Multi-agent flocking control with complex obstacles and adaptive distributed convex optimization

作     者：Pei, Huiqin Hu, Xinyu Luo, Zilong 

作者机构：East China Jiaotong Univ Sch Elect & Automat Engn Nanchang 330013 Peoples R China 

出 版 物：《JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS》 (J Franklin Inst)

年 卷 期：2024年第361卷第16期

核心收录：

学科分类：0808[工学-电气工程] 07[理学] 08[工学] 0701[理学-数学] 0811[工学-控制科学与工程] 

基　　金：Natural Science Foundation of P. R. China Key Research and Development Project of Jiangxi Provincial Technology Department [20202BBEL53018] Jiangxi Province 2022 Graduate Student Innovation Special Fund Project [YC2022-s485] 

主　　题：Multi-agent Distributed convex optimization Flocking control Obstacle avoidance 

摘      要：The optimization issue involving flocking control and obstacle avoidance behavior in continuous- time multi-agent systems is the main topic of this work. When an agent encounters an obstacle, a virtual agent is introduced to generate repulsive force, enabling the multi-agent system to navigate around obstacles smoothly. Under the local interaction between agents, a multi-agent flocking control and obstacle avoidance algorithm is proposed with utilizing adaptive distributed convex optimization. This algorithm can minimize the sum of local costs of the system. A symbolic function-based estimation method is introduced to effectively relax the constraints of the cost function. The Lyapunov approach is employed to show the stability of the multi-agent system. With the proposed algorithm, each agent can achieve flocking behavior for convex optimization in complex obstacle environments by interacting with their neighbors, virtual agents, and virtual leaders. Last but not least, simulation examples are given to further illustrate the effectiveness and efficiency of the suggested control algorithm.