Digital implementation of neural network inverse control for induction motor based on DSP

The induction motor is multi-variable, nonlinear and strong-coupled system. Due to parameters' variation during operation of induction motor, the decoupling and linearization implemented by field oriented control and analytical inverse control is destroyed. For that, a novel linearization and decoupling method named as artificial neural network(ANN) inverse for induction motor control is proposed. With the combination of neural network and inverse system decoupling control method, the inverse model of induction motor is constructed by neural network and integrator. The neural network inverse system which has good robustness was obtained through reasonable and effective training. A pseudo-linear composite system was obtained by cascading the induction motor and neural network inverse system, and dynamic decoupling of induction motor was achieved. On the basis of dynamic decoupling for induction motor, A neural network inverse control scheme based on DSP for induction motor drive is presented. The hardware structure and software design of the neural network inverse control scheme are described in details. The experiment results show that the proposed scheme has excellent dynamic and static control performance.

[1]  T.G. Habetler,et al.  High-performance induction motor speed control using exact feedback linearization with state and state derivative feedback , 2003, IEEE Transactions on Power Electronics.

[2]  Xianzhong Dai,et al.  Neural network inverse control of current-fed induction motor , 2008, 2008 IEEE International Symposium on Industrial Electronics.

[3]  Dai Xian.  Neural Network Inverse Synchronous Control of Two-motor Variable Frequency Speed-regulating System , 2005 .

[4]  Guohai Liu,et al.  Neural Network Inverse Synchronous Control of Two-motor Variable Frequency Speed-Regulating System , 2006, 2006 IEEE International Conference on Networking, Sensing and Control.

[5]  Zhang Hao,et al.  Dynamic decoupling control of bearingless switched reluctance motors based on neural network inverse system , 2005, 2005 International Conference on Electrical Machines and Systems.

[6]  P. Sicard,et al.  Field-oriented control of induction motors using neural-network decouplers , 1997 .

[7]  Frank L. Lewis,et al.  Neural net robot controller with guaranteed tracking performance , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[8]  Frank L. Lewis,et al.  Robust backstepping control of induction motors using neural networks , 2000, IEEE Trans. Neural Networks Learn. Syst..

[9]  Romeo Ortega,et al.  Comparison of two nonlinear controllers for current-fed induction motors , 1997, 1997 European Control Conference (ECC).

[10]  F. Ashrafzadeh,et al.  A novel neural network controller and its efficient DSP implementation for vector controlled induction motor drives , 2002, Conference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344).

[11]  Bimal K. Bose,et al.  Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective , 2007, IEEE Transactions on Industrial Electronics.

[12]  T. G. Habetler,et al.  High-performance induction motor speed control using exact feedback linearization with state and state derivative feedback , 2004 .

[13]  Riccardo Marino,et al.  Global adaptive output feedback control of induction motors with uncertain rotor resistance , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[14]  A. Chu,et al.  A novel neural network controller and its efficient DSP implementation for vector controlled induction motor drives , 2002 .

[15]  Xin Wang,et al.  The ANN Inverse Control of Induction Motor with Robust Flux Observer Based on ESO , 2007, ISNN.

[16]  P.F.A. MacConnell,et al.  Nonlinear adaptive state-feedback speed control of a voltage-fed induction motor with varying parameters , 2006, IEEE Transactions on Industry Applications.