Distributed fuzzy adaptive fault-tolerant control with unknown time-varying power drift signals and asymmetric dead-zones

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS Fuzzy Sets and Systems Pub Date : 2025-04-15 Epub Date: 2025-01-28 DOI:10.1016/j.fss.2025.109295
Jiyu Zhu , Yadong Yang , Xuan Qiu , Tianping Zhang , Qikun Shen
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Abstract

In this study, we consider the distributed fuzzy fault-tolerant control (FTC) problem for a class of interconnected nonlinear systems with multiple unknown time-varying power drift signals, asymmetric actuator, and output dead-zones. Based on our proposed dead-zone models, an effective distributed finite-time adaptive FTC strategy is developed. In previous studies, the unknown system powers were assumed to be positive odd integers that are greater than or equal to one and their boundaries were also assumed to be positive odd integers, but we relax these assumptions, where the powers are assumed to be unknown time-varying bounded real functions and their boundaries are real constants, and not necessarily positive odd integers. In addition, the proposed output dead-zone approximation model can achieve full approximation within a limited adjustable range, rather than the asymptotic approximation found in previous studies. Theoretical analysis proves that the tracking error of each subsystem converges to a small neighborhood of the origin in finite time. Finally, a simulated coupled inverted pendulum example is presented to demonstrate the validity of the proposed FTC strategy.
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具有未知时变功率漂移信号和非对称死区的分布式模糊自适应容错控制
在本研究中,我们考虑一类具有多个未知时变功率漂移信号、非对称执行器和输出死区的互连非线性系统的分布式模糊容错控制问题。基于我们提出的死区模型,提出了一种有效的分布式有限时间自适应FTC策略。在以往的研究中,将未知系统幂假设为大于等于1的正奇数,其边界也假设为正奇数,但我们放宽了这些假设,将未知系统幂假设为未知时变有界实函数,其边界为实常数,而不一定是正奇数。此外,本文提出的输出死区近似模型可以在有限的可调范围内实现完全逼近,而不是以往研究中发现的渐近逼近。理论分析证明了各子系统的跟踪误差在有限时间内收敛到原点的一个小邻域。最后,通过一个耦合倒立摆仿真实例验证了所提FTC策略的有效性。
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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