UNIVERSITI PUTRA MALAYSIA

AHMED ABDULELAH AHMED

FK 2014 22

SIMULATED REAL TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

© COPYRIG

HT UPMSIMULATED REAL

Thesis Submitted to the School of Graduate Studies, UniversitMalaysia, in

SIMULATED REALUSING MODIFIED HILL CLIMBING APPROACH

Thesis Submitted to the School of Graduate Studies, UniversitMalaysia, in Fulfi

SIMULATED REAL-TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, UniversitFulfilment of the Requirements for the Degree of

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

By

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of

Science

JULY

1

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

By

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of

Science

JULY 2014

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

AHMED ABDULELAH AHMED

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of

TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

Thesis Submitted to the School of Graduate Studies, Universitlment of the Requirements for the Degree of Master of

TIME CONTROLLER FOR TUNING ALGORITHM

Thesis Submitted to the School of Graduate Studies, Universiti Putra Master of

TIME CONTROLLER FOR TUNING ALGORITHM

Putra Master of

© COPYRIG

HT UPM

COPYRIGHT

All material contained within the thesis, including without limitation text, logos, icons, photographs and all other artwork, is copyright material of Universiti Putra Malaysia unless otherwise stated. Use may be made of any material contained within the thesis for non-commercial purposes from the copyright holder. Commercial use of material may only be made with the express, prior, written permission of Universiti Putra Malaysia. Copyright © Universiti Putra Malaysia

© COPYRIG

HT UPM

DEDICATIONS

This work is dedicated to

dad and mom, without you I am nothing

brother and sister, I love you

my beloved wife, my light

© COPYRIG

HT UPM

i

Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the degree of Master of Science

SIMULATED REAL TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

By

AHMED ABDULELAH AHMED

JULY 2014

Chair: Azura Che Soh, PhD

Faculty: Engineering

Many techniques and inventions in the field of automatic control keeps going forwards, especially that the introduction of modern computing provided a huge ground for innovation in this field. Intelligent control was one of the direct beneficiaries of the computer systems advancements. That led to new ways to tackle old problems like model inaccuracies and inconsistencies. Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time. In this research, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. Although all adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that require neither high processing power nor long processing time, as opposed to identification techniques calculations. The main principle in the tuning process is to compare the output of the plant with a desired reference signal within an acceptable error margin. In order to investigate the ability of the proposed tuning method to deal with different system complexities, simulations of three different case studies were conducted. In each case study, different possibilities to generate the desired reference signal is discussed along with how much the complexity of the system would affect the end result. Also, in each case study a discussion contrasts the limitations and conditions needed to be identified to use the proposed method. The proposed design performed very well, improving

© COPYRIG

HT UPM

ii

overshoot and response speeds in example systems depending on reference response generation method. The results showed that using different methods to generate the reference response gives system designer flexibility over favouring a specific response characteristics or an overall decent response. The simulation results illustrates that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real time calibration problem.

© COPYRIG

HT UPM

iii

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains

SIMUL ATED REAL-TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH

Oleh

AHMED ABDULELAH AHMED

JULAI 2014

Pengerusi: Azura Che Soh, PhD

Fakulti: Kejuruteraan

Banyak teknik dan penciptaan dalam bidang kawalan automatik terus berkembang terutama dengan pengenalan pengkomputeran moden yang telah menyediakan ruang yang luas untuk inovasi dalam bidang ini. Kawalan pintar adalah salah satu daripada penerima manfaat hasil kemajuan sistem komputer. Ini telah membawa kepada cara baru untuk mengatasi masalah sedia ada seperti model yang tidak tepat dan tidak konsisten. Kebiasaannya, kalibrasi parameter bagi sistem kawalan perlu dilakukan kerana parameter loji yang berubah-ubah dari semasa ke semasa. Dalam kajian ini, teknik penalaan algoritma pintar yang sesuai untuk penalaan sistem masa nyata berdasarkan algoritma pengoptimuman mendaki bukit dan model rujukan suai sistem kawalan(MRAC) dicadangkan. Walaupun semua metodologi penalaan kawalan suai bergantung sebahagian atau sepenuhnya pada talian pengenalan sistem loji, kaedah yang dicadangkan hanya menggunakan model untuk rekabentuk pengawal asal, bertujuan memudahkan pengiraan yang tidak memerlukan kuasa pemprosesan tinggi dan memendekkan masa pemprosesan yang bertentangan dengan pengiraan teknik pengenalan. Prinsip utama dalam proses penalaan adalah untuk membandingkan pengeluaran loji dengan isyarat rujukan yang diingini dalam margin ralat yang boleh diterima. Untuk mengenalpasti keupayaan kaedah penalaan yang dicadangkan dalam menangani sistem dengan kompleksiti yang berbeza, simulasi tiga kajian kes yang berbeza telah dijalankan. Dalam setiap kajian kes, kemungkinan yang berbeza untuk menjana isyarat rujukan yang dikehendaki dibincangkan bersama berdasarkan kompleksiti sistem yang akan memberi kesan kepada hasil akhir. Selain itu, dalam setiap kajian kes perbincangan perbezaan had

