Download Applied Intelligent Control of Induction Motor Drives by Tze?Fun Chan, Keli Shi(auth.) PDF

By Tze?Fun Chan, Keli Shi(auth.)

Induction cars are crucial workhorses in undefined. they're as a rule used as constant-speed drives while fed from a voltage resource of mounted frequency. introduction of complicated energy digital converters and strong electronic sign processors, even if, has made attainable the advance of excessive functionality, adjustable velocity AC motor drives.

This booklet goals to discover new components of induction motor keep watch over in line with synthetic intelligence (AI) innovations as a way to make the controller much less delicate to parameter adjustments. chosen AI thoughts are utilized for various induction motor keep watch over innovations. The e-book provides a realistic computing device simulation version of the induction motor that may be used for learning a variety of induction motor force operations. The regulate techniques explored comprise expert-system-based acceleration keep an eye on, hybrid-fuzzy/PI two-stage keep an eye on, neural-network-based direct self keep an eye on, and genetic set of rules established prolonged Kalman clear out for rotor velocity estimation. There also are chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM method, and experimental investigations. A bankruptcy is supplied as a primer for readers to start with simulation reviews on a variety of AI concepts.

  • Presents significant man made intelligence options to induction motor drives
  • Uses a pragmatic simulation method of get readers begun on force improvement
  • Authored through skilled scientists with over twenty years of expertise within the box
  • Provides various examples and the newest study effects
  • Simulation courses on hand from the book's better half web site

This booklet may be worthy to graduate scholars and learn engineers who concentrate on electrical motor drives, electrical automobiles, and electrical send propulsion. Graduate scholars in clever keep an eye on, utilized electrical movement, and effort, in addition to engineers in business electronics, automation, and electric transportation, also will locate this publication invaluable.

Simulation fabrics on hand for obtain at www.wiley.com/go/chanmotorContent:
Chapter 1 advent (pages 1–7):
Chapter 2 Philosophy of Induction Motor keep watch over (pages 9–30):
Chapter three Modeling and Simulation of Induction Motor (pages 31–74):
Chapter four basics of clever keep watch over Simulation (pages 75–108):
Chapter five Expert?System?Based Acceleration keep an eye on (pages 109–132):
Chapter 6 Hybrid Fuzzy/PI Two?Stage keep an eye on (pages 133–166):
Chapter 7 Neural?Network?based Direct Self keep watch over (pages 167–197):
Chapter eight Parameter Estimation utilizing Neural Networks (pages 199–241):
Chapter nine GA?Optimized prolonged Kalman filter out for pace Estimation (pages 243–271):
Chapter 10 Optimized Random PWM ideas in line with Genetic Algorithms (pages 273–311):
Chapter eleven Experimental Investigations (pages 313–371):
Chapter 12 Conclusions and destiny advancements (pages 373–379):

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M. K. Sinha) IEEE Press, New Jersey. , and Matsuse, K. (1996) Speed sensorless control of induction motor, in Sensorless Control of AC Motor Drives (eds K. Rajashekara, A. Kawamura, and K. Matsuse), IEEE Press, New Jersey. , and Tarchioni, L. (1993) A new EKF-based algorithm for flux estimation in induction machines. IEEE Transactions on Industrial Electronics, 40(5), 496–504. K. (1997) A new direct self-control scheme for an inverter-fed induction motor. Second International Power Electronics and Motion Control Conference, Hangzhou, November.

Is an explanation function, and f0 denotes the modification procedure of the knowledge base. Based on the knowledge acquired from control experts in encoded form, the control function is derived by the on-line inference engine. The humanlike knowledge-inference system may be applied to cope with complex induction motor drive systems, or those with parameter uncertainties. 11. Genetic algorithm in control: ! x gðtÞ a. Input-output pair ¼ z IMðxÞ b. c. d. e. 4 where x denotes the input samples, z denotes the outputs, g(t) denotes the generation function of input samples, and IM denotes the plant outputs.

IEEE Transactions on Industrial Electronics, 44, 270–273. W. (1990) Adaptive decoupling control of induction motor drives. IEEE Transactions on Industrial Electronics, 37(1), 41–47. W. (1990) Application of nonlinear observers for rotor position detection on an induction motor using machine voltages and currents. IEEE Industry Applications Society, 416–421. , and Warwick, K. (1995) Dynamic recurrent neural network for system identification and control. IEE Proceedings – Control Theory and Applications, 142(4), 307–314.

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