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E-raamat: Sensorless AC Electric Motor Control: Robust Advanced Design Techniques and Applications

  • Formaat: PDF+DRM
  • Sari: Advances in Industrial Control
  • Ilmumisaeg: 16-Mar-2015
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319145860
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  • Formaat: PDF+DRM
  • Sari: Advances in Industrial Control
  • Ilmumisaeg: 16-Mar-2015
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319145860

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This monograph shows the reader how to avoid the burdens of sensor cost, reduced internal physical space, and system complexity in the control of AC motors. Many applications fields—electric vehicles, wind- and wave-energy converters and robotics, among them—will benefit.
Sensorless AC Electric Motor Control describes the elimination of physical sensors and their replacement with observers, i.e., software sensors. Robustness is introduced to overcome problems associated with the unavoidable imperfection of knowledge of machine parameters—resistance, inertia, and so on—encountered in real systems. The details of a large number of speed- and/or position-sensorless ideas for different types of permanent-magnet synchronous motors and induction motors are presented along with several novel observer designs for electrical machines. Control strategies are developed using high-order, sliding-mode and quasi-continuous-sliding-mode techniques and two types of observer–controller schemes based on backstepping and sliding-mode techniques are described. Experimental results validate the performance of these observer and controller configurations with test trajectories of significance in difficult sensorless-AC-machine problems.
Control engineers working with AC motors in a variety of industrial environments will find the space-and-cost-saving ideas detailed in Sensorless AC Electric Motor Control of much interest. Academic researchers and graduate students from electrical, mechanical and control-engineering backgrounds will be able to see how advanced theoretical control can be applied in meaningful real systems.
1 Dynamical Models of AC Machines 1(44)
1.1 Applications of AC Machines
1.2 Electric Vehicles: Traction System
1(5)
1.3 The Concordia/Clark and Park Transformations
6(6)
1.3.1 The Park Transformation Preserving Amplitude
7(1)
1.3.2 The Clarke Transformation
8(1)
1.3.3 The Park Transformation Preserving Power
9(1)
1.3.4 The Concordia Transformation
10(1)
1.3.5 Transformation Matrices
11(1)
1.3.6 Transformation from a Stationary Reference (α, β, 0) Frame to a Rotating Reference (d, q, 0) Frame
11(1)
1.4 Permanent Magnet Synchronous Motor
12(15)
1.4.1 Description
12(1)
1.4.2 Classification of Permanent Magnet Synchronous Motors (PMSM)
12(2)
1.4.3 Modeling Assumptions
14(8)
1.4.4 Nonlinear Model in State-Space Representation
22(5)
1.5 Induction Motor
27(12)
1.5.1 Motor Description and Modeling Assumptions
27(1)
1.5.2 Dynamic Model of the Induction Motor
28(3)
1.5.3 IM Model in the State-Space Representation
31(8)
1.6 Operating Conditions and Benchmark
39(5)
1.6.1 Benchmarks for AC Machines
39(1)
1.6.2 Experimental Setup
40(4)
1.7 Conclusions
44(1)
1.8 Bibliographical Notes
44(1)
2 Observability Property of AC Machines 45(34)
2.1 Observability Property of AC Machines
45(2)
2.2 Observability
47(7)
2.2.1 Observability of Linear Systems
47(1)
2.2.2 Observability of Nonlinear Systems
47(7)
2.3 Permanent Magnet Synchronous Motor Observability Analysis (PMSM)
54(8)
2.3.1 IPMSM Observability Analysis
55(5)
2.3.2 SPMSM Observability Analysis
60(2)
2.4 Induction Motor Observability Analysis
62(13)
2.4.1 Mathematical Model in the (d, q) Rotor Flux Frame
62(1)
2.4.2 Introduction to the Sensorless IM Observability
