Event-Triggered Attitude Consensus of Multiple Rigid Body Systems With Prescribed Performance

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-11-08 DOI:10.1109/TCYB.2024.3485889
Xin Jin;Yang Tang;Yang Shi;Xiaotai Wu;Wei Lin
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Abstract

The event-triggered almost global attitude consensus problem is considered in this article for multiple rigid body systems with prescribed performance. Two kinds of attitude consensus protocols using axis-angle vectors are proposed at the kinematic level with different prescribed performance constraints. The first protocol aims to achieve the event-triggered attitude consensus almost globally under jointly connected graphs. Based on a prescribed performance function with local states, the configuration space of parameterized attitude representations is shown to be positively invariant which almost globally covers $\mathbb {SO}(3)$ . The second protocol is designed to reach attitude consensus with the prescribed transient behavior guaranteed in the event-triggered setting. By defining a prescribed performance function using the metric on axis-angle spaces, a dynamic event-triggered framework is designed to ensure both the attitude geometric topology constraint and prescribed convergence performance. Finally, numerical results are given to show the validness of the two control protocols.
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具有规定性能的多刚体系统的事件触发姿态一致性
本文研究了具有规定性能的多刚体系统的事件触发的几乎全局姿态一致问题。在不同的性能约束条件下,提出了两种基于轴角矢量的姿态一致协议。第一个协议的目标是在联合连通图下实现几乎全局的事件触发姿态一致。基于具有局部状态的规定性能函数,证明了参数化姿态表示的构形空间是正不变的,几乎全局覆盖$\mathbb {SO}(3)$。第二种协议的目的是在事件触发设置下,在保证规定的瞬态行为的情况下达成姿态共识。通过在轴角空间上定义一个规定的性能函数,设计了一个动态事件触发框架,以保证姿态几何拓扑约束和规定的收敛性能。最后给出了数值结果,验证了两种控制协议的有效性。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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