Composite recurrent Laguerre orthogonal polynomials neural network dynamic control for continuously variable transmission system using altered particle swarm optimization

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Abstract

The composite recurrent Laguerre orthogonal polynomials neural network (NN) control system using altered particle swarm optimization (PSO) is developed for controlling the V-belt continuously variable transmission (CVT) system driven by permanent magnet synchronous motor to obtain better control performance. The simplified dynamic and kinematic models of a V-belt CVT system are derived by law of conservation. The control system consists of an inspector control, a recurrent Laguerre orthogonal polynomials NN control with adaptation law, and a recouped control with estimation law. Moreover, the adaptation law of online parameters in the recurrent Laguerre orthogonal polynomials NN is originated from Lyapunov stability theorem. Additionally, two optimal learning rates of the parameters by means of altered PSO are posed in order to achieve better convergence. At last, comparative studies shown by experimental results are illustrated to demonstrate the control performance of the proposed control scheme.

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Acknowledgments

The author gratefully acknowledges financial support from Ministry of Science and Technology Grant MOST 103-2221-E-239-016 in Taiwan, R.O.C.

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Correspondence to Chih-Hong Lin.

Additional information

(1) The composite recurrent Laguerre orthogonal polynomials NN control system using altered PSO is designed to control a PM synchronous motor-driven V-belt CVT.

(2) Online tuning parameters of the recurrent Laguerre orthogonal polynomials NN-based Lyapunov stability theorem are developed.

(3) Two optimal learning rates of parameters in the recurrent Laguerre orthogonal polynomials NN using altered PSO are posed.

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Lin, CH. Composite recurrent Laguerre orthogonal polynomials neural network dynamic control for continuously variable transmission system using altered particle swarm optimization. Nonlinear Dyn 81, 1219–1245 (2015). https://doi.org/10.1007/s11071-015-2064-7

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Keywords

  • V-belt continuously variable transmission
  • Permanent magnet synchronous motor
  • Laguerre orthogonal polynomials neural network
  • Lyapunov stability
  • Particle swarm optimization