Development of Adaptive Speed Observers for Induction Machine System Stabilization - Ahmed A. Zaki Diab, Abo-Hashima  M. Al-Sayed, Hossam Hefnawy Abbas Mohammed, Yehia Sayed Mohammed

Development of Adaptive Speed Observers for Induction Machine System Stabilization (eBook)

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2020 | 1st ed. 2020
XXII, 80 Seiten
Springer Singapore (Verlag)
978-981-15-2298-7 (ISBN)
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This book describes the development of an adaptive state observer using a mathematical model to achieve high performance for sensorless induction motor drives. This involves first deriving an expression for a modified gain rotor flux observer with a parameter adaptive scheme to estimate the motor speed accurately and improve the stability and performance of sensorless vector-controlled induction motor drives. This scheme is then applied to the controls of a photovoltaic-motor water-pumping system, which results in improved dynamic performance under different operating conditions. The book also presents a robust speed controller design for a sensorless vector-controlled induction motor drive system based on H∞ theory, which overcomes the problems of the classical controller.



Ahmed A. Zaki Diab, Ph.D.; received B.Sc. and M.Sc. in Electrical Engineering from Minia University, Egypt in 2006 and 2009, respectively. In 2015, he received Ph.D. from Electric Drives and Industry Automation Department, Faculty of Mechatronics and Automation at Novosibirsk State Technical University, Novosibirsk, Russia. He had obtained postdoctoral Fellowship at the National research university 'MPEI', Moscow Power Engineering Institute, Moscow, Russia from September 2017 to March 2018. Since 2007, he has been with the Department of Electrical Engineering, Faculty of Engineering, Minia University, Egypt as a Teaching Assistant, a Lecturer Assistant, and since 2015, as an Assistant Professor. Currently, He is a Visitor researcher (postdoctoral) at Green Power Electronics Circuits Laboratory, Kyushu University, Japan (awarded the MIF Research Fellowship 2019, Japan). Dr. Diab is certified as a Siemens Engineer and Trainer in several fields of automation and process control systems and He is a supervisor of the Automatic Control and Traction Lab., Faculty of Engineering, Minia University, Egypt. His present research interests include Renewable Energy Systems, Power Electronics, and Machines Drives.

Abo-Hashima M. Al-sayed, Ph.D.; received his B.Sc., and M.Sc. in Electrical Engineering from Minia University, Minia, Egypt, in 1994 and 1998, respectively. He was a Ph.D. student in the Institute of Electrical Power Systems and Protection, Faculty of Electrical Engineering, Dresden University of Technology, Dresden, Germany from 2000 to 2002. He received his Ph.D. in Electrical Power from the Faculty of Engineering, Minia University, Egypt in 2002, according to a channel system program, which means a Scientific Co-operation between the Dresden University of Technology, Germany and Minia University, Egypt. Since 1994, he has been with the Department of Electrical Engineering, Faculty of Engineering, Minia University, as a Teaching Assistant, a Lecturer Assistant, an Assistant Professor, and Associate Professor. He was a Visiting Researcher at Kyushu University, Japan, from 2008 to 2009. He is the head of Mechatronics and Industrial Robotics Program, Faculty of Engineering, Minia University from 2011 till now. His research interests include Protection Systems, Renewable Energy, and Power Systems.

Hossam Hefnawy Abbas Mohammed, Ph.D.; received his B.S., M.Sc. and Ph.D. in Electrical Engineering from Department of Electrical Engineering, Faculty of Engineering, Minia University, Egypt, in 2004, 2015 and 2019, respectively. He has joined Middle Egypt Electricity Distribution Company as electrical engineer in 2004. Also, he had worked in Telecom Egypt Co. as Head of Operation and Maintenance Department of Control Center Devices in 2008.      Dr. Hossam is currently working in Electricity and water Authority in Kingdom of Bahrain. He had more than fourteen years of practical working experience. His research interests cover power electronics, electric machines control, renewable energy, modeling and simulation of power converters, computer algebra systems, power quality and harmonics analysis, advanced control theory and DSP-based control applications.
Yahia Sayed Mohammed, Ph.D.; received his B.Sc., M.Sc. and Ph.D.  in Electrical Engineering from Assiut University, Assiut, Egypt, in 1983, 1989 and 1998, respectively. He is a professor and the head of Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt. His research interests include Machine Drives, and Renewable Energy.



