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- W2897536407 abstract "In order to reduce effect of nonlinear time-varying uncertainty for a continuously variable transmission (CVT) system driven by synchronous reluctance motor (SynRM), a blend recurrent Gegenbauer orthogonal polynomials neural network adaptive particle swarm optimization (OPNNAPSO) control system is proposed in this paper. The blend recurrent Gegenbauer OPNNAPSO control system consists of a censor control, a recurrent Gegenbauer OPNN control with adaptive law based on Lyapunov stability and a recompensed control. Furthermore, the adaptive particle swarm optimization (APSO) is proposed for regulating two varied learning rates of parameters in the recurrent Gegenbauer OPNN to obtain better dynamic response and faster convergence. Finally, comparative studies demonstrated by experimental results are illustrated to verify the effectiveness of the proposed control scheme." @default.
- W2897536407 created "2018-10-26" @default.
- W2897536407 creator A5032399102 @default.
- W2897536407 date "2016-08-01" @default.
- W2897536407 modified "2023-09-26" @default.
- W2897536407 title "Application of SynRM Driving CVT System Using Blend Recurrent Gegenbauer OPNNAPSO Control" @default.
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- W2897536407 doi "https://doi.org/10.1109/icaums.2016.8479990" @default.
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