control of gantry crane system based on fuzzy...
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CONTROL OF GANTRY CRANE SYSTEM BASED ON FUZZY LOGIC
TECHNIQUE
AZLIA BINTI ABDUL RAHMAN
A project report submitted in partial fulfilment of the
requirements for the award of the degree of
Master of Engineering (Electrical – Mechatronics and Automatic Control)
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
JANUARY 2013
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To my beloved family, lecturers and friends who have given me a lot of support and
encouragement. Thank you so much.
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ACKNOWLEDGEMENT
Alhamdulillah, I am greatly indebted to Allah SWT for His blessings and His
power.
I would like to take this opportunity to express my gratitude to my project
supervisor, Dr. Abdul Rashid bin Husain for guiding & giving me lots of idea in
order to complete this project.
Support and technical assistant from the industry sector from Siemens
Malaysia SDN. BHD, Mr. Amiruddin Zahamail, which support me throughout these
thesis should also be recognized for his sponsorships – he has provided assistance at
various occasions and technical supports. His brilliant ideas and opinion are very
useful.
Last but not least, I would like to give a special thanks to my parent and
family for their love, understanding, support and bless. I really love them so much.
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ABSTRACT
Gantry cranes are widely used in industry for transporting heavy loads and hazardous
materials in shipyards, factories, nuclear installations, and high building construction.
The crane should move the load as fast as possible without causing any excessive
movement at the final position. However, most of the common gantry crane results in
a swing motion when payload is suddenly stopped after a fast motion. The swing
motion can be reduced but will be time consuming i.e. reduce the facility availability
as well as productivity. Moreover, the gantry crane needs a skilful operator to control
manually based on his or her experiences to stop the swing immediately at the right
position. Furthermore to unload, the operator has to wait the load stop from
swinging. The failure of controlling crane also might cause accident and may harm
people and surrounding. To overcome this problem, an intelligent gantry crane
system had been introduced. Fuzzy logic controllers is proposed, designed and
implemented for controlling payload position as well as the swing angle of the gantry
crane. PID control approach will be taken as comparator based on the previous
research. This project is to propose the control design of AC Servo drive system for
linear guide application of gantry crane. The typical linear guide applications can be
hoist system like crane, lift, gantry crane system. In this proposed control design, the
main purpose of controlling gantry crane system is transporting the load as fast as
possible to the required position with precision, without any force disturbance and
parameter variations which is swing motion which cause a steady and/or transient
error in the conventional ac servo drive system. Basically this system is designed
according to the experimental results which convinced the collected data obtained,
and simulation approach.
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ABSTRAK
Kren gantri digunakan secara meluas dalam industri untuk mengangkut beban berat
dan bahan-bahan berbahaya di limbungan kapal, kilang, pepasangan nuklear, dan
pembinaan bangunan tinggi. Kren harus bergerak secepat mungkin tanpa
menyebabkan mana-mana pergerakan yang berlebihan di kedudukan terakhir. Walau
bagaimanapun, yang paling biasa kren gantri bermasaalah dalam gerakan ayunan
apabila muatan tiba-tiba dihentikan selepas gerakan pantas. Sudut ayunan boleh
dikurangkan tetapi akan memakan masa iaitu mengurangkan adanya kemudahan
serta produktiviti. Selain itu, kren gantri memerlukan pengendali mahir untuk
mengawal secara manual berdasarkan pengalaman beliau untuk menghentikan
ayunan segera di kedudukan yang betul. Tambahan pula untuk memunggah,
pengendali telah menunggu hentian beban dari buaian. Kegagalan mengawal kren
juga mungkin menyebabkan kemalangan dan boleh membahayakan orang dan
sekitarnya. Untuk mengatasi masalah ini, pintar gantri kren sistem telah
diperkenalkan. Fuzzy logik adalah dicadangkan, direka dan dilaksanakan untuk
mengawal kedudukan muatan serta sudut swing kren gantri. Pendekatan kawalan
PID akan diambil sebagai comparator berdasarkan penyelidikan sebelumnya. Projek
ini adalah untuk mencadangkan reka bentuk kawalan AC sistem pemacu servo untuk
aplikasi panduan linear gantri kren. Panduan tipikal aplikasi linear boleh angkat
sistem seperti kren, lif, sistem gantri kren. Dalam reka bentuk kawalan yang
dicadangkan ini, tujuan utama sistem kren gantri mengawal dan mengangkut beban
secepat mungkin pada kedudukan yang dikehendaki dengan tepat, tanpa gangguan
mana-mana angkatan dan variasi parameter yang merupakan gerakan ayunan yang
menyebabkan kesilapan yang mantap dan / atau fana dalam ac konvensional servo
drive sistem. Pada asasnya, sistem ini direka mengikut kepada keputusan eksperimen
yang membuktikan data yang dikumpul diperolehi, dan pendekatan simulasi.
