作者：
Hu, YanjieZhan, JingyuanLi, XiangFudan Univ
Dept Elect Engn Adapt Networks & Control Lab Shanghai 200433 Peoples R China Fudan Univ
Sch Informat Sci & Engn Res Ctr Smart Networks & Syst Shanghai 200433 Peoples R China Beijing Univ Technol
Coll Metropolitan Transportat Beijing Key Lab Transportat Engn Beijing 100124 Peoples R China
This study presents a self-triggered distributed model predictive control algorithm for the flock of a multi-agent system. All the agents in a flock are endowed with the capability of determining the sampling time ada...
详细信息
This study presents a self-triggered distributed model predictive control algorithm for the flock of a multi-agent system. All the agents in a flock are endowed with the capability of determining the sampling time adaptively to reduce the unnecessary energy consumption in communication and control updates. The agents are dynamically decoupled in a flock, and each agent is driven by a local modelpredictivecontroller, which is designed by minimising the position irregularity between the agent and its neighbours, velocity tracking errors as well as its control efforts. Moreover, the collision avoidance is considered by introducing constraints in the modelpredictive minimisation problem. In order to adaptively determine the sampling time, a self-triggeredalgorithm is designed by guaranteeing the decrease of the Lyapunov function. Finally, numerical simulations are given to demonstrate the feasibility of the proposed flocking algorithm.
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