SynRM Driving CVT System Using an ARGOPNN with MPSO Control System

Chih-Hong Lin; Kuo-Tsai Chang

SynRM Driving CVT System Using an ARGOPNN with MPSO Control System

Chih-Hong Lin

Kuo-Tsai Chang

Vol. 19, No. 3, pp. 771-783, May 2019

10.6113/JPE.2019.19.3.771

Continuously variable transmission

Gegenbauer orthogonal polynomials neural network

Particle Swarm Optimization

Synchronous reluctance motor

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Abstract

Due to nonlinear-synthetic uncertainty including the total unknown nonlinear load torque, the total parameter variation and the fixed load torque, a synchronous reluctance motor (SynRM) driving a continuously variable transmission (CVT) system causes a lot of nonlinear effects. Linear control methods make it hard to achieve good control performance. To increase the control performance and reduce the influence of nonlinear time-synthetic uncertainty, an admixed recurrent Gegenbauer orthogonal polynomials neural network (ARGOPNN) with a modified particle swarm optimization (MPSO) control system is proposed to achieve better control performance. The ARGOPNN with a MPSO control system is composed of an observer controller, a recurrent Gegenbauer orthogonal polynomial neural network (RGOPNN) controller and a remunerated controller. To insure the stability of the control system, the RGOPNN controller with an adaptive law and the remunerated controller with a reckoned law are derived according to the Lyapunov stability theorem. In addition, the two learning rates of the weights in the RGOPNN are regulating by using the MPSO algorithm to enhance convergence. Finally, three types of experimental results with comparative studies are presented to confirm the usefulness of the proposed ARGOPNN with a MPSO control system.

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Cite this article

[IEEE Style]

C. Lin and K. Chang, "SynRM Driving CVT System Using an ARGOPNN with MPSO Control System," Journal of Power Electronics, vol. 19, no. 3, pp. 771-783, 2019. DOI: 10.6113/JPE.2019.19.3.771.

[ACM Style]

Chih-Hong Lin and Kuo-Tsai Chang. 2019. SynRM Driving CVT System Using an ARGOPNN with MPSO Control System. Journal of Power Electronics, 19, 3, (2019), 771-783. DOI: 10.6113/JPE.2019.19.3.771.