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Neural Computing and Applications

, Volume 17, Issue 4, pp 339–345 | Cite as

Neural adaptive control for a class of nonlinear systems with unknown deadzone

  • Zhonghua Wang
  • Yong Zhang
  • Hui Fang
Original Article

Abstract

This paper focuses on the adaptive control of a class of nonlinear systems with unknown deadzone using neural networks. By constructing a deadzone pre-compensator, a neural adaptive control scheme is developed using backstepping design techniques. Transient performance is guaranteed and semi-globally uniformly ultimately bounded stability is obtained. Another feature of this scheme is that the neural networks reconstruction error bound is assumed to be unknown and can be estimated online. Simulation results are given to demonstrate the effectiveness of the proposed controller.

Keywords

Deadzone Adaptive control Neural networks Nonlinear systems Backstepping Robust control 

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Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  1. 1.School of Control Science and EngineeringUniversity of JinanJinanPeople’s Republic of China

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