Anti swing control strategy for automatic 3 DOR crane system using FLC

Saya:

SESI PENGAJIAN: 2008/2009

RUSLINDA BINTI RUSLEE (840702-11-5024) (HURUF BESAR)

mengah.lI membenarkan tesis (P-SM/Smjana/Doktor Falsafah)* ini disimpan di Perpustakaan dengan syarat-syarat kegunaan seperti berikut:

1. Tesis adalah hakmilik Universiti Tun Hussien Onn Malaysia.

2. Perpustakaan dibenarkan membuat salinan untuk tujuan pengajian sahaja.

3. Perpustakaan dibenarkan membuat salinan tesis ini sebagai bahan pertukaran antara institusi pengajian tinggi.

4. **Sila tandakan(.J)

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Alamat Tetap: SULIT TERHAD TIDAK TERHAD

8793 TAMAN SAMUDRA 21300 SEBERANG TAKIR KUALA TERENGGANU TERENGGANU DARUL IMAN

Tarikh: ,:)--0 / II

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(Mengandungi maklumat yang berdmjah keselamatan atau kepentingan Malaysia seperti yang tennaktub di dalam AKT A RAI-ISIA RASMI 1972)

(Mengandungi maklumat TERHAD yang telah ditentukan oleh organisasi/badan di mana penyelidikan dijalankan)

(T ANDATANGAN PENYELIA J) DR. HJ. JIW A BIN ABDULLAH

EN. JAMALUDIN BIN JALANI Tarikh:

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CAT A T AN:

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Potong yang tidak berkenaan.

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Jika tesis ini SULIT atau TERHAD, sila lampirkan surat daripada pihak

berJ...lIasa/organisasi berkenaan dengan menyatakan sekali sebab dan tempoh tesis ini perlu dikelaskan sebagai SULIT atau TERHAD.

Signature Supervisor I Date

Signature Supervisor II Date

••••••••• ~~.-<' •••••••••••••••••••••••

DR.I 'W-A'.. BIN ABDULLAH

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JAMALUDIN BIN JALANI

RUSLINDA BINTI RUSLEE

A project report submitted as a partial fulfillment

of the requirement for the award of the

Master's Degree in Electrical Engineering

Faculty of Electrical and Electronics Engineering

Universiti Tun Hussein Onn Malaysia (UTHM)

"I declared that this project is the result of my own work except the ideas and references which 1 have clarified their sources" .

Signature ...

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BINTI RUSLEE

Name of Writer

Special dedicated to Ruslee Md Rijin, Mik Wook Salim

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ACKNOWLEDGEMENT

Alhamdulillah, all praise to Allah, the Most Beneficent and the Most Merciful,

who have helped me lots during my research.

First of all, I am greatly indebted to Allah SWT on His blessing to make this

project successful.

I am deeply grateful for the help that I received from my supervisor, Dr. Hj.

liwa Bin Abdullah and Mr. .Tamaludin Bin lalani during this development of this

project. Their efforts in helping in the development of the project, trough technical

difficulties and in search for relevant literature are much appreciated. Not forgetting to

express my appreciation to Mr. Loh Wei Hong form i-Math Sdn Bhd for his helping me

especially in software problems.

A special thanks to my dearest parents and my lovely darling for their love,

support and motivation for me to handle this project. To appreciate their immense

contribution, this thesis is lovingly dedicated to them.

Last but no least, I would like to extend my gratitude to all friends, colleagues

and who helped me directly or indirectly for their encouragement and help. Their views

and tips are useful indeed. Unfortunately, it is not possible to list of them in this

ABSTRACT

The 3 Degree-of-Freedom (DOF) crane represents one of the most widely

deployed real-world platforms in the world today. It uses levers and pulleys for

gripping, lifting and moving loads horizontally, as well as lowering and releasing the

gripper to the original position. Hence the system produces swing angle which need to

be controlled so that the payload could be transferred efficiently. The existing 3 DOF

systems used conventional Linear Quadratic Regulator (LQR) controller to control the

position and swing angle. This project report proposed the usage of Fuzzy Logic

Controller (FLC) in place ofLQR controller. FLC has a simpler and practical design

approached. It avoids laborious mathematical formulation and computation thus

reducing operating time. The FLC performance for position control and anti-swing

control are compared with LQR controller using MA TLAB simulation. The simulation

results showed, under laboratory limitation, that FLC performed better compared to the

