Adaptive Fault-Tolerant Control for Stochastic Nonlinear Systems With Unknown Output Dead-Zones

IF 3.8 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-09-02 Epub Date: 2026-05-04 DOI:10.1002/acs.70102

Yixuan Yuan, Liping Xie, Junsheng Zhao, Kanjian Zhang

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Abstract

The present paper investigates the fault-tolerant control problem for nonlinear systems with stochastic noise and dead-zone output. In contrast to the extant literature, the present work effectively compensates for the impact of unknown dead-zone output on the system by constructing a dead-zone output approximation model and introducing a Nussbaum-type function. Furthermore, considering the multiple effects of stochastic noise and actuator faults, this paper employs a fault-tolerant control strategy to reduce the risk of system performance degradation and ensure system safety. On this basis, an efficient and readily deployable fault-tolerant control scheme is proposed through further integration of adaptive techniques and fuzzy logic systems. The stability of the system is thoroughly analyzed by constructing a Lyapunov function and incorporating desired performance criteria, which proves the stability of the proposed control scheme. The efficacy and practicability of the proposed control scheme are substantiated by two simulation illustrations.

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输出死区未知的随机非线性系统的自适应容错控制

研究了具有随机噪声和死区输出的非线性系统的容错控制问题。与现有文献相比，本文通过构造死区输出近似模型和引入nussbaum型函数，有效地补偿了未知死区输出对系统的影响。此外，考虑随机噪声和执行器故障的多重影响，采用容错控制策略，降低系统性能下降的风险，保证系统安全。在此基础上，进一步将自适应技术与模糊逻辑系统相结合，提出了一种高效、易部署的容错控制方案。通过构造李雅普诺夫函数并结合期望的性能准则，对系统的稳定性进行了深入分析，证明了所提控制方案的稳定性。通过两个仿真实例验证了所提控制方案的有效性和实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.