Abstract
This paper proposes an observer-based event-triggered algorithm to solve circle formation control problems for both first- and second-order multiagent systems, where the communication topology is modeled by a spanning tree-based directed graph with limited resources. In particular, the observation-based event-triggering mechanism is used to reduce the update frequency of the controller, and the triggering time depends on the norm of the state function and the trigger threshold of measurement errors. The analysis shows that sufficient conditions are established for achieving the desired circle formation, while there exists at least one agent for which the next interevent interval is strictly positive. Numerical simulations of both first- and second-order multiagent systems are also given to demonstrate the effectiveness of the proposed control laws.
Highlights
Many research efforts have been devoted to controlling of multiagent systems (MASs) due to both its practical potentials in a variety of applications [1,2,3] and theoretical challenges of physical constraints [4,5,6]
For MASs subjected to aperiodic sampling and communication delays, the problem of