© COPYRIG

HT UPM

iv

dan syarat perlu dikenalpasti untuk menggunakan kaedah yang dicadangkan. Reka bentuk yang dicadangkan berupaya dengan baik, meningkatkan terlajak dan kelajuan tindak balas dalam sistem contoh. Hasil kajian menunjukkan bahawa menggunakan kaedah yang berlainan untuk menjana tindak balas rujukan memberikan fleksibiliti kepada pereka system lebih memihak kepada ciri-ciri tindak balas tertentu atau tindak balas yang baik secara keseluruhan. Keputusan simulasi menunjukkan bahawa skim kaedah yang dicadangkan dalam kajian ini sebagai penyelesaian yang berdaya maju dan serba boleh untuk menangani penalaan pengawal untuk sistem dengan ketidaktepatan model serta pengawal masa sebenar masalah penentukuran.

© COPYRIG

HT UPM

v

ACKNOWLEDGEMENTS

I would like to express my deep gratitude to my supervisor Dr. Azura Bt. Che Soh for helping and supporting me during my journey in pursuing a Master’s degree. Her insightful guidance and support was the leading force that got me to carry on completing this research. I cannot imagine myself getting a better supervisor for my study.

Besides my advisor, I would like to thank my co-supervisors: Prof. Madya Dr. Samsul Bahari b. Mohd. Noor and Dr. Mohd. Khair b. Hassan for helping me clear many troubles out of my way with their knowledgeable reviewing and critique.

I would also like to thank the laboratories staff at Universiti Putra Malaysia for assisting me during my research.

© COPYRIG

HT UPM

vii

This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master of Science. The members of the Supervisory Committee were as follows: Azura Bt. Che Soh, PhD Senior Lecturer Faculty of Engineering Universiti Putra Malaysia (Chairman) Samsul Bahari b. Mohd. Noor, PhD Associate Professor Faculty of Engineering Universiti Putra Malaysia (Member) Mohd. Khair b. Hassan, PhD Senior Lecturer Faculty of Engineering Universiti Putra Malaysia (Member)

_________________________________ BUJANG BIN KIM HUAT, PhD Professor and Dean School of Graduate Studies Universiti Putra Malaysia

Date:

© COPYRIG

HT UPM

viii

Declaration by graduate student I hereby confirm that: • this thesis is my original work; • quotations, illustrations and citations have been duly referenced; • this thesis has not been submitted previously or concurrently for any

other degree at any other institutions; • intellectual property from the thesis and copyright of thesis are fully-

owned by Universiti Putra Malaysia, as according to the Universiti Putra Malaysia (Research) Rules 2012;

• written permission must be obtained from supervisor and the office of Deputy Vice-Chancellor (Research and Innovation) before thesis is published (in the form of written, printed or in electronic form) including books, journals, modules, proceedings, popular writings, seminar papers, manuscripts, posters, reports, lecture notes, learning modules or any other materials as stated in the Universiti Putra Malaysia (Research) Rules 2012;

• there is no plagiarism or data falsification/fabrication in the thesis, and scholarly integrity is upheld as according to the Universiti Putra Malaysia (Graduate Studies) Rules 2003 (Revision 2012-2013) and the Universiti Putra Malaysia (Research) Rules 2012. The thesis has undergone plagiarism detection software.

