Distributed Optimal Coordination for Heterogeneous Linear Multiagent Systems With Event-Triggered Mechanisms

• Published in: IEEE transactions on automatic control Vol. 65; no. 4; pp. 1763 - 1770
• Main Authors: Li, Zhenhong, Wu, Zizhen, Li, Zhongkui, Ding, Zhengtao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic properties; Control theory; Convergence; Convexity; Coordination; Distributed convex optimization; event-triggered; Heuristic algorithms; Laplace equations; Linear programming; Linear systems; Multi-agent systems; Multiagent systems; Symmetric matrices; Upper bound
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2019.2937500

This note considers the distributed optimal coordination (DOC) problem for heterogeneous linear multiagent systems. The local gradients are locally Lipschitz and the local convexity constants are unknown. A control law is proposed to drive the states of all agents to the optimal coordination that minimizes a global objective function. By exploring certain features of the invariant projection of the Laplacian matrix, the global asymptotic convergence is guaranteed utilizing only local interaction. The proposed control law is then extended with event-triggered communication schemes, which removes the requirement for continuous communications. Under the event-triggered control law, it is proved that no Zeno behavior is exhibited and the global asymptotic convergence is preserved. The proposed control laws are fully distributed, in the sense that the control design only uses the information in the connected neighborhood. Furthermore, to achieve the DOC for linear multiagent systems with unmeasurable states, an observer-based event-triggered control law is proposed. A simulation example is given to validate the proposed control laws.