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<p>In this research, a class of stochastic nonstrict feedback systems with state variables subject to function constraints is investigated. Traditional approaches introduce Barrier Lyapunov Functions (BLF) to avoid violations of function constraints. However, the presence of stochastic disturbances leads to differential explosion when directly employing BLF, resulting inefficient non-functional components into the control strategy. To alleviate the challenges posed by asymmetric constraints dependent on time and state variables in control systems, this study focuses on the design of a controller for stochastic systems. Furthermore, to overcome the need for redundant derivatives and complex parameter design, the controller adopts a combination of fuzzy observer and dynamic filtering techniques. Finally, in order to enhance the practicality of the controller and conserve communication resources, controller quantization is considered in this research. The practicability of the proposed method is demonstrated through a numerical calculation and a concise simulation example of the Continuous Stirred Tank Reactor (CSTR) model.</p>

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Dynamic Filtering Fuzzy Control for Nonstrict Feedback Stochastic Systems with State Function Constraints

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Liping Xie,
  • Sijia Chen,
  • Shixiong Fang,
  • Kanjian Zhang

摘要

In this research, a class of stochastic nonstrict feedback systems with state variables subject to function constraints is investigated. Traditional approaches introduce Barrier Lyapunov Functions (BLF) to avoid violations of function constraints. However, the presence of stochastic disturbances leads to differential explosion when directly employing BLF, resulting inefficient non-functional components into the control strategy. To alleviate the challenges posed by asymmetric constraints dependent on time and state variables in control systems, this study focuses on the design of a controller for stochastic systems. Furthermore, to overcome the need for redundant derivatives and complex parameter design, the controller adopts a combination of fuzzy observer and dynamic filtering techniques. Finally, in order to enhance the practicality of the controller and conserve communication resources, controller quantization is considered in this research. The practicability of the proposed method is demonstrated through a numerical calculation and a concise simulation example of the Continuous Stirred Tank Reactor (CSTR) model.