Distributed dynamic event-triggered asymptotic tracking control of time-varying nonlinear multi-agent systems

Abstract

This paper investigates the event-based consensus tracking control of nonlinear multi-agent systems (MASs) with disturbances and unknown time-varying parameters (TVPs). Firstly, to circumvent the challenge brought by unknown TVPs, the bound estimation method is adopted, focusing solely on estimating the bounds of these parameters without any effort to address their derivatives. Secondly, by constructing some smooth functions as compensation terms and incorporating a set of positive integrable functions into the process of virtual controller design, the effect of unknown TVPs is fully compensated and a backstepping based distributed asymptotic consensus tracking control algorithm is developed. Additionally, to achieve more efficient transmission and further save resources, a dynamic event-triggered control (ETC) strategy is presented, where a dynamic variable is embedded in the trigger condition to adjust the threshold flexibly. In particular, reasonable proofs are given to confirm that our presented control method can not only guarantee the boundedness of all closed-loop signals but also realize the asymptotic output tracking and avoids Zeno behavior, irrespective of the parameters variation speed and any information about the desired trajectory’s high order derivatives. Ultimately, simulation results attest the validity of our strategy.