Consensus tracking for discrete distributed parameter multi-agent systems via iterative learning control
Cun Wang, Xisheng Dai, Qingnan Huang, Jingjing Wang, Su Wang · 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) · 2020
In this paper, the consensus tracking problem of discrete distributed parameter multi-agent systems are studied. The communication topology of the system remains unchanged, and only some agents can directly obtain the trajectory information of the virtual leader. An iterative learning control law including the consensus error between any two agents in the system is designed, and the convergence condition of the algorithm is obtained with the help of the contraction mapping principle. In the sense of L2norm, the consensus tracking error among all agents in the system can converge to zero along the iteration axis. Finally, simulation examples prove the applicability of the algorithm.