Journal of Systems Engineering and Electronics ›› 2006, Vol. 17 ›› Issue (2): 374-380.doi: 10.1016/S1004-4132(06)60064-9

• CONTROL THEORY AND APPLICATION • Previous Articles     Next Articles

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

Zhang Tianping & Met Jiandong   

  1. Dept of Computer, Coll. of Information Engineering, Yangzhou Univ. , Yangzhou 225009, P. R. China
  • Online:2006-06-26 Published:2019-12-20


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.

Key words: neural networks, decentralized control, sliding mode control, adaptive control, global stability