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TABLE OF CONTENTS
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENTS iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xi
LIST OF ABBREVIATIONS xiii
LIST OF SYMBOLS xiv
LIST OF APPENDICES xv
1 INTRODUCTION 1
1.1 Introduction 1
1.2 Objectives 3
1.3 Scope of Project 3
1.4 Methodology 4
1.5 Thesis Outline 6
2 MODELLING OF THE GANTRY CRANE SYSTEM 7
2.1 Introduction 7
2.2 Literature Review 9
2.3 Model Description 11
2.4 Derivation of the Equation of Motion 12
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3 FUZZY LOGIC CONTROLLER 18
3.1 Introduction of Fuzzy Logic Control 18
3.1.1 Fundamentals of Fuzzy Logic Control 19
3.2 Fuzzy Logic Control System 21
3.3 Fuzzy Logic Controller Design
for Gantry Crane 22
3.3.1 Control Structure 22
3.3.2 Fuzzification and Inference 29
3.3.3 Defuzzification 30
4 SIMULATION RESULTS AND ANALYSIS 32
4.1 Introduction 32
4.2 Simulation 32
4.2.1 Dynamic Model of Gantry Crane
in SIMULINK 38
4.3 Results and Analysis 41
5 EXPERIMENTAL SETUP 47
5.1 Introduction 47
5.2 Hardware Implementation 47
5.3 Software Implementation 50
5.3.1 Simatic Step7 Software 50
5.3.2 FuzzyControl++ V5.0 Software 54
5.3.2.1 Fuzzy System Design 54
5.4 Experimental Results and Analysis 54
x
LIST OF TABLES
TABLE NO. TITLE PAGE
2.1 Summary of Literature Review 9
4.1 Numerical Values of AC Servo Motor Model 38
4.2 Position Control Performance 42
4.3 Swing Angle Control Performance 44
5.1 Lab-scale of Gantry Crane Parameter Values 48
5.2 Comparison of Simulation and Experimental Results 65
xi
LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 Flow Chart of Project Methodology 5
2.1 Model of Gantry Crane System 11
3.1 General Fuzzy Control System 19
3.2 The Fuzzy Control Rule Base 20
3.3 Block Control of Fuzzy Control System 21
3.4 Block Diagram of Gantry Crane System 22
3.5 Principle of Fuzzy Logic Control 24
3.6 Antecedents of Gantry Crane System 24
3.7 Fuzzy Controller Structure 24
3.8 Membership functions of position control 26
3.9 Membership functions of swing angle control 27
4.1 FIS Editor for Position Control 33
4.2 Membership Function of Input Error for Position Control 33
4.3 Membership Function of Input Error Rate
for Position Control 34
4.4 Membership Function of Output Voltage for Position Control 34
4.5 FIS Editor for Swing Angle Control 35
4.6 Membership Function of Input Error for Swing Angle Control 35
4.7 Membership Function of Input Error Rate
for Swing Angle Control 36
4.8 Membership Function of Output Voltage
for Swing Angle Control 36
4.9 Rules for Position Control 37
4.10 Rules for Swing Angle Control 37
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4.11 Dynamic System of Overall View of Gantry Crane Model 39
4.12 Fuzzy Logic Controller for Position and
Swing Angle Applied on Gantry Crane Model 39
4.13 Dynamic System of Gantry Crane and AC Servo Motor 40
4.14 Comparison of Position Control Output Response
for Fuzzy and PID Controller 41
4.15 Comparison of Swing Angle Control Output Response
for Fuzzy and PID Controller 43
4.16 Fuzzy Logic Control Surface Behavior of Position Control 44
4.17 Fuzzy Logic Control Surface Behavior of Swing Angle Control
45
4.18 VRML Animation of Gantry Crane System
via 3-D Visualization
46
5.1 Lab-scale Gantry Crane System 48
5.2 Digital and Analogue Inputs Outputs Connection 49
5.3 Integration Software and Hardware System
for Lab-scale Gantry Crane 50
5.4 Programming Data Blocks in Step 7 for PLC S7-300 52
5.5 Function Blocks Used in Simatic Step 7 52
5.6 Programming Configuration in Simatic Step 7 53
5.7 STL Structure Programming in Simatic Step 7 53
5.8 Fuzzy Logic Controller Design for Position Control
via FuzzyControl++ V5.0 Software Toolbox 57
5.9 Fuzzy Logic Controller Design for Swing Angle Control
via FuzzyControl++ V5.0 Software Toolbox 59
5.10 Singleton Functions 60
