Distributed Time-Varying Optimization-Based Protocols for Affine Formation Maneuver

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2025-01-20 DOI:10.1109/TIE.2025.3528506
Piaoyi Su;Zhexin Shi;Jianglong Yu;Xiwang Dong;Zhang Ren;Danwei Wang
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Abstract

In this work, an affine formation maneuver control problem is studied for second-order multiagent system. The agents’ task is to achieve affine formation maneuver through local interaction while minimizing the global time-varying cost functions. First, a distributed time-varying optimization problem with affine formation constraints is presented, where the solution trajectory is the affine transformation of the desired nominal configuration. Second, distributed time-varying optimization-based protocols are proposed. Using the proposed protocols, the agents’ states asymptotically converge to the optimal solution, and thus the desired affine formation and the collective maneuvers issues can be solved. Third, the asymptotic convergence is proved using Lyapunov arguments. Finally, the effectiveness of the protocols is demonstrated by numerical simulation and experimental examples.
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基于分布式时变优化协议的 Affine 编队操纵
研究了一类二阶多智能体系统的仿射编队机动控制问题。智能体的任务是通过局部交互实现仿射编队机动,同时最小化全局时变代价函数。首先,提出了一个具有仿射编队约束的分布式时变优化问题,其求解轨迹为期望标称构型的仿射变换。其次,提出了基于分布式时变优化的协议。利用所提出的协议,智能体的状态渐近收敛到最优解,从而可以求解期望的仿射编队和集体机动问题。第三,利用Lyapunov参数证明了该算法的渐近收敛性。最后,通过数值模拟和实验实例验证了协议的有效性。
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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