Logistic Adaptive Controller with Overhead Reduction for Multirobot Systems
IEEE Transactions on Industrial Electronics(2024)
摘要
This article studies a real-time collaborative control problem of multirobot systems from the kinematics level. The main goal of the research is to reduce the nonessential overhead while improving the operational performance of the multirobot system. To this end, a logistic adaptive controller with event-triggered mechanism is developed to utilize the system’s resources more efficiently. By using only inputs that have a significant effect on the robot’s fore-and-aft behavior, a balance is established between reducing resource overhead and maintaining desired output. Meanwhile, the concepts of payoff and strategy in game theory are introduced to spontaneously describe the collaborative behavior of a multirobot system. It is then formulated as a dynamic quadratic programming problem by optimization method. The convergence of the proposed controller, the optimality of the strategies, and the Zeno-freeness of the triggering mechanism are proved theoretically in this article. Simulation results show that the proposed controller significantly reduces the communication and computational overhead required for the multirobot system.
更多查看译文
关键词
Event-triggered mechanism,game theory,multirobot systems,neural dynamics,logistic adaptive controller
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要