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

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

Induction automobiles are crucial workhorses in undefined. they're in general used as constant-speed drives while fed from a voltage resource of fastened frequency. introduction of complicated strength digital converters and robust electronic sign processors, despite the fact that, has made attainable the improvement of excessive functionality, adjustable velocity AC motor drives.

This ebook goals to discover new components of induction motor keep an eye on in response to man made intelligence (AI) strategies so that it will make the controller much less delicate to parameter adjustments. chosen AI innovations are utilized for various induction motor keep an eye on suggestions. The e-book offers a realistic computing device simulation version of the induction motor that may be used for learning a number of induction motor force operations. The keep an eye on thoughts explored contain expert-system-based acceleration keep an eye on, hybrid-fuzzy/PI two-stage keep an eye on, neural-network-based direct self regulate, and genetic set of rules dependent prolonged Kalman clear out for rotor pace estimation. There also are chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM approach, and experimental investigations. A bankruptcy is equipped as a primer for readers to start with simulation stories on a number of AI innovations.

  • Presents significant man made intelligence suggestions to induction motor drives
  • Uses a realistic simulation method of get readers began on force improvement
  • Authored by means of skilled scientists with over twenty years of expertise within the box
  • Provides a number of examples and the newest study effects
  • Simulation courses on hand from the book's better half site

This publication should be worthwhile to graduate scholars and study engineers who focus on electrical motor drives, electrical cars, 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 e-book important.

Simulation fabrics to be had for obtain at
Chapter 1 creation (pages 1–7):
Chapter 2 Philosophy of Induction Motor keep an eye on (pages 9–30):
Chapter three Modeling and Simulation of Induction Motor (pages 31–74):
Chapter four basics of clever keep an eye on Simulation (pages 75–108):
Chapter five Expert?System?Based Acceleration keep watch over (pages 109–132):
Chapter 6 Hybrid Fuzzy/PI Two?Stage regulate (pages 133–166):
Chapter 7 Neural?Network?based Direct Self regulate (pages 167–197):
Chapter eight Parameter Estimation utilizing Neural Networks (pages 199–241):
Chapter nine GA?Optimized prolonged Kalman clear out for velocity Estimation (pages 243–271):
Chapter 10 Optimized Random PWM recommendations 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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6), torque T may be expressed as a function of stator current iss and stator flux lsm while the lsm is a function of iss and stator voltage Vss . 24) is used as a control function while the acceleration doo/dt and iss are obtained or derived from the measured signals. Although the concept of acceleration control can be explained using the above theory, the details of the control scheme need to be developed at the algorithm level (Shi, Chan, and Wong, 1997). 6 Need for Intelligent Control The difficulties that arise in induction motor control can be classified under three categories: (a) complex computation, (b) nonlinearity, (c) uncertainty (Narendra and Mukhopadhyay, 1996).

GðtÞ x a. Input-output pair ¼ z IMðxÞ where x is the input samples, z is the outputs, g(t) denotes the generation function of input samples, and IM denotes the plant outputs. ' w x b. Training ¼ Re f b z where w is the weight of network, b is the bias of network, f denotes the activation function, and Re denotes the training algorithm. c. Implementation z0 ¼ f ðwx0 þ bÞ 0 where z denotes the output of neural-network and x0 denotes the practical inputs. ). The selection of these functions often depends on the applications of neural network.

K. L. Ho, “Modeling and simulation of a novel two-stage controller for an induction motor,” International Association of Science and Technology for Development (IASTED) Journal on Power and Energy Systems, 19(3), 257–264, Ó 1999, with the permission from ACTA Press. Applied Intelligent Control of Induction Motor Drives, First Edition. Tze-Fun Chan and Keli Shi. © 2011 John Wiley & Sons (Asia) Pte Ltd. Published 2011 by John Wiley & Sons (Asia) Pte Ltd. ISBN: 978-0-470-82556-3 32 Applied Intelligent Control of Induction Motor Drives Modeling and simulation of the three-phase induction machine is well documented in the literature and digital computer solution can be performed using several methods, such as numeric programming, symbolic programming and the electromagnetic transient program (EMTP) (Domijan and Yin, 1994).

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