Time-Varying Formation of Heterogeneous Multiagent Systems via Reinforcement Learning Subject to Switching Topologies

• Published in: IEEE transactions on circuits and systems. I, Regular papers Vol. 70; no. 6; pp. 2550 - 2560
• Main Authors: Liu, Deyuan, Liu, Hao, Lu, Jinhu, Lewis, Frank L.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: air-ground coordination; Dynamic models; Heterogeneous vehicles; Multiagent systems; Optimal control; Quadrotors; Reinforcement learning; Rotary wing aircraft; Switches; Switching; time-varying formation control; Time-varying systems; Topology; Tracking control; Vehicle dynamics
• ISSN: 1549-8328; 1558-0806
• DOI: 10.1109/TCSI.2023.3250516

This paper investigates the optimal formation control of a heterogeneous multiagent system consisting of multiple quadrotors and ground vehicles via reinforcement learning to achieve the time-varying formation under switching topologies. A distributed observer is firstly constructed to generate references using local information for each vehicle to form time-varying formation and the convergence of the observer under switching topologies is proven. Then, reinforcement learning methods are provided for the heterogeneous vehicle group to realize the optimal tracking control without information of vehicle dynamical model. Simulation tests are given to confirm the effectiveness of the proposed method.