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Speed control of induction motor using neural network sliding mode controller

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2 Author(s)
Kang Peng ; Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China ; Jin Zhao

In this paper, a new control scheme for speed control is proposed that utilizes sliding mode control (SMC) and radial basis function neural network (RBFNN) to achieve the robustness. First, the design of conventional sliding mode control scheme is investigated. However, the bounds of uncertainties in the induction motor are needed to preserve the robust property. The proposed neural network sliding mode control law can avoid calculating the limits of the uncertainties in the induction motor, and be robust to these uncertainties. Unlike conventional SMC, a RBFNN controller replaces the output of the sliding mode controller to eliminate undesired chattering. Finally, computer simulation results have demonstrated that the proposed control scheme provides robust dynamic characteristics without large chattering.

Published in:

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Date of Conference:

15-17 April 2011