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Genetic algorithms-based fuzzy neural network sliding mode control for brushless doubly fed machine

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1 Author(s)
Zongkai Shao ; School of Hydropower & Information Engineering Huazhong University of Science and Technology, Wuhan, China

In this paper, because a genetic algorithms-based fuzzy neural network control is incorporated into the sliding mode control (SMC) to adaptively regulate the adaptive law of SMC, a genetic algorithm fuzzy neural network sliding mode controller (GAFNSMC) for brushless doubly fed machine (BDFM) adjustable speed system is presented. The proposed controller for BDFM eliminates the average chattering encountered by most SMC schemes, and employs the robustness and excellent static and dynamic performances of SMC. Simulation results show that the proposed control strategy is of the feasibility, correctness and effectiveness.

Published in:

2010 International Conference on Computer and Communication Technologies in Agriculture Engineering  (Volume:3 )

Date of Conference:

12-13 June 2010