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Decentralized direct adaptive neural network control for a class of interconnected systems

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2 Author(s)
Tianping, Zhang ; Dept of Computer, Coll. of Information Engineering, Yangzhou Univ., Yangzhou 225009, P. R. China ; Jiandong, Met

The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconnections is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized direct adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local informatioa According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.

Published in:

Systems Engineering and Electronics, Journal of  (Volume:17 ,  Issue: 2 )