Adaptive finite-time optimal time-varying formation control for second-order stochastic nonlinear multiagent systems

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-13 DOI:10.1002/acs.3788

Jiaxin Zhang, Yue Fu, Jun Fu

引用次数: 0

Abstract

This work addresses a fuzzy-based finite-time optimal time-varying formation (TVF) control issue for a class of second-order stochastic multi-agent systems (SMASs) with unknown nonlinearities. First, novel optimal cost functions with exponential power terms are constructed, which enables the SMASs to achieve finite-time stability in the mean square sense with minimum cost. Then, based on the cost functions, an optimal controller is proposed, in which fuzzy logic systems (FLSs) are used as universal approximators to identify the unknown uncertainties. Theorem analyses show that the proposed control strategy can guarantee the mean-square finite-time bounded of all signals in the system and then the TVF control task can be simultaneously realized with minimum cost. Finally, the effectiveness of the presented control method is verified by a multiple omni-directional robot system.

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二阶随机非线性多代理系统的自适应有限时间最优时变编队控制

本研究针对一类具有未知非线性的二阶随机多代理系统（SMAS），提出了基于模糊的有限时间最优时变形成（TVF）控制问题。首先，构建了具有指数幂项的新型最优成本函数，使 SMAS 能够以最小的成本实现均方意义上的有限时间稳定性。然后，基于成本函数，提出了一种最优控制器，其中模糊逻辑系统（FLS）被用作识别未知不确定性的通用近似值。定理分析表明，所提出的控制策略可以保证系统中所有信号的均方有限时间约束，从而以最小的成本同时实现 TVF 控制任务。最后，通过一个多全向机器人系统验证了所提出的控制方法的有效性。

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.