Robust speed-controlled induction motor drive based on recurrent neural network

This paper proposes a recurrent neural network speed controller for an induction motor drive. This speed controller consists of a recurrent neural network identifier (RNNI) and recurrent neural network controller (RNNC). The RNNI is used to provide real-time adaptive identification of the unknown motor dynamics. The RNNC is used to produce an adaptive control force so that the motor speed can accurately track the reference command. A back-propagation algorithm was used as the learning algorithm to automatically adjust the weights of the RNNI and RNNC in order to minimize the performance functions. The proposed control scheme can quickly estimate the plant parameters and produce a control force, such that the motor speed can accurately track the reference command. Both computer simulations and experimental results demonstrated that the proposed control scheme was able to obtain robust speed control.

[1]  Nobuyuki Matsui,et al.  Autocompensation of torque ripple of direct drive motor by torque observer , 1993 .

[2]  Kwang Y. Lee,et al.  An optimal tracking neuro-controller for nonlinear dynamic systems , 1996, IEEE Trans. Neural Networks.

[3]  Tien-Chi Chen,et al.  Robust control of induction motor with a neural-network load torque estimator and a neural-network identification , 1999, IEEE Trans. Ind. Electron..

[4]  Shyamala C. Sivakumar,et al.  Online stabilization of block-diagonal recurrent neural networks , 1999, IEEE Trans. Neural Networks.

[5]  Toshio Fukuda,et al.  Theory and applications of neural networks for industrial control systems , 1992, IEEE Trans. Ind. Electron..

[6]  Tien Chi Chen,et al.  Model reference robust speed control for induction-motor drive with time delay based on neural network , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[7]  Kwanghee Nam,et al.  A load torque compensation scheme under the speed measurement delay , 1998, IEEE Trans. Ind. Electron..

[8]  Adel Razek,et al.  Decoupled direct control for PWM inverter-fed induction motor drives , 2002 .

[9]  Faa-Jeng Lin,et al.  RFNN controlled sensorless induction spindle motor drive , 2004 .

[10]  Chih-Yi Huang,et al.  A microcomputer-based induction motor drive system using current and torque control , 1999 .

[11]  Yoshiaki Ichikawa,et al.  Neural network application for direct feedback controllers , 1992, IEEE Trans. Neural Networks.

[12]  Tien-Chi Chen,et al.  Model reference neural network controller for induction motor speed control , 2002 .

[13]  Tommy W. S. Chow,et al.  A recurrent neural-network-based real-time learning control strategy applying to nonlinear systems with unknown dynamics , 1998, IEEE Trans. Ind. Electron..

[14]  Faa-Jeng Lin.  Real-time IP position controller design with torque feedforward control for PM synchronous motor , 1997, IEEE Trans. Ind. Electron..

[15]  Bimal K. Bose,et al.  Modern Power Electronics and AC Drives , 2001 .

[16]  Aitor J. Garrido,et al.  A sensorless variable structure control of induction motor drives , 2004 .

[17]  R. Kotaru,et al.  Neural net-based robust controller design for brushless DC motor drives , 1999, IEEE Trans. Syst. Man Cybern. Part C.

[18]  Mietek A. Brdys,et al.  Dynamic neural controllers for induction motor , 1999, IEEE Trans. Neural Networks.

[19]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[20]  Michele Milano,et al.  Linear quadratic state feedback and robust neural network estimator for field-oriented-controlled induction motors , 1999, IEEE Trans. Ind. Electron..