Induction Motor Control Design
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Riccardo Marino, Patrizio Tomei, Cristiano M. Verrelli
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Induction Motor Control Design
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Springer-Verlag
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9781849962841
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Advances in Industrial Control
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1
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CHF 133.60
:
:
Elektronik, Elektrotechnik, Nachrichtentechnik
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English
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351
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Wasserzeichen/DRM
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PC/MAC/eReader/Tablet
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PDF
This book provides the most important steps and concerns in the design of estimation and control algorithms for induction motors. A single notation and modern nonlinear control terminology is used to make the book accessible, although a more theoretical control viewpoint is also given. Focusing on the induction motor with, the concepts of stability and nonlinear control theory given in appendices, this book covers: speed sensorless control; design of adaptive observers and parameter estimators; a discussion of nonlinear adaptive controls containing parameter estimation algorithms; and comparative simulations of different control algorithms. The book sets out basic assumptions, structural properties, modelling, state feedback control and estimation algorithms, then moves to more complex output feedback control algorithms, based on stator current measurements, and modelling for speed sensorless control. The induction motor exhibits many typical and unavoidable nonlinear features.
Born in Ferrara in 1956, Riccardo Marino, received his degree in Nuclear engineering 'cum laude' in July 1979 and the Master in Systems Engineering in 1981 from the University of Rome 'La Sapienza'. In 1982 he obtained the title of Doctor of Science in System Science and Mathematics from Washington University in St. Louis, Missouri, U.S.A. Since 1984 he has been with the Department of Electronic Engineering at the University of Rome 'Tor Vergata' where he is Professor of Systems Theory (he was a researcher from 1984 to 1987 and Associate Professor from 1987 to 1990). He taught the course on Systems Theory from 1987 to 1999, the course on Dynamical Systems from 2000 to 2005. He currently teaches from 2000 the course on Nonlinear Systems. Professor Marino has visited the following institutions collaborating on joint research programs: University of Illinois at Urbana-Champaign, USA, in 1985/86, in 1989 and in 1990, Twente University in Enschede, The Netherlands, in 1986, Polytechnik of Kiev, Ukraine, in 1988, University of California at Santa Barbara, USA in 1992, Ecole des Mines de Paris, Fontainebleau, in 1999, Sophia University, Tokyo, in 2002 and in 2007. He is co-author of the book Nonlinear Control Design: Geometric, Adaptive and Robust, Prentice Hall, Hemel Hempstead, 1995, of more than 70 journal papers and more than 100 communications in international congresses. His scientific interests and contributions are mainly on the design of estimation and control algorithms and their applications to robots, electric machines, and vehicles. Professor Marino was the coordinator of the Doctoral Program in Sensor and Learning Systems Engineering at the University of Rome Tor Vergata from 1999 to 2007. He was associate editor of several scientific journals, member of the Directing Board of the European Control Association and director of several research projects financed by the Italian Ministry of University. Patrizio Tomei was born in Rome, Italy, on June 21, 1954. He received the 'dottore' degree in Electronic Engineering in 1980 and the 'dottore di ricerca' degree in 1987, both from the University of Rome 'La Sapienza'. He is currently Professor of Adaptive Systems at the University of Rome 'Tor Vergata'. He is co-author (with R. Marino) of the book Nonlinear Control Design (Prentice Hall, 1995). His research interests are in adaptive control, nonlinear control, robotics, and control of electrical machines. Cristiano Maria Verrelli was born in Italy on September 12, 1977. He received the Ph.D. in Systems Engineering from the University of Rome 'Tor Vergata' in 2005. He has been visiting scholar at Laboratoire des signaux et systèmes L2S (Supélec, Gif-Sur-Yvette) and at Laboratoire Systèmes Complexes LSC (Evry) in 2004 and 2005. He currently is a Researcher at the Department of Electronic Engineering at the University of Rome 'Tor Vergata'. His research interests are in robust adaptive nonlinear control with application to electrical machines.
Series Editors Foreword
9
Preface
12
Contents
17
1 Dynamical Models and Structural Properties
19
1.1 Modeling Assumptions
20
1.2 State Space Models
23
1.3 Steady-state Operating Conditions with Sinusoidal Voltages
34
1.3.1 Power Loss Minimization
37
1.3.2 Field Weakening
38
1.3.3 Torque Speed Characteristics
39
1.4 Inverse System and Tracking Dynamics
53
1.5 Observability
59
1.6 Parameter Identifiability
64
1.6.1 Load Torque Identifiability
64
1.6.2 Rotor Resistance Identifiability
66
1.7 Feedback Linearizability
69
1.8 Experimental Set-up
73
1.9 Conclusions
76
Problems
77
2 State Feedback Control
80
2.1 Stability Analysis of Feedforward Control
81
2.2 Direct Field-oriented Control
90
2.3 Indirect Field-oriented Control
100
2.4 Input Output Feedback Linearizing Control
110
2.5 Adaptive Input Output Feedback Linearizing Control
118
2.6 Dynamic Feedback Linearizing Control
126
2.7 Global Control with Arbitrary Rate of Convergence
135
2.8 Experimental Results
141
2.9 Conclusions
143
Problems
146
3 Flux Observers and Parameter Estimation
150
3.1 Nonadaptive Observers
150
3.1.1 Open-loop Rotor Flux Observer
150
3.1.2 Open-loop Rotor Current Observer
153
3.1.3 Rotor Flux Observer with Arbitrary Rate of Convergence
156
3.2 Adaptive Flux Observer with Rotor Resistance Estimator
161
3.3 Two Load Torque Estimators
174
3.4 Experimental Results
179
3.5 Conclusions
180
Problems
182
4 Output Feedback Control
187
4.1 Generalized Indirect Field-oriented Control
187
4.2 Observer-based Control
193
4.3 Adaptive Observer-based Control with Uncertain Load Torque
203
4.4 Adaptive Control with Uncertain Load Torque and Rotor Resistance
213
4.4.1 Observer-based Control
215
4.4.2 Global Control
218
4.5 Experimental Results
234
4.6 Conclusions
236
Problems
239
5 Speed-sensorless Feedback Control
244
5.1 PI Control from Stator Current Errors
245
5.2 Global Control with Flux Measurements
251
5.3 Adaptive Control with Flux Measurements
259
5.4 Adaptive Control with Uncertain Load Torque
275
5.5 Adaptive Control with Uncertain Load Torque and Rotor Resistance
291
5.6 Conclusions
301
Problems
304
6 Conclusions
307
Appendix A - Lyapunov Stability
312
Appendix B - Nonlinear Control Theory
323
Bibliographical Notes
343
References
347
Index
359