Signature: _______________________ Date: __________________

Name and Matric No.: _________________________________________

© COPYRIG

HT UPM

ix

Declaration by Members of Supervisory Committee This is to confirm that: • the research conducted and the writing of this thesis was under our

supervision; • supervision responsibilities as stated in the Universiti Putra Malaysia

(Graduate Studies) Rules 2003 (Revision 2012-2013) are adhered to. Signature: __________________ Signature: ___________________ Name of Chairman of Supervisory Committee:

__________________

Name of Member of Supervisory Committee:

___________________

Signature: __________________ Signature: ___________________ Name of Member of Supervisory Committee:

__________________

Name of Member of Supervisory Committee:

___________________

© COPYRIG

HT UPM

x

TABLE OF CONTENTS

Page ABSTRACT i ABSTRAK iii ACKNOWLEDGEMENTS v APPROVAL vi DECLARATION viii LIST OF TABLES xiii LIST OF FIGURES xv LIST OF ABBREVIATIONS

xix

CHAPTER

1 INTRODUCTION 1 1.1. General Background 1 1.2. Problem Statement and Importance of Research 2 1.3. Research Objectives and Scope 2 1.3.1. Objectives 2 1.3.2. Research Scope 3 1.4. Research Contributions 3 1.5. Research flow 3 1.6. Thesis organization

6

2 LITERATURE REVIEW 7 2.1. Introduction 7 2.2. Adaptive control 7 2.2.1. Gain scheduling 8 2.2.2. Self-tuning regulators 9 2.2.3. Model reference adaptive control 10 2.3. Automatic controller optimization and tuning 11 2.3.1. Real time tuning 12 2.3.2. Brief review of optimization algorithms 12 2.3.2.1. Artificial intelligence methods 13 2.3.2.2. Genetic algorithms 13 2.3.2.3. Hill climbing algorithm 15 2.4. Brief review of controllers used in experiments 17 2.4.1. PID controller 18 2.4.2. Linear quadratic regulator 19 2.4.3. Fuzzy logic controller 21 2.5. Summary

23

3 RESEARCH METHODOLOGY 25 3.1. Introduction 25 3.2. Summary of design workflow 25 3.3. Control strategy design 27

© COPYRIG

HT UPM

xi

3.3.1. Control paradigm 27 3.3.2. The desired reference response 28 3.3.3. The error function 28 3.3.4. The tuning algorithm 29 3.3.4.1. Procedure explanation 30 3.3.4.2. Algorithm properties 33 3.3.5. Process controller 34 3.3.6. Important aspects to consider during design

phase 34

3.4. Models of example systems 35 3.4.1. Twin rotor MIMO system (TRMS) model 35 3.4.2. Fixed wing airplane pitch angle model 38 3.4.3. DC motor model 39 3.5. The desired reference response generation for each

process 41

3.5.1. TRMS 41 3.5.1.1. Using PID controller 41 3.5.1.2. Using fuzzy controller 42 3.5.1.3. Using LQR 45 3.5.2. Fixed wing airplane pitch angle 45 3.5.2.1. Using PID controller 45 3.5.2.2. Using fuzzy controller 46 3.5.3. DC motor 48 3.5.3.1. Using PID controller 48 3.5.3.2. Using fuzzy controller 49 3.6. Applying the tuning algorithm 51 3.7. Summary

52

4 RESULTS AND DISCUSSION 53 4.1. Introduction 53 4.2. TRMS simulation 53 4.2.1. TRMS process controller tuning using PID

controller to generate the desired reference response

53

4.2.2. TRMS process controller tuning using fuzzy controller to generate the desired reference response

56

4.2.3. TRMS process controller tuning using LQR to generate the desired reference response

60

4.2.4. Comparison among the TRMS cases 63 4.3. Fixed wing airplane pitch angle simulation 65 4.3.1. Fixed wing airplane pitch angle controller

tuning using PID to generate the desired reference response

65

4.3.2. Fixed wing airplane pitch angle controller tuning using fuzzy controller to generate the

67

© COPYRIG

HT UPM

xii

desired reference response 4.3.3. Comparison between the cases of fixed wing

airplane pitch angle 69

4.4. DC motor system simulation 71 4.4.1. DC motor controller tuning using PID to

generate the desired reference response 71

4.4.2. DC motor controller tuning using fuzzy controller to generate the desired reference response

72

4.4.3. Comparison between the DC motor cases 74 4.5. Summary

75

5 CONCLUSION AND FUTURE WORK 77 5.1. Conclusion 77 5.2. Contribution 78 5.3. Future work

78

REFERENCES 79 APPENDICES 86 APPENDIX A 86 APPENDIX B 88 B.1. Program for TRMS example 88 B.2. Program for fixed-wing airplane example 91 B.3. Program for DC motor example 93 BIODATA OF STUDENT 95 LIST OF PUBLICATIONS 96