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

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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.

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Authors and Affiliations

  1. School of Control Science and Engineering, University of Jinan, Jinan, 250022, People’s Republic of China

    Zhonghua Wang, Yong Zhang & Hui Fang

Authors
  1. Zhonghua Wang
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  2. Yong Zhang
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  3. Hui Fang
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Correspondence to Zhonghua Wang.

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Wang, Z., Zhang, Y. & Fang, H. Neural adaptive control for a class of nonlinear systems with unknown deadzone. Neural Comput & Applic 17, 339–345 (2008). https://doi.org/10.1007/s00521-007-0124-8

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  • DOI: https://doi.org/10.1007/s00521-007-0124-8

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