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

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

Induction vehicles are crucial workhorses in undefined. they're usually used as constant-speed drives whilst fed from a voltage resource of mounted frequency. creation of complicated strength digital converters and robust electronic sign processors, notwithstanding, has made attainable the advance of excessive functionality, adjustable velocity AC motor drives.

This e-book goals to discover new components of induction motor keep an eye on in response to man made intelligence (AI) strategies with a purpose to make the controller much less delicate to parameter adjustments. chosen AI recommendations are utilized for various induction motor regulate thoughts. The booklet offers a realistic machine simulation version of the induction motor which may be used for learning numerous induction motor force operations. The keep an eye on suggestions explored comprise expert-system-based acceleration keep an eye on, hybrid-fuzzy/PI two-stage regulate, neural-network-based direct self regulate, 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 numerous AI ideas.

  • Presents significant man made intelligence ideas to induction motor drives
  • Uses a realistic simulation method of get readers begun on force improvement
  • Authored via skilled scientists with over two decades of expertise within the box
  • Provides quite a few examples and the most recent learn effects
  • Simulation courses on hand from the book's better half web site

This ebook should be precious to graduate scholars and learn engineers who focus on electrical motor drives, electrical automobiles, 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 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 regulate (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 regulate (pages 109–132):
Chapter 6 Hybrid Fuzzy/PI Two?Stage keep watch over (pages 133–166):
Chapter 7 Neural?Network?based Direct Self keep an eye on (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 options according to 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 resources for Applied Intelligent Control of Induction Motor Drives

Example text

15). The flux ler ¼ ledr þ jleqr and pler can be obtained directly from the outputs of the electromechanical block. When the two-phase quantities (voltages or currents) are transformed to three-phase coordinates, the peak value of the three phase quantities is 2/3 times of the two-phase quantities. 6 is jVs j ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 e 2 e 2 3 ðVds Þ þ ðVqs Þ . The parameters of the induction motor used for simulation are listed under ‘Motor 1’ of Appendix B. To illustrate the application of the dynamic model of the induction motor to transient motor operation, a simulation study of direct-on-line starting is demonstrated.

3 Neural-Network Control Scheme (Bose, 1997b; Simoes and Bose, 1995) Neural network is the most generic form of AI for emulation of human thinking compared to expert systems and fuzzy logic. In 1943, McCulloch and Pitts first proposed a network composed of binary-valued artificial neurons that were capable of performing simple threshold logic computations. The modern era of neural network with rejuvenated research practically started in 1982 when Hopfield presented his invention. Since then, many network models and learning rules have been introduced.

Feedback signal F ¼ 6 6 iqs 7 ¼ qðxÞ; where x ¼ 6 s 7 or x ¼ 6 s 7 6 s 7 6 ldr 7 6 Vds 7 5 5 4 ldr 5 4 4 s s l V qs qr TL " # ids ðT*ÀT; lsdr *Àlsdr ; yr Þ b. Control function u ¼ iqs ðT*ÀT; lsdr *Àlsdr ; yr Þ with the field-orientation conditions: leqr ¼ 0 and ledr ¼ const: c. Control strategies: coordinate transformations, current controlled and field-orientation conditions. 5. Indirect FOC algorithm (Trzynadlowski, 1994): a. Feedback signal F ¼ ½ yr Š " s # ids ðT*ÀT; lsdr *Àlsdr ; yr Þ b. Control function u¼ s iqs ðT*ÀT; lsdr *Àlsdr ; yr Þ Philosophy of Induction Motor Control 21 with the field-orientation conditions: leqr ¼ 0 and ledr ¼ const: Control strategies: coordinate transformations, current controlled and field orientation conditions.

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