This book describes the development of an adaptive state observer using a mathematical model to achieve high performance for sensorless induction motor drives. This involves first deriving an expression for a modified gain rotor flux observer with a parameter adaptive scheme to estimate the motor speed accurately and improve the stability and performance of sensorless vector-controlled induction motor drives. This scheme is then applied to the controls of a photovoltaic-motor water-pumping system, which results in improved dynamic performance under different operating conditions. The book also presents a robust speed controller design for a sensorless vector-controlled induction motor drive system based on Hinfinity theory, which overcomes the problems of the classical controller.

About This Book 6
IntroductionThe speed sensorless vector control techniques of induction motor drives are used in high performance applications. These techniques generally require an accurate determination of the machine parameters, rotor flux and motor speed. It uses a full order-type adaptive rotor flux observer that takes parameters variation into account to achieve high steady state performance without spoiling the dynamic response.In this book, an adaptive state observer is derived based on the induction machine model. A modified gain rotor flux observer with a parameter adaptive scheme has been proposed for sensorless vector control induction motor drives. The optimal value of the observer gain has been proved by minimizing the error between the measured and estimated states. Also, the stability of the proposed observer with the parameter adaptation scheme is proved by the Lyapunov’s theorem.The application of sensorless vector control drives to control a photovoltaic (PV) motor pumping system has been presented in this book. The principle of vector control has been applied to control the single stage of voltage source inverter (VSI) feeding the three-phase induction motor. The main objective of this work is to design and analyze a single stage maximum power point tracking (MPPT) from PV module and eliminate the speed encoder. Elimination of the speed encoder aims to increase the reliability of the PV motor pumping system. Therefore, a full order adaptive state observer has been designed to estimate the rotor speed of the motor pumping system. Moreover, the incremental conductance method is used for achieving MPPT of the PV system. The control scheme with full order adaptive state observer has been investigated under different operating conditions of varying natures of solar radiation and air temperature. The simulation results show that the response of the PV motor pumping system with the adaptive speed observer has a good dynamic performance under different operating conditions.In order to improve the dynamic response and to overcome the problems of the classical speed controller (such as overshoot, long settling time and oscillations of motor speed and torque), a robust controller design based on the H? theory for high performance sensorless induction motor drives is implemented. The proposed controller is robust against system parameter variations and achieves good dynamic performance. In addition, it rejects disturbances well and can minimize system noise. The H? controller design has a standard form that emphasizes the selection of the weighting functions that achieve the robustness and performance goals of motor drives in a wide range of operating conditions. The model reference adaptive system (MRAS) is used to estimate the motor speed based on the measurement of stator voltages and currents. In this work, the stability of the estimator scheme is discussed and proved based on Popov’s criterion. To investigate the effectiveness of the proposed control scheme at different operating conditions (such as a sudden change of the speed command/load torque disturbance), its performance is compared with those of the classical control one. Experimental and simulation results demonstrate that the presented control scheme with the H? controller and MRAS speed estimator has an accurate estimated motor speed and a good dynamic performance. 7
