Event-triggered predictive control for linear discrete-time multi-agent systems

• Published in: Neurocomputing (Amsterdam) Vol. 505; pp. 238 - 248
• Main Authors: Zhang, Tian-Yong, Xu, Yong, Sun, Jian
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 21.09.2022
• Subjects: Closed-loop state estimation; Event-triggered predictive control; Multi-agent system; Synchronization; Multi-agent system; Synchronization; Event-triggered predictive control; Closed-loop state estimation
• ISSN: 0925-2312; 1872-8286
• DOI: 10.1016/j.neucom.2022.07.052

This paper considers the event-triggered predictive control(ETPC) problem for linear discrete-time multi-agent systems. To achieve accurate state estimation under event-triggered communication between agents, an event-triggered predictive control scheme as well as a novel class of triggering condition are proposed for synchronization of multi-agent systems with single-integrator dynamics, where the control input of each agent no longer remains constant but updates periodically within the time interval between two consecutive triggering instants. Then, the proposed scheme is extended to the general linear multi-agent systems. By comparing with the time-triggered control(TTC) method and the existing event-triggered control(ETC) methods, the control performance of the proposed ETPC scheme is almost the same as that of the TTC approach, and the communication payload between agents is reduced with much less triggering times than existing ETC methods. Finally, two numerical examples are given to verify the theoretical analysis and demonstrate the superiority of the proposed method comparing with some existing methods.