A Six-Phase CRIM Driving CVT using Blend Modified Recurrent Gegenbauer OPNN Control

作者：Lin Chih Hong

来源：Journal of Power Electronics, 2016, 16(4): 1438-1454.

DOI：10.6113/JPE.2016.16.4.1438

• Artificial bee colony optimization
• Lyapunov stability theorem
• Modified recurrent Gegenbauer orthogonal polynomial neural network
• Six-phase copper rotor induction motor

Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.

• 出版日期2016-7