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Sage Revised Reiterative Even Zernike Polynomials Neural Network Control with Modified Fish School Search Applied in SSCCRIM Impelled System

Author

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  • Chih-Hong Lin

    (Department of Electrical Engineering, National United University, Miaoli 360, Taiwan)

Abstract

In light of fine learning ability in the existing uncertainties, a sage revised reiterative even Zernike polynomials neural network (SRREZPNN) control with modified fish school search (MFSS) method is proposed to control the six-phase squirrel cage copper rotor induction motor (SSCCRIM) impelled continuously variable transmission assembled system for obtaining the brilliant control performance. This control construction can carry out the SRREZPNN control with the cozy learning law, and the indemnified control with an assessed law. In accordance with the Lyapunov stability theorem, the cozy learning law in the revised reiterative even Zernike polynomials neural network (RREZPNN) control can be extracted, and the assessed law of the indemnified control can be elicited. Besides, the MFSS can find two optimal values to adjust two learning rates with raising convergence. In comparison, experimental results are compared to some control systems and are expressed to confirm that the proposed control system can realize fine control performance.

Suggested Citation

  • Chih-Hong Lin, 2020. "Sage Revised Reiterative Even Zernike Polynomials Neural Network Control with Modified Fish School Search Applied in SSCCRIM Impelled System," Mathematics, MDPI, vol. 8(10), pages 1-30, October.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:10:p:1760-:d:426992
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    References listed on IDEAS

    as
    1. Chih-Hong Lin, 2020. "Altered Grey Wolf Optimization and Taguchi Method with FEA for Six-Phase Copper Squirrel Cage Rotor Induction Motor Design," Energies, MDPI, vol. 13(9), pages 1-17, May.
    2. Lidan Wang & Meitao Duan & Shukai Duan, 2013. "Memristive Chebyshev Neural Network and Its Applications in Function Approximation," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, June.
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