摘要
This study investigates the consensus problem of a nonlinear discrete-time multi-agent system(MAS)under bounded additive disturbances.We propose a self-triggered robust distributed model predictive control consensus algorithm.A new cost function is constructed and MAS is coupled through this function.Based on the proposed cost function,a self-triggered mechanism is adopted to reduce the communication load.Furthermore,to overcome additive disturbances,a local minimum-maximum optimization problem under the worst-case scenario is solved iteratively by the model predictive controller of each agent.Sufficient conditions are provided to guarantee the iterative feasibility of the algorithm and the consensus of the closed-loop MAS.For each agent,we provide a concrete form of compatibility constraint and a consensus error terminal region.Numerical examples are provided to illustrate the effectiveness and correctness of the proposed algorithm.
基金
Project supported by the National Natural Science Foundation of China(Nos.61973074,U1713209,61520106009,61533008,and 61921004)
the National Key R&D Program of China(No.2018AAA0101400)
the Science and Technology on Information System Engineering Laboratory,China(No.05201902)。
作者简介
Jiaqi LI,E-mail:jiaqil2018@seu.edu.cn,ORCID:https://orcid.org/0000-0003-0614-4358;Qingling WANG,E-mail:qlwang@seu.edu.cn;Yanxu SU,E-mail:yanxu.su@seu.edu.cn;Corresponding author:Changyin SUN,E-mail:cysun@seu.edu.cn,ORCID:https://orcid.org/0000-0001-9269-334X。
