offshore objects to improve the human safety

and survivability of the constructions. This unique solution has been already used in the research

and commercial projects of different vessels for numerous clients – domestic and international.

The projects included navy vessels, special purposes vessels, passenger vessels, container

vessels, gas carriers as well as fishing vessels.

Another significant achievement of the dissertation is that the control system developed,

is a ready-made for broad distribution as a catalogue product of the Maritime Advanced Research

Centre, CTO S.A to another hydromechanics laboratories. 61.1% of the wave makers in towing

tanks worldwide are single unit and 43.2% are equipped with hydraulic driving mechanism [1],

such as the one considered in the dissertation. The modernization of these research facilities can

be low-costly carried out to make them the user-friendly, time-efficient and low employee-offload.


32

Moreover, the implementation of the developed system to the control of the fully electric drive with

a multi-segmented flap is easy to execute. This is of great importance due to the fact that 51.3%

of the wave makers in towing tanks worldwide are equipped with electric driving mechanism [1]

and the use of electric drives constantly increases.

The method and the ultra-sound device for a wave profile measurement on the surface

of liquid, were developed and implemented within the works related to the dissertation. It is the

subject of a Polish and an European patent application [44], [45]. The method and the device

developed are the ready-made products for a wave profile measurements and can be also broadly

distributed as a catalogue product of the Maritime Advanced Research Centre, CTO S.A.

The solution developed under the dissertation, enabled the Author to develop the

procedures [46]-[48]. The procedures were incorporated as the internal documents included in

the Quality Management System of the Maritime Advanced Research Centre, CTO S.A., certified

under ISO 9001:2015. Hence, the works within the dissertation, also improved the Quality

Management System of the research centre.

Besides, due to the resources available in the deepwater towing tank, the hydraulic drive

was applied within the dissertation. From the point of view of the general trend, the PMSM is more

worth considering as the wave maker drive. To date, the 51.3% of wave makers worldwide are

equipped with the electric driving mechanism, versus the 43.2% equipped with the hydraulic one

[1]. According to the trend the number of the electric drive applications is expected to increase.

Thus, within the future works it is recommended to apply the electric drive and insight into more

advanced solutions for improvement of the model tests different than the typical seakeeping tests

at a desired state of sea in a model scale.

Among the more advanced methods related to modelling of environmental conditions, the

worthy of future consideration are:

the active absorption of the waves to further shorten the time interval between

subsequent realizations, needed to calm the water [1];

multi-segmented flap for the active absorption of transverse waves instead of the

straighteners to shorten the wave maker section and lengthen the test section of

the towing tank;

method to suppress the nonlinear components, that would be unintended while

the monochromatic waves generation [21];

sensorless drive to control the flap-velocity and flap-position at reduced costs and

reduced maintenance [38].


33

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an adaptive control of the wave in a towing tank

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