5.11 Control Behaviors Performance of Fuzzy Control System for
Position Control in FuzzyControl++ V5.0 Software 62
5.12 Control Behaviors Performance of Fuzzy Control System
for Swing Angle Control in FuzzyControl++ V5.0 Software 63
5.13 Output Responses of Velocity and Error for Position and
Swing Angle Control 64
xiii
LIST OF ABBREVIATIONS
PLC - Programmable Logic Controller
FLC - Fuzzy Logic Controller
FB - Function Block
PID - Proportional-Integrator-Derivative
PD - Proportional-Derivative
AC - Alternate Current
VRML - Virtual Reality Modeling Language
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LIST OF SYMBOLS
- Exponention friction factor
- Motor damping coefficient
- Viscose friction coefficient
- Coulomb friction coefficient
- Maximal static friction
- Load inertia
- Motor inertia
- Maximal amplifier current
K - Motor gain
- Gear stiffness factor
- Inductance of magnetizing circuit
n - Gear transmission
- Resistance of magnetizing circuit
- Motor starting torque backlash
xv
LIST OF APPENDICES
APPENDIX TITLE PAGE
A Configuration of FuzzyControl++ and Simatic Step7 71
B Data Sheet of 9400 AC Servo High Line Lenze 80
CHAPTER 1
INTRODUCTION
1.1 Introduction
This project is basically designing and implementing fuzzy logic control to
control payload position as well as the swing angle for an intelligent gantry crane
system. Throughout the world, there have been many researches about the concept
and implementation of this system which is deemed suitable for all types of control
applications. For this project, the implementation of fuzzy logic control is applied to
a gantry crane model to overcome and improve the performance level from other
controllers approach proposed such as PD and PID, which is been said that they have
higher steady state error and low sensitivity to disturbance. The fuzzy logic
controllers were designed based on information of the skillful operators and without
the need of crane model and its parameters [5]. The performance of the proposed
intelligent gantry crane system had been evaluated based on simulation and
experimentally on a lab-scale gantry crane system.
In this project, AC Servo drive system is been introduced to control the linear
guide which is application of gantry crane. When people talk about servo drives
today, they generally mean highly dynamic three-phase drives. Servo drives
primarily perform positioning tasks in tooling machines, manipulators or robots. But
these ac servo drive system are increasingly finding their way into printing machines,
conveyor belts and cutting machinery where precise positioning or angular
synchronism are required. Here, servo converters, motors with sensor technology
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and mechanical transfer elements form an extremely integrated system whose
components have to be seen as a single entity. Because of the low cost, high
reliability, power efficiency, and easy maintenance, induction and permanent-magnet
AC motor drives have been widely used in industrial applications, which stimulate
research in its motion control to achieve high performance.
The development of fuzzy logic control design is implemented using fuzzy
logic toolbox in Matlab Simulink. The main features of the fuzzy logic design
process consist of the development of input and output of the membership functions.
In the case of gantry crane, error and error rate of position and swing angle are taken
into consideration as an input. Meanwhile, the voltage is taken as an output. Since
there is no specific form to be used when designing fuzzy logic control, thus, the
basic triangle and trapezoidal forms are chosen for input and output membership
functions [17]. In most cases, the performance of fuzzy control is minimally
influenced by the shapes of memberships, but mainly by the characteristics of control
rules.