63(1)
2.4.3 Induction Motor Observability with Speed Measurement
63(2)
2.4.4 Observability of the Induction Motor: Sensorless Case
65(9)
2.4.5 Unobservability Line
74(1)
2.5 Normal Forms for Observer Design
75(2)
2.6 Conclusions
77(1)
2.7 Bibliographical Notes
78(1)
3 Observer Design for AC Motors 79(42)
3.1 Observers for Nonlinear Systems
80(15)
3.1.1 Definitions and Preliminary Results
81(1)
3.1.2 A High Gain Observer
81(3)
3.1.3 Kalman-Like Observers
84(11)
3.2 PMSM Adaptive Interconnected Observers
95(11)
3.2.1 Adaptive Interconnected Observers for SPMSM
95(6)
3.2.2 Adaptive Interconnected Observers for IPMSM
101(5)
3.3 High Order Sliding Mode Observers for PMSM
106(8)
3.3.1 Sliding Mode Observers
106(1)
3.3.2 High Order Sliding Mode Observer for SPMSM
107(5)
3.3.3 HOSM Interconnected Observers for IPMSM: Rotor Speed and Stator Resistance Estimation
112(2)
3.4 Adaptive Interconnected Observer for the Induction Motor
114(2)
3.5 Conclusions
116(1)
3.6 Bibliographical Notes
116(5)
4 Robust Synchronous Motor Controls Designs (PMSM and IPMSM) 121(22)
4.1 Backstepping Control
121(7)
4.1.1 Backstepping Control of SPMSM
122(3)
4.1.2 Integral Backstepping Control of IPMSM
125(3)
4.2 High-Order Sliding Mode Control
128(9)
4.2.1 High-Order Sliding Mode Control of SPMSM
129(3)
4.2.2 MTPA Current Reference for IPMSM
132(1)
4.2.3 High-Order Sliding Mode Control of IPMSM
133(4)
4.3 Conclusions
137(1)
4.4 Bibliographical Notes
137(6)
5 Robust Induction Motor Controls Design (IM) 143(20)
5.1 Field-Oriented Control
143(6)
5.1.1 Speed and Flux References
144(2)
5.1.2 Flux Controller Design
146(1)
5.1.3 Speed Control Design
147(2)
5.2 Integral Backstepping Control and Field-Oriented Control
149(6)
5.2.1 Speed and Flux Loops
150(1)
5.2.2 Current Loops
151(4)
5.3 High-Order Sliding Mode Control
155(6)
5.3.1 Introduction
155(1)
5.3.2 Application to the Induction Motor Control
155(6)
5.4 Conclusions
161(1)
5.5 Bibliographical Notes
162(1)
6 Sensorless Output Feedback Control for SPMSM and IPMSM 163(38)
6.1 Robust Adaptive Backstepping Sensorless Control
163(22)
6.1.1 SPMSM Case
163(10)
6.1.2 IPMSM Case
173(12)
6.2 Robust Adaptive High Order Sliding Mode Control
185(13)
6.2.1 SPMSM Case
185(6)
6.2.2 IPMSM Case
191(7)
6.3 Conclusions
198(1)
6.4 Bibliographical Notes
198(3)
7 Sensorless Output Feedback Control for Induction Motor 201(34)
7.1 Classical Sensorless Field-Oriented Control
201(9)
7.1.1 Trajectory Tracking for Sensorless Field-Oriented Control
201(5)
7.1.2 Experimental Results
206(2)
7.1.3 Conclusion
208(2)
7.2 Robust Adaptive Observer-Backstepping Sensorless Control
210(6)
7.2.1 Sensorless Observer-Controller Scheme Stability Analysis
210(1)
7.2.2 Experimental Results
211(4)
7.2.3 Conclusions
215(1)
7.3 Robust Adaptive High Order Sliding Mode Control
216(15)
7.3.1 Analysis of the Closed-Loop System
222(1)
7.3.2 Experimental Results
223(4)
7.3.3 Conclusions
227(4)
7.4 Conclusions
231(1)
7.5 Bibliographical Notes
231(4)
8 Conclusions 235(2)
References 237(6)
Index 243
Alain Glumineau received the PhD degree in Automatic Control  in 1981 from  the school of Mechanical Engineering, Nantes University,  France. Since 1982 he has been with the IRCCyN Laboratory (http://www.irccyn.ec-nantes.fr) in Ecole Centrale de Nantes, France,  as Associate Professor then Full Professor. Alain Glumineau's current interests concern theoretical issues in nonlinear control with applications mainly to electric and pneumatic systems.

Jesús de León Morales received the Ph.D. degree in Automatic Control from Claude Bernard Lyon 1 University, France, in 1992. Since 1993, he is a Professor of Electrical Engineering at Universidad Autonoma de Nuevo Leon, Mexico. He is currently working on applications of control theory, electrical machines, nonlinear observers and power systems.