基于事件触发机制的多自主水面航行器编队避障控制OA
Formation obstacle avoidance control for multi-autonomous surface vehicle based on event triggered mechanism
多智能体系统的编队避障控制作为智能交通领域的重要研究方向,因其高度实用性,广泛应用于军事和民用环境.传统的周期性采样更新机制在处理非理想状态时效果有限,并且其高资源需求导致了系统资源的显著浪费.为解决这一问题,以自主水面航行器模型为背景,基于事件触发控制和领导跟随法,提出了一种多智能体系统编队一致性算法,并在该算法中引入了有向图结构.利用李雅普诺夫稳定性理论,对所提出算法的稳定性进行了严格的数学证明,证明了系统的稳定性并避免了芝诺行为.此外,在保证编队一致性的前提下,采用改进的人工势场法实现了避障和避碰功能.实验结果验证了改进后的人工势场法在避障效果上的显著优势.
The formation and obstacle avoidance control of multi-Agent systems,as an important research direction in the field of intelligent transportation,is widely applied in military and civilian environments due to its high practicality.The tra-ditional periodic sampling update mechanism has limited effectiveness in handling non-ideal conditions and its high resource demand leads to significant system resource waste.To address this issue,this paper,using an autonomous surface vehicle model as a background,proposes a multi-Agent system formation consistency algorithm based on event-triggered control and the leader-follower method,incorporating a directed graph structure into the algorithm.Utilizing Lyapunov stability theory,this paper provides a rigorous mathematical proof of the stability of the proposed algorithm,demonstrating system stability while avoiding Zeno behavior.Furthermore,under the premise of maintaining formation consistency,this paper implements obstacle avoidance and collision avoidance functions using an improved artificial potential field method.Experimental results verify the significant advantages of the improved artificial potential field method in obstacle avoidance performance.
朱志鹏;张钊;周红艳;陈雪波
辽宁科技大学,辽宁 鞍山 114051辽宁科技大学,辽宁 鞍山 114051辽宁科技大学,辽宁 鞍山 114051辽宁科技大学,辽宁 鞍山 114051
计算机与自动化
智能交通编队策略事件触发控制水面航行器人工势场法
intelligent transportationformation strategyevent-triggered controlsurface vehiclesartificial potential field
《指挥控制与仿真》 2025 (2)
10-18,9
国家自然科学基金项目(71771112)辽宁省高校基本科研业务费专项资金(LJ202410146025)
评论