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.
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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)
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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.
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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,
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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.
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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.].
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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.
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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Fig. 8.2. Simulation of work of the synthesized model with electric drive
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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.
Marcin Drzewiecki – An Adaptive Control of the Wave in a Towing Tank
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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].
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BIBLIOGRAPHY
[1] A. Iafrati et al., Report of the Specialist Committee on Modelling of Environmental Conditions, Proceedings of 28th ITTC, September 2017, Volume II, Appendix A: QUESTIONNAIRE ON MODELLING OF ENVIRONMENTAL CONDITIONS.
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