UNIVERSITI PUTRA MALAYSIA SIMULATED REAL TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH AHMED ABDULELAH AHMED

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1 UNIVERSITI PUTRA MALAYSIA SIMULATED REAL TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH AHMED ABDULELAH AHMED FK

2 H By T U PM SIMULATED REAL-TIME REAL TIME CONTROLLER FOR TUNING ALGORITHM USING MODIFIED HILL CLIMBING APPROACH PY R IG AHMED ABDULELAH AHMED C O Thesis Submitted to the School of Graduate Studies, Universit Universiti Putra Malaysia, in Fulfilment Fulfilment of the Requirements for the Degree of Master of Science JULY

3 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

4 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

5 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 Chair: Azura Che Soh, PhD Faculty: Engineering By AHMED ABDULELAH AHMED JULY 2014 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 realtime 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 i

6 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. ii

7 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 Pengerusi: Azura Che Soh, PhD Fakulti: Kejuruteraan Oleh AHMED ABDULELAH AHMED JULAI 2014 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 iii

8 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. iv

9 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. v

10 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: vii

11 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 fullyowned 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 ) and the Universiti Putra Malaysia (Research) Rules The thesis has undergone plagiarism detection software. Signature: Date: Name and Matric No.: viii

12 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 ) 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: ix

13 TABLE OF CONTENTS ABSTRACT ABSTRAK ACKNOWLEDGEMENTS APPROVAL DECLARATION LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS CHAPTER Page i iii v vi viii xiii xv xix 1 INTRODUCTION General Background Problem Statement and Importance of Research Research Objectives and Scope Objectives Research Scope Research Contributions Research flow Thesis organization 6 2 LITERATURE REVIEW Introduction Adaptive control Gain scheduling Self-tuning regulators Model reference adaptive control Automatic controller optimization and tuning Real time tuning Brief review of optimization algorithms Artificial intelligence methods Genetic algorithms Hill climbing algorithm Brief review of controllers used in experiments PID controller Linear quadratic regulator Fuzzy logic controller Summary 23 3 RESEARCH METHODOLOGY Introduction Summary of design workflow Control strategy design 27 x

14 Control paradigm The desired reference response The error function The tuning algorithm Procedure explanation Algorithm properties Process controller Important aspects to consider during design 34 phase 3.4. Models of example systems Twin rotor MIMO system (TRMS) model Fixed wing airplane pitch angle model DC motor model The desired reference response generation for each 41 process TRMS Using PID controller Using fuzzy controller Using LQR Fixed wing airplane pitch angle Using PID controller Using fuzzy controller DC motor Using PID controller Using fuzzy controller Applying the tuning algorithm Summary 52 4 RESULTS AND DISCUSSION Introduction TRMS simulation TRMS process controller tuning using PID 53 controller to generate the desired reference response TRMS process controller tuning using fuzzy 56 controller to generate the desired reference response TRMS process controller tuning using LQR to 60 generate the desired reference response Comparison among the TRMS cases Fixed wing airplane pitch angle simulation Fixed wing airplane pitch angle controller 65 tuning using PID to generate the desired reference response Fixed wing airplane pitch angle controller tuning using fuzzy controller to generate the 67 xi

15 desired reference response Comparison between the cases of fixed wing 69 airplane pitch angle 4.4. DC motor system simulation DC motor controller tuning using PID to 71 generate the desired reference response DC motor controller tuning using fuzzy 72 controller to generate the desired reference response Comparison between the DC motor cases Summary 75 5 CONCLUSION AND FUTURE WORK Conclusion Contribution 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 xii

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