Mixed Modified Recurring Rogers-Szego Polynomials Neural Network Control with Mended Grey Wolf Optimization Applied in SIM Expelling System
Chen Der-Fa,
Yi-Cheng Shih,
Shih-Cheng Li,
Chin-Tung Chen and
Jung-Chu Ting
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Chen Der-Fa: Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan
Yi-Cheng Shih: Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan
Shih-Cheng Li: Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan
Chin-Tung Chen: Graduate School of Vocational and Technological Education, National Yunlin University of Science and Technology, Yunlin 640, Taiwan
Jung-Chu Ting: Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan
Mathematics, 2020, vol. 8, issue 5, 1-28
Abstract:
Due to a good ability of learning for nonlinear uncertainties, a mixed modified recurring Rogers-Szego polynomials neural network (MMRRSPNN) control with mended grey wolf optimization (MGWO) by using two linear adjusted factors is proposed to the six-phase induction motor (SIM) expelling continuously variable transmission (CVT) organized system for acquiring better control performance. The control system can execute MRRSPNN control with a fitted learning rule, and repay control with an evaluated rule. In the light of the Lyapunov stability theorem, the fitted learning rule in the MRRSPNN control can be derived, and the evaluated rule of the repay control can be originated. Besides, the MGWO by using two linear adjusted factors yields two changeable learning rates for two parameters to find two ideal values and to speed-up convergence of weights. Experimental results in comparisons with some control systems are demonstrated to confirm that the proposed control system can achieve better control performance.
Keywords: six-phase induction motor; Rogers-Szego polynomials neural network; grey wolf optimization; Lyapunov stability theorem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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