一种基于动态事件触发的分布式优化算法

A distributed optimization algorithm based on dynamic event triggered control

针对多智能体系统优化问题,提出一种基于动态事件触发机制的分布式优化算法.基于李雅普诺夫函数方法设计一种新型的动态事件触发控制器,相较于传统静态事件触发控制方法,所提出算法可有效降低多智能体间通信负担以及控制器计算负担.此外,利用周期采样信息进行事件触发条件设计,可避免智能体连续检测事件触发条件,并可消除Zeno现象.通过数值仿真验证了算法的有效性.

The dynamic event triggered mechanism is used to design a distributed optimization algorithm for multi-agent systems.Compared with traditional static triggered control,the dynamic event triggered controller based on Lyapunov function can effectively reduce the communication burden between agents as well as the calculation burden of controllers.In addition,the event triggering condition is designed using periodic sampling information,thus is not required to be checked repeatedly by agents.Moreover,Zeno behavior can be avoided.A numerical simulation is given to verify the effectiveness of the algorithm.