Active Disturbance Rejection Formation Tracking Control for Uncertain Nonlinear Multi-Agent Systems With Switching Topology via Dynamic Event-Triggered Extended State Observer

In this paper, the time-varying formation tracking (TVFT) control problem is concerned for multi-agent systems (MASs). The primary objective is to achieve asymptotical convergence for formation tracking error subject to nonparametric and nonvanishing uncertainties. Firstly, in order to estimate lumped unmodeled dynamics and external disturbances, an event-triggered fuzzy extended state observer (FESO) inspired by our previous works is established for follower group, in which efficient nonlinear observation pattern and convenient linear numerical tractability are integrated. For rationally scheduling transmission, a dynamic event-triggered mechanism is applied to form adaptively regulating strategy. Secondly, a distributed TVFT control law is developed by utilizing neighborhood formation tracking errors. Different from conventional disturbance-tolerant methodologies, total disturbance compensation is introduced to attenuate uncertainty influence in real time. Consequently, active disturbance rejection formation tracking control architecture is systematically constructed for uncertain MASs. Moreover, considering switching topology, the controller design algorithm is presented by piecewise Lyapunov analysis. Finally, the effectiveness and advantages of the proposed event-triggered FESO-based active disturbance rejection control protocol is illustrated by an numerical example on unmanned aerial vehicle swarm system.

Automated summary

This paper investigates the time-varying formation tracking control problem for multi-agent systems (MASs). The main objective is to achieve asymptotic convergence of formation tracking error despite nonparametric and nonvanishing uncertainties. A fuzzy extended state observer (FESO) based on event-triggered mechanism is proposed to estimate unmodeled dynamics and external disturbances. Furthermore, a distributed control law is developed using neighborhood formation tracking errors, and total disturbance compensation is introduced to attenuate uncertainty influence in real time. The effectiveness of the proposed control protocol is demonstrated using a numerical example on unmanned aerial vehicle swarm system.