Memory-based consensus control for multi-agent systems with time-varying topology and communication constraints

Abstract

This paper focuses on the design of event-triggered observer-based heterogeneous memory controllers for leader-following multi-agent systems with time-varying topology. In order to save limited on-board resources, a novel adaptive event-triggered strategy based on the nonlinear transformation law of the estimation error is proposed in this paper, which can effectively reduce some unnecessary data transmission due to small fluctuations after the estimation error converges. Then, a more general topology structure described by an interval type-2 fuzzy model is adopted, which contains both nonlinear time-varying law and uncertain parameters. Taking into account the differences in the interactions between various agents, the heterogeneous fuzzy-dependent controllers with past state measurements are constructed to further improve consensus performance. Moreover, some sufficient conditions are derived to solve the designed observers and controllers while ensuring that the desired consensus of the multi-agent systems can be achieved. Finally, two examples are given to illustrate the superiority and effectiveness of the proposed event-triggered strategy, and also to verify that introducing past state measurements into the controller helps enhance the consensus control performance.