As for the hardware part, it consists of many parts of mechanical sub-system,
an actuation mechanism for transferring payload, position and swing angle sensors,
real-time control software/hardware. PLC S7-300 (Siemens) model is used as
controller mechanism to control AC Servo drive system which attached to the linear
guide for positioning of gantry crane in with the payload is connected. Two sensors
are used to measure linear guide position and payload swing angle. For this lab scale
gantry crane, a planar movement with fixed cable, length of cable and fixed load is
been considered. The experiment will be run based on the fuzzy controlled
parameters setting.
3
1.2 Objectives
The main objective of this project is to design and implement fuzzy logic
control in order to control payload position as well as the swing angle for an
intelligent gantry crane system. The objectives can be narrowed to many intentions :
(i) To design the control algorithm for planar gantry crane system by using fuzzy
logic controllers to control the payload position to be moved to the desired
position while payload swing angle will be kept asymptotically small at final
position.
(ii) To develop simulation for the proposed system.
(iii) To implement the proposed control method based on the VRML animation
and lab scale gantry crane design based on experimental and compare the
result effectiveness with classical PID controllers approach.
1.3 Scope of Project
This project is a combination of hardware and software parts development to
implement the fuzzy logic control method on gantry crane system. For the software
part, MATLAB Simulink software is chosen to program and simulate the fuzzy logic
controller and apply to the gantry crane system.
The scopes of project for software are :
i. Literature study on the most appropriate programming and toolbox in
Matlab Simulink for simulation of proposed gantry crane model.
ii. Analyze and study on how to design a fuzzy logic controller.
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iii. Apply fuzzy logic controller algorithm to the developed model of gantry
crane in Matlab Simulink.
iv. Run the simulation and design in VRML animation and fix the error.
v. Interface the software and hardware part by using Simatic Net Software to
communicate FuzzyControl++ and Programmable Logic Controller
(PLC) from Siemens. The programming for the PLC is been done using
Simatic S7 PLC (SIEMENS).
1.4 Methodology
In order to meet the objectives of the project, the system is designed based on
several steps of approach which to optimize the anti-swing and zero steady state error
performance of gantry crane system. The methodology to complete this project will
be done on simulation and experiment evaluation. The control method proposed is
Fuzzy logic control (FLC). Fuzzy logic controller will be compared with PID
controller from previous researches, which the existing mathematical model
development will be applied for ac servo and gantry crane. The proposed FLC is
based on fuzzy algorithm and the fuzzy rules developed.
The proposed controller consists of fuzzy logic controllers for both position
and anti-swing control respectively. The objective of the proposed fuzzy logic
controllers is to control the payload position X(s) so that it moves to the desired
position Xref(s) as fast as possible without excessive swing angle of the payload θ(s).
Here, the design of fuzzy logic control is based on a heuristic approach. Figure 1.1
below shows the flow chart of project methodology.
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Figure 1.1 : Flow Chart of Project Methodology
Identify & analyze gantry crane problem - swing motion
Study on gantry crane control method - PID & Fuzzy
Develop mathematical model for system
Design Fuzzy Logic Controller (based heuristic)
Implement Simulation to perform control methods- Matlab/Simulink
and program to PLC
Design improvement lab-scale for gantry crane + system
integration (software)
Run experiment to perform control methods
Evaluate & compare performance of output from
simulation & experiment
6
1.5 Thesis Outline
This thesis consists of six chapters. Chapter 1 is about the introduction,
objectives, scope of project and methodology. The purpose is to give a brief
overview of this project.
Chapter 2 defines and illustrates the steps employed in the fuzzy logic
controller. Including detailed about modeling and derivation of equations for the
gantry crane system. All these methodology should be followed for a better
performance.
Chapter 3 is the fuzzy logic controller. This chapter provides a theory of
fuzzy logic, the fuzzy logic control system, fuzzy logic control design and
application of fuzzy control to a gantry crane. It describes about research and
information about the project, which every fact found through the journals or other
references, will be compared and the better methods have been chosen for the
project.
Chapter 4 shows the details of designing a controller and dynamic system in
simulation Matlab/Simulink and VRML animation. It also describes the analysis of
project findings. The results are presented by the transient response of the output
performance.
Chapter 5 describes about the implementation of experimental on lab-scale of
gantry crane in terms of software and hardware parts.
Chapter 6 provides the conclusion and some suggestion for future works for
this project.