ABSTRAK

Kren automaik 3DOF merupakan salah satu kren digunakan secara meluas di

dunia terutamanya di platform industri berat yang mana menggunakan pengumpil, tuil

dan takal bagi mencengkam, mengangkut, mengalih serta menggerakkan beban dari

satu tempat ke temp at lain secara mendatar, menurunkan serta melepaskan beban

tersebut dan kembali kepada kedudukan asal sistem. Oleh yang demikian, perpindahan

beban atau muatan ini pastinya akan menghasilkan sedikit sudut ayunan dan sudut

ayunan ini perlu dikawal bagi memastikan kelancaran kerja pemindahan beban secara

cepat, efektif dan selamat. 3DOF kren ini telah mengamplikasikan sistem kawalan

konvensional yang dikenali sebagai sistem kawalan pengatur kuadratik datar bagi

mengatasi masalah tersebut. Satu sistem altematif iaitu sistem logik kabur dicadangkan

untuk mengatasi masalah ayunan ini dimana ianya mempunyai reka bentuk yang lebih

mudah dan praktikal selain dapat mengurangkan penggunaan matematik yang kompleks

bagi menggantikan sistem kawalan yang sedia ada dan ini dapat mengurangkan

penggunaan masa. Kebolehan sistem logik kabur bagi kawalan posisi dan anti ayunan

ini dibandingkan dengan pencapaian sistem kawalan konvensional iaitu sistem kawalan

pengatur kuadratik datar dengan menggunakan peri sian simulasi MA TLAB. Hasil dari

simulasi membuktikan bahawa sistem logik kabur ini juga merupakan satu sistem

kawalan yang mempunyai potensi setanding dengan sistem kawalan yang sedia ada bagi

INTRODUCTION

The 3 DOF crane represents one of the most widely deployed real-world

platforms in the world today that uses levers and pulleys for gripping, lifting and

moving loads horizontally, as well as lowering and release the gripper back. The task

of the 3 DOF crane is to move the payload from one point to another point. Hence the

system produces swing angle which need to be controlled so that the payload will be

transferred quickly, effectively and safely. The 3 DOF crane is separated into three

subsystems which are payload, jib and tower. To deal with these systems, a lot of

control techniques have been used on the basis of controlling swing angle. Since many

controllers can be used to control the system, therefore the most practical and effective

controller have been investigated to replace and implemented to this 3 DOF crane

system. This project only focuses on controlling jib subsystem. The existing controller

of payload and tower subsystem is still used for the controlling purpose. The

conventional LQR controller is used to control position and swing angle of the 3 DOF

crane. Therefore, the simpler and practical controller approach needs to be applied to

the system known as Fuzzy Logic Controller (FLC). In addition, the FLC is known as a

non-model based controller approach and can fulfill the design method as well as

achieve high performances. The application of Fuzzy Logic Controller in the 3 DOF

crane systems is expected to be better than conventional controllers. The design of

Fuzzy Logic Controller is also minimize the mathematical computation and reducing

time consuming. Hence, FLC is predicted to have simpler design approach and pcrfoml

TABLE OF CONTENTS

CHAPTER TITLE PAGE

ACKNOWLEDGEMENT IV

ABSTRACT V

SYNOPSIS vii

T ABLE OF CONTENTS VIII

LIST OF TABLE XI

LIST OF FIGURE xii

LIST OF SYMBOL XIV

LIST OF ABBREVIATION xvi

LIST OF APPENDICES xviii

CHAPTER I INTRODUCTION

1.1 Project Overview

1.2 Problem Statement 2

1.3 Objectives Project 2

1.4 Scopes project 3

2.1 2.2 2.3 2.4 2.5 CHAPTER III 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 CHAPTER IV 4.1

4.2

Introduction

Related Work

Types of Crane

2.3.1 Gantry Crane

2.3.2 Rotary Crane

2.3.3 Boom Crane

Linear Quadratic Regulator (LQR)

