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<p>Many nonlinear systems in practical engineering encounter random noises and contain unmodeled dynamics and dead-zone inputs, which increase the challenges of system control and lead to poor tracking responses. Considering this problem, in this work, we study the tracking control issue of high-order stochastic nonlinear systems (SNSs) and aim to find a solution. By developing a direct fuzzy control method, proposing a new adaptive control strategy, and utilizing the small gain theorem, a new adaptive tracking controller is constructed to address the difficulties raised by unmodeled dynamics and dead-zone input. By constructing an integral-type Lyapunov function, it is shown that the considered SNSs are input-to-state stable in probability (ISSP) and all system signals are bounded in probability. Numerical and practical examples show the effectiveness of the theory.</p>

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Adaptive Fuzzy Tracking Control of Stochastic Systems with Unmodeled Dynamics, Odd Rational Powers, and Dead-Zone Input

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Zhong-Ao Cui,
  • Lingrong Xue,
  • Zhen-Guo Liu,
  • Zong-Yao Sun

摘要

Many nonlinear systems in practical engineering encounter random noises and contain unmodeled dynamics and dead-zone inputs, which increase the challenges of system control and lead to poor tracking responses. Considering this problem, in this work, we study the tracking control issue of high-order stochastic nonlinear systems (SNSs) and aim to find a solution. By developing a direct fuzzy control method, proposing a new adaptive control strategy, and utilizing the small gain theorem, a new adaptive tracking controller is constructed to address the difficulties raised by unmodeled dynamics and dead-zone input. By constructing an integral-type Lyapunov function, it is shown that the considered SNSs are input-to-state stable in probability (ISSP) and all system signals are bounded in probability. Numerical and practical examples show the effectiveness of the theory.