REFERENCES
[1] Mahmud Iwan and Wahyudi, Fuzzy-tuned PID Control Design for Automatic
Gantry Crane, International Conference on Intelligent and Advanced
Systems, 2007.
[2] M.A.Ahmad, M.S. Ramli, R.M.T. Raja Ismail, A.N.K. Nasir and M.A.
Zawawi, The Investigations of PD-type Fuzzy Logic with Different Polarities
Input Shaping for Anti-Sway Control of a Gantry Crane System, Conference
on Innovative Technologies, 2009.
[3] Chunshien Li and Chun-Yi Lee, Fuzzy Motion Control of an Auto-
Warehosuing Crane System, IEEE Trans. Industrial Electronics, vol. 48, no.
5, October 2001.
[4] Yaolong Tan, Jie Chang, and Hualin Tan, Adaptive Backstepping Control
and Friction Compensation for AC Servo with Inertia and Load Uncertainties,
IEEE Trans. Industrial Electronics, vol. 50, no. 5, October 2003.
[5] Wahyudi and J.Jalani, Robust Fuzzy Logic Controller for an Intelligent
Gantry Crane System, IEEE Trans. Industrial Electronics, August 2006.
[6] Mohd Ashraf, Ahmad Nor and Haszuraidah, Techniques of Anti-Sway and
Input Tracking Control of Gantry Crane System, International Conference
IEEE, 2009.
[7] Chunshien Li and Chun-Yi Lee, Fuzzy Motion Control of an Auto-
Warehousing Crane System, IEEE Trans. Industrial Electronics,vol. 48, no.
5, 2001.
[8] Nalunat Khongkoom,Attapol Kanchanathep and Suthichai, Control of the
Position Servo Motor by Fuzzy Logic, Journal of Faculty of Engineering and
Research Center for Communications and Information Technology,King
Mongkut’s Institute of Technology,Thailand, 2000.
[9] Karel Jezernik, High Precision VSS Motion Control of Servo Drives,
International Journal of University of Maribor, Faculty of Electrical
Engineering and Computer Science, 2002
69
[10] Yingzhe Wu,Hui Li and Ye Bi, Study on Missile Rudder Servo System Based
on Mixed Fuzzy-PID Control Algorithm, IEEE International Conference on
Mechatronics and Automation, 2011.
[11] A. Pisano, A. Davila, L. Fridman, and E. Usai, Cascade control of pm dc
drives via second-order sliding-mode technique, IEEE Transactions on
Industrial Electronics, vol. 55, pp. 3846–3854, 2008.
.
[12] Rajeeb Dey,Nishant Sinha,Priyanka Chaubey, Active Sway Control of a
Single Pendulum Gantry Crane System using Output-Delayed Feedback
Control Technique, International Conference Control, Automation, Robotics
and Vision Singapore, 2010.
[13] M.A.M. Schreppers, Control of a Gantry Crane Process by a Fuzzy Logic
Controller, M.Sc. Thesis, June 1993.
[14] Arto Makkonen and Heikki N.Koivo, Fuzzy Control of a Nonlinear
Servomotor Model, 3rd
Internatinal Workshop on Advanced Motion Control,
pp. 833-841, March 1994.
[15] Xu J. and Feng X, Design of Adaftive Fuzzy PID tuner Using Optimization
Method, 5th World Congress on Intelligent Control and Automation, 2004.
[16] Renno J.M., Trabia M.B. and Moustafa K.A.F., Anti-swing Adaptive Fuzzy
Controller for An Overhead Crane with Hoisting,IMECE ASME International
Mechanical Engineering Congress & Exposition, 2004.
[17] Omar, H.M, Control of Gantry and Tower Cranes, Ph. D. Thesis, M.S
Virginia Tech, 2003.
[18] Wahyudi and J.Jalani, Modelling and parameters identification of gantry
crane system, in Proceedings of International Conference on Mehctronics,
no. 129, 2005.
[19] Trabia M.B., Renno J.M. and Moustafa K.A.F. , A General Anti-swing Fuzzy
Controller for An Overhead Crane with Hoisting, Proceedings of IEEE
International Conference on Fuzzy Systems, 2006.
[20] Lee, H.H, and Cho, A New Fuzzy Logic Anti Swing Control for Industrial
Dimensional Overhead Cranes, Thesis of Department of Mechanical
Engineering, University of Suwon, 2001.