PID Adaptive Control in the Application of the Induction Motor System Based on the RBF Neural Network Inverse

Abstract:

In view of the nonlinear mapping ability of artificial neural network, the ability of self-learning and adaptive uncertainty system dynamic characteristic, fault tolerant and generalization ability and parallel processing ability, etc., the article puts forward a PID adaptive control algorithm based on neural network inverse as well, introducing RBF neural network to the inverse control, and operating PID integration. In a sudden external disturbance and model parameter change, the control scheme can significantly reduce resistance perturbation influence on speed, and strong robustness on parameter variations and external disturbances of the system.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 2393-2396
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.2393
• Online since: May 2014
• Authors: Zhang Li*, Yu Bo
• Keywords: Adaptive Control, Induction Motor (IM), Inverse System, RBF Neural Network

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