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

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

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

This e-book goals to discover new components of induction motor regulate according to synthetic intelligence (AI) recommendations on the way to make the controller much less delicate to parameter adjustments. chosen AI concepts are utilized for various induction motor keep watch over innovations. The booklet offers a pragmatic laptop simulation version of the induction motor which may be used for learning a number of induction motor force operations. The regulate concepts explored contain expert-system-based acceleration keep an eye on, hybrid-fuzzy/PI two-stage regulate, neural-network-based direct self keep an eye on, and genetic set of rules established prolonged Kalman clear out for rotor pace estimation. There also are chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM procedure, and experimental investigations. A bankruptcy is equipped as a primer for readers to start with simulation reports on a variety of AI strategies.

  • Presents significant man made intelligence options to induction motor drives
  • Uses a realistic simulation method of get readers began on force improvement
  • Authored through skilled scientists with over two decades of expertise within the box
  • Provides various examples and the most recent study effects
  • Simulation courses on hand from the book's significant other web site

This e-book may be beneficial to graduate scholars and examine engineers who focus on electrical motor drives, electrical autos, and electrical send propulsion. Graduate scholars in clever regulate, utilized electrical movement, and effort, in addition to engineers in business electronics, automation, and electric transportation, also will locate this booklet important.

Simulation fabrics on hand for obtain at
Chapter 1 advent (pages 1–7):
Chapter 2 Philosophy of Induction Motor regulate (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 keep an eye on (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 filter out for pace Estimation (pages 243–271):
Chapter 10 Optimized Random PWM suggestions in accordance 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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Extra info for Applied Intelligent Control of Induction Motor Drives

Sample text

GA searches a population of points in parallel instead of a single point. 2. GA does not require derivative information or other auxiliary knowledge; only the objective function and the corresponding fitness levels will influence the directions of search. 3. GA uses probabilistic transition rules instead of deterministic ones. In this book, a real-coded genetic algorithm is proposed to optimize the extended Kalman filter (EKF) for estimating the rotor speed of an induction motor. It is shown that the real-coded GA is effective for optimizing the EKF performance of three different controllers, namely the closedloop V/Hz controller, DSC, and FOC.

Based on the nonlinear control theory as well as the human ability to comprehend, reason, and learn, intelligent techniques may be used to overcome the above difficulties. 7 17 Intelligent Induction Motor Control Schemes Intelligence is defined as the ability to comprehend, reason, and learn. The definition of intelligent control from Astr€ om and McAvoy has been used widely: ‘An intelligent control system has the ability to comprehend, reason, and learn about processes, disturbances and operating conditions in order to optimize the performance of the process under consideration’  (Astr€ om and Bj€ orn, 1995).

5th equation: s s ; iqs ; oo g. with state variables flsdR ; lsqR ; ids 6th equation: s s ; iqR ; oo g. 14), rotor speed oo, rotor fluxes ðlsdr ; lsqr Þ, and stator currents ðids ; iqs Þ are the states, while rotor inertia J, stator and rotor inductances (Ls, Lr), mutual inductance LM, stator and rotor resistances (Rs, Rr), and the number of poles P are the parameters. The voltages s s ðVds ; Vqs Þ are inputs, and TL is the load torque. From the ‘T’ equivalent circuit, another six fifth-order equations with different state variables can be obtained: 7th equation: s s with state variables flsdM ; lsqM ; ids ; iqs ; oo g.

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