Distributed Model Reference Adaptive Optimization of Disturbed Multiagent Systems With Intermittent Communications

• Published in: IEEE transactions on cybernetics Vol. 52; no. 6; pp. 5464 - 5473
• Main Authors: Guo, Ge, Kang, Jian, Li, Ranran, Yang, Guanghong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive control; Cost function; Distributed optimization; disturbance; Disturbance observers; Germanium; Heuristic algorithms; intermittent communication; Mathematical models; Model reference adaptive control; model reference adaptive control (MRAC); Multi-agent systems; Multiagent systems; Numerical models; Optimization; Robustness (mathematics); Topology; Transient performance
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2020.3032429

This article pays close attention to a distributed optimization problem for multiagent systems subject to exogenous disturbances. A novel distributed model reference adaptive control (D-MRAC) scheme is proposed that no explicit disturbance observer or internal model unit is involved, which not only enhances robustness but also improves transient performance. In contrast to the continuous communication that is often assumed in the existing distributed optimization works, the new method allows for more realistic scenarios in which the agents communicate with each other at discrete-time instants. It is shown by Lyapunov analysis that the concerned distributed optimization problem can be solved by the proposed D-MRAC scheme as long as the communication interval is smaller than a given threshold, which can be calculated by following the steps given in this article. Numerical simulations have shown the effectiveness of the presented method.