IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Jun Zhang , Yi Zuo , Shaocheng Tong
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引用次数: 0

摘要

本文研究了具有无限执行器故障的多输入多输出(MIMO)非线性多代理系统(MAS)的自适应模糊渐近形成容错控制(FTC)问题。受控工厂包含未知非线性动力学和无限致动器故障。未知非线性动力学通过模糊逼近技术进行处理。通过引入可积分函数和利用有界估计算法,获得虚拟控制器和参数自适应规律。为了克服无限致动器故障所带来的困难,提出了一种基于两步设计技术的新型致动器故障补偿方法。通过在反步递归设计中引入规定性能函数 (PPF),开发了一种自适应模糊渐近形成 FTC 方案。基于 Lyapunov 稳定性理论,证明了闭环信号都是有界的,编队误差渐近收敛为零,并且可以保证编队误差的收敛速率和最大超调。最后,将所开发的编队 FTC 应用于一组海上水面飞行器,验证了其有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prescribed-performance-based adaptive fuzzy asymptotic formation control for MIMO nonlinear multi-agent systems with infinite actuator faults
In this article, the adaptive fuzzy asymptotic formation fault-tolerant control (FTC) problem is investigated for multi-input and multi-output (MIMO) nonlinear multi-agent systems (MASs) with infinite actuator faults. The controlled plant contains unknown nonlinear dynamics and infinite actuator faults. The unknown nonlinear dynamics are handled by using fuzzy approximation technique. The virtual controllers together with the parameter adaptive laws are obtained by introducing an integrable function and utilizing bounded estimation algorithms. To overcome the difficulty caused by the infinite actuator faults, a novel actuator fault compensation method is presented based on a two-step design technique. By introducing a prescribed performance function (PPF) to the backstepping recursive design, an adaptive fuzzy asymptotic formation FTC scheme is developed. Based on the Lyapunov stability theory, it is proved that the closed-loop signals are all bounded, the formation error converges asymptotically to zero, and the convergence rate and maximum overshoot of the formation error can be guaranteed. Finally, the developed formation FTC is applied to a group of marine surface vehicles, and its effectiveness and practicability are verified.
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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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