Contents 9
About the Authors 12
Abbreviations 15
Symbols 16
List of Figures 18
1 Introduction and Background of Induction Machine System Stabilization 20
1.1 Research Objectives 21
1.2 Organization of the Book 22
References 23
2 Literature Review of Induction Motor Drives 25
2.1 Introduction 25
2.2 Rotor Flux Estimator for Sensorless Induction Motor 26
2.3 Rotor Flux Observer for Sensorless Induction Motor 28
2.4 Effect of Speed Estimation Methodology on Sensorless Induction Motors 29
2.5 Adaptive Speed Observer for Sensorless Vector Control for Motor Pumping System Applications 30
2.6 Effect of Parameter Variation of the Speed Controllers on Sensorless Induction Motors 32
2.6.1 Speed Controller Based on Classical PI Controller 32
2.6.2 Speed Controller Based on Fuzzy Logic Controller 32
2.6.3 Speed Controller Based on Linear Quadratic Gaussian Method 32
2.6.4 Speed Controller Based on HInfinity Control Theory 33
References 34
3 Development and Stabilization of Adaptive State Observers for Induction Machines 37
3.1 Introduction 37
3.2 Dynamic Model of the Induction Machine 38
3.3 Full Order Adaptive State Observer 39
3.4 Adaptive Observer Scheme for Motor Parameters and Speed Estimation 40
3.5 Developed Gain of Adaptive Rotor Flux Observer 43
3.6 Model Reference Adaptive System for Speed Estimation 46
3.6.1 Conventional Model Reference Adaptive System 46
3.6.2 Modified Model Reference Adaptive System 47
References 49
4 Sensorless Vector Control for Photovoltaic Array Fed Induction Motor Driving Pumping System 50
4.1 Introduction 50
4.2 Description of the Proposed Standalone PV Motor Pumping System 51
4.3 Modeling of the Proposed Standalone PV Motor Pumping System 52
4.3.1 Modeling of the Photovoltaic Cell 52
4.3.2 Estimation of DC Link Capacitor 53
4.3.3 Design of the Centrifugal Pump 54
4.3.4 PWM VSI Based Current Controller Scheme 55
4.3.5 Dynamic Model of Induction Motor 56
4.4 Proposed Control Scheme for PV Motor Pumping System 56
4.4.1 MPPT Control Algorithms 56
4.4.2 Field Oriented Control of Induction Motor Drive 57
4.5 Proposed Full Order Adaptive Speed Observer 59
4.6 Simulation Results 61
References 64
5 Robust Speed Controller Design Using H? Theory for High Performance Sensorless Induction Motor Drives 66
5.1 Introduction 66
5.2 Modeling of Vector Controlled Induction Motor Drives 67
5.3 Design of the Proposed Robust Controller Based on H? Theory 69
5.4 Robust Speed Estimation Based on MRAS Techniques for an IFO Control 72
5.5 Proposed Sensor-Free Induction Motor Drive for High-Performance Applications 76
5.6 Simulation and Experimental Results 77
5.6.1 Simulation Results and Discussions 77
5.6.2 Experimental Results and Discussions 81
References 85
6 Conclusions and Recommendation for Future Work 87
6.1 Conclusions 87
6.2 Suggestion for Future Work 88
Appendix A Technical Specifications of the PV Module and Induction Motor Under Study 89
A.1 PV Module Specifications 89
A.2 Induction Motor Specifications 90
Appendix B Induction Motor Parameters and Technical Specifications 91
Appendix C Digital Signal Processor Kit 92
C.1 DSP Controller Design 92
C.2 DSP Based High Voltage Digital Motor Control Kit 92
C.2.1 Features of the TMS320F28035 System 93
C.2.2 Features of the High Voltage Motor Control and PFC Board 94
References 95

Erscheint lt. Verlag 3.1.2020
Reihe/Serie SpringerBriefs in Electrical and Computer Engineering
SpringerBriefs in Electrical and Computer Engineering
Zusatzinfo XXII, 80 p.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Wirtschaft Betriebswirtschaft / Management Logistik / Produktion
Schlagworte adaptive state observer • gain rotor flux observer • induction machine model • Induction Motor Drives • Lyapunov’s theorem • Maximum power point tracking (MPPT) • model reference adaptive system (MRAS) • photovoltaic motor pumping system • sensorless vector control • Voltage Source Inverter
ISBN-10 981-15-2298-7 / 9811522987
ISBN-13 978-981-15-2298-7 / 9789811522987
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