• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
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  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
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Title Improved Neural Network-Based Self-Tuning fuzzy PID Controller for Induction Motor Speed Control
Authors 김상민 ; 한우용 ; 이창구
Page pp.691-696
ISSN 1975-8359
Keywords Fuzzy PID ; Self-Tuning Matlab/Simulink ; dSPACE(DS1102) ; Induction motor
Abstract This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.