柔性机器人多智能体系统的动态事件触发自适应模糊命令滤波渐近包容控制

IF 4.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Yulong Li , Jihang Sui , Huilin Yang , Ben Niu , Chenguang Ning , Limin Han
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引用次数: 0

摘要

基于一种新的动态事件触发机制,提出了柔性机器人多智能体系统的自适应模糊渐近控制方案。首先,提出了一种基于命令滤波技术和反演法的两步坐标变换方法,有效地解决了“复杂度爆炸”问题;其次,需要强调的是,由于实际柔性机械臂质量中存在未知的非线性,因此控制器的设计尤其具有挑战性。因此,引入模糊逻辑系统(FLSs)来处理未知非线性。基于一个辅助动态变量,设计DETM以节省通信资源,避免芝诺现象。所提出的控制方案不仅保证了闭环系统中所有变量都是一致最终有界的,而且保证了follower的输出能够在由多个leader形成的动态凸包内进化,且包容误差最终趋于零。最后,仿真结果表明了所提控制方案的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic event-triggered adaptive fuzzy command filtered asymptotic containment control for flexible robotic manipulator multiagent systems
This paper presents the adaptive fuzzy asymptotic containment control scheme for flexible robotic manipulator multiagent systems (MASs) based on a novel dynamic event-triggered mechanism (DETM). Firstly, a two-step coordinate transformation method is presented based on the command filtered technique and the backstepping method, which effectively works out the issue of “explosion of complexity”. Secondly, it should be worth stressing that the controller design is particularly challenging because of the unknown nonlinearities that appear in the actual flexible robotic manipulator MASs. Therefore, the fuzzy logic systems (FLSs) are introduced to deal with the unknown nonlinearities. Based on an auxiliary dynamic variable, a DETM is designed to save communication resources without the Zeno phenomenon. The proposed control scheme not only ensures that all variables in the closed-loop system are uniformly ultimately bounded (UUB), but also the outputs of the followers can evolve within the dynamic convex hull formed by the multiple leaders, and the containment errors can eventually tend to zero. Finally, the simulation results indicate the feasibility of the proposed control scheme.
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来源期刊
CiteScore
7.30
自引率
14.60%
发文量
586
审稿时长
6.9 months
期刊介绍: The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.
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