Iterative learning consensus tracking control for a class of multi-agent systems with output saturation
LIANG Jia-qi
BU Xu-hui
LIU Jian
QIAN Wei
Abstract：In this paper, a distributed iterative learning control algorithm is proposed to the consensus tracking control problem of multi-agent systems with output saturation. First, it is assumed that the considered multi-agent system has a fixed communication topology and only a part of agents can obtain the desired trajectory information. The P-type iterative learning control law is developed from the consensus tracking error that constructed by the constraint output. Then, a sufficient condition of the algorithm is given by using the approach of contraction mapping, and the theoretical convergence analysis of the tracking error is also provided. Finally, the theoretical results are extended into multi-agent systems with randomly switching topology. Simulation results further validate the effectiveness of the proposed algorithm.
Keywords：multi-agent systems (MAS)iterative learning control (ILC)consensusoutput saturationdistributed algorithmsrandomly switching topologies
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 786-794 )