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Predefined Performance Fuzzy Control for Hysteresis Stochastic Nonlinear Systems

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Abstract

Predefined performance control (PPC) has been applied to many engineering fields, such as unmanned aerial vehicle, emergency braking, and so on. Note that above engineering applications have the characteristic of hysteresis, which results in degraded performance for most existing PPC schemes. This paper investigates the problem of PPC for stochastic nonlinear systems with hysteresis input. Different from existing PPC schemes, an improved finite-time performance function is introduced to select the desired convergence time flexibly. By incorporating an intermediate parameter into the controller, a novel control design framework is presented to adaptively compensate hysteresis input. Besides, the unknown nonlinear dynamics of the systems are approximated by fuzzy logic systems, and the computational complexity problem is reduced by using dynamic surface control technique. Then, the proposed control scheme ensures that tracking error converges to the specific region, which can be set arbitrarily within the physical limitations. Finally, two examples are provided to demonstrate the validity of proposed scheme.

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Acknowledgements

Supported in part by the National Natural Science Foundation of China under Grant (62301212,62371182), the Program for Science and Technology Innovation Talents in the University of Henan Province under Grant (23HASTIT021), Major Science and Technology Projects of Longmen Laboratory under Grant (231100220300), Aeronautical Science Foundation of China under Grant (20220001042002), the Science and Technology Development Plan of Joint Research Program of Henan under Grant (222103810036, 225200810007), the Scientific and Technological Project of Henan Province under Grant (222102240009).

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Authors and Affiliations

  1. College of Information Engineering, Henan University of Science and Technology, Luoyang, 471023, Henan, China

    Fazhan Tao, Hanzheng Ju, Zhumu Fu, Nan Wang & Haoxiang Ma

  2. Longmen Laboratory, Luoyang, 471023, Henan, China

    Fazhan Tao

  3. Key Laboratory of Robot and Intelligent System of Henan Province, Henan University of Science and Technology, Luoyang, 471023, Henan, China

    Hanzheng Ju, Zhumu Fu & Haoxiang Ma

  4. Luoyang Normal University, Luoyang, 471934, Henan, China

    Mengyang Li

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  1. Fazhan Tao
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Correspondence to Zhumu Fu.

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Tao, F., Ju, H., Fu, Z. et al. Predefined Performance Fuzzy Control for Hysteresis Stochastic Nonlinear Systems. Int. J. Fuzzy Syst. 26, 1313–1327 (2024). https://doi.org/10.1007/s40815-023-01668-x

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  • DOI: https://doi.org/10.1007/s40815-023-01668-x

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