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Approximation-based adaptive fuzzy control for a class of non-strict-feedback stochastic nonlinear systems

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Abstract

This paper considers the problem of adaptive fuzzy control of a class of single-input/single-output (SISO) nonlinear stochastic systems in non-strict-feedback form. Fuzzy logic systems are used to approximate the uncertain nonlinearities and backstepping technique is utilized to construct an adaptive fuzzy controller. The proposed controller guarantees that all the signals in the resulting closed-loop system are bounded in probability. The main contribution of this note lies in providing a control strategy for a class of nonlinear systems in nonstrict-feedback form. Simulation result is used to test the effectiveness of the suggested approach.

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Authors and Affiliations

  1. School of Mathematics and Physics, Bohai University, Jinzhou, 121000, China

    HuanQing Wang

  2. Institute of Complexity Science, Qingdao University, Qingdao, 266071, China

    HuanQing Wang, Bing Chen & Chong Lin

Authors
  1. HuanQing Wang
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  2. Bing Chen
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  3. Chong Lin
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Correspondence to Bing Chen.

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Wang, H., Chen, B. & Lin, C. Approximation-based adaptive fuzzy control for a class of non-strict-feedback stochastic nonlinear systems. Sci. China Inf. Sci. 57, 1–16 (2014). https://doi.org/10.1007/s11432-013-4785-x

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  • DOI: https://doi.org/10.1007/s11432-013-4785-x

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