Fuzzy Logic Control System

2.5.1 Fuzzy Control by Mamdani Method

2.5.2 Fuzzy Control by Takagi-Sugeno-Kang Method

2.5.3 Membership Function in Fuzzy Set

METHODOLOGY

Introduction

Modeling the Jib Plant

Fuzzy Logic Controller

Proposed Controller Structure

Basic Concept of Fuzzy Logic Controller

Membership Function of Fuzzy Logic Controller

Fuzzy Rule Base

Fuzzy Inference and Defuzzification

RESULT AND ANALYSIS

Introduction

3DOF Crane Model

CHAPTER V

4.5

4.6

5.1

5.2

System Performance with Fuzzy Logic Controller

System Performance of LQR and FLC

CONCLUSION AND RECOMMENDATION

Introduction

Future Recommendation

ACHIEVEMENT & PUBLICATION

REFERENCES

APPENDICES

46

49

55

56

57

58

TABLE NO TITLE PAGE

3.1

Parameters for jib modeling plant

24

3.2

The generated of rules of position control

35

3.3

The generated of rules of anti-swing control

35

4.1

Perfonnance ofLQR controller for position control

44

4.2

Perfonnance of LQR controller for anti-swing control

45

4.3

Perfomlance of FLC for position control

47

4.4

Perfomlance ofFLC for anti-swing control

48

4.5

Compared perfonnance ofLQR and FLCfor position control

53

LIST OF FIGURE

FIGURE NO. TITLE PAGE

2.1 Gantry crane 8

2.2 Rotary crane 9

2.3 Boom crane 10

2.4 Block diagram ofTSK rules operation 17

2.5 Straight lines of membership function 19

2.6 Gaussian type of membership function 20

3.1 Free body diagram of jib system 22

" j.-') The system block diagram with FLC 25

3.3 Schematic diagram of 3DOF Crane system

using FLC 26

3.4 Elements of Fuzzy Logic Controller 27

3.5 Membership function of position control 29

3.6 Membership function of anti-swing control 31

3.7 Physical movement for the positive force

displacement 33

3.8 Physical movement for the negative force

displacement 34

4.1 Model of 3DOF Crane 38

4.2 The limit switch location for safety trolley

movement 39

4.3 Simulated plot for trolley position without

4.5 Jib system with LQR controller 42

4.6 Trolley position for LQR simulated result 44

4.7 Pendulum swing angle for LQR simulated result 45

4.8 Jib system with FLC 46

4.9 Trolley position for FLC simulated result 47

4.10 Pendulum swing angle for FLC simulated result 48

4.11 Response at 0.1 m step input reference 49

4.12 Response at 0.2m step input reference 50

4.13 Response at 0.3m step input reference 51

A B C D a Y

X _J

rj,pullcy g mtrollcy 17m,} Ktj d(t) rd(t) Yd(t)

8d(t)

LIST OF SYMBOL

state matrix

input matrix

output matrix

direct transmission

motion angle perpendicular jib length

payload angle

current DC motor

position trolley

position of payload from jib

length of payload

position of payload from tower

mass of trolley

radius of trolley pulley from pivot to end of tooth

gravitational

mass of trolley

jib motor equivalent moment of inertia

motor gear ration for jib

jib motor gearbox effIciency

jib motor efficiency

jib motor torque constant

desired position

radial acceleration

rotational acceleration

e

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/lu2 /lx

/lx-~ly

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output swing angle

degree of membership flInction of output for position control

degree of membership function of output for anti-swing control

degree of membership function of error for position control

degree of membership function of error rate for position control

degree of membership function of error for anti-swing control

degree of membership function of error rate for anti-swing

control

maximum operator

minimum operator

CARE COA CW DARE FIS FLC gaussmf gauss2mf gbellmf LQR MF N NB NS P PB PD

LIST OF ABBREVIATIONS

Continuous time Algebraic Ricatti Equation

Centre of Area

clock wise

Discrete time Algebraic Ricatti Equation

Fuzzy Inference System

Fuzzy Logic Controller

gaussian membership function (simple curve)

gaussian membership function (two sided composite of different

curve)

generalized bell membership function

Linear Quadratic Regulator

membership function Negative Negative Big Negative Small Positive Positive Big

trapmf

trimr

TSK Z

tarpezoidal membership function

triangle membership function

Takagi-Sugeno Kang

LIST OF APPENDICES

APPENDIX TITLE PAGE

A 3 DOF CRANE SETUP CODE 61

B 3 DOF CRANE CONFIGURA nON CODE

64

C 3 DOF CRANE CONVERSION CODE

69

D 3 DOF CRANE CALLBACK CODE 70

E 3 DOF CRANE JIB EQUATION 71

F 3 DOF CRANE CLEAR CALLBACK CODE 73

INTRODUCTION

1.1 Project Overview

Crane is a machine that use levers and pulleys for gripping, lifting and moving

loads horizontally, as well as lowering and release the gripper back. It is considered as

one of the most important machines that are being used in industry to transfer loads

from one desired position to another position. These cranes have very strong structures

in order to lift heavy payloads in factories, in building construction, on ships, and in

harbors. These tasks are performed with the aid of hoisting mechanism that works as an

integral part of the crane. Until recently, cranes were manually operated by

professional person. But when cranes became larger and they are being moved at high

speeds, their manual operation became difficult. In factories, cranes speed up the

production processes by moving heavy materials to and from the factory as well as

moving the products along production or assembly lines. In building construction,

cranes facilitate the transport of building materials to high and critical spots. Similarly

on ships and in harbors, cranes save time and consequently money in making the

3 DOF crane was included in the overhead crane types and are widely used in

industry for moving heavy objects. However, the overhead cranes have serious

problems such as the acceleration and always induce undesirable load swing, which is

frequently aggravated by load hoisting. Such load swing usually degrades work

efficiency and sometimes causes load damages and even compromise safety aspects.

From a dynamics point of view, the overhead cranes are under actuated mechanical

systems. The overhead cranes have fewer control inputs than the degrees of freedom,

which complicate the related control problems. The first attempt to control the position

and swing angle of the system is done using classical controller, utilizing LQR method.

However, this conventional controller involved complex mathematical computation

which is time consuming. In this project report, it is proposed to apply FLC mechanism

to overcome the problem of exact position and swing effect.

1.3 Objectives Project

The objectives of this project are:

i) To investigate better control strategy to transfer loads using

Fuzzy Logic Controller.

ii) To investigate better control strategy to suppress swing using

Fuzzy Logic Controller.