Electromagnetic torque control for six-phase induction motor expelled continuously variable transmission clumped system using sage dynamic control system

Abstract

The continuously variable transmission (CVT) clumped system with lots of nonlinear uncertainties operated by the six-phase induction motor (SIM) is lacking in good control performance for using the linear control. In light of good ability of learning for nonlinear uncertainties, the sage dynamic control system using mixed modified recurrent Rogers–Szego polynomials neural network (MMRRSPNN) control and revised grey wolf optimization (RGWO) with two adjusted factors is proposed to acquire better control performance. The MMRRSPNN control and RGWO with two adjusted factors can execute intendant control, modified recurrent Rogers–Szego polynomials neural network (MRRSPNN) control with a fitted learning rule, and repay control with an evaluated rule. In addition, in the light of the Lyapunov stability theorem, the fitted learning rule in the MRRSPNN and the evaluated rule of the repay control are founded. Besides, the RGWO with two adjusted factors yields two changeable learning rates for two weights parameters to find two optimal values and to speed-up convergence of two weights parameters. Experimental results in comparisons with those control systems are demonstrated to confirm that the proposed control system can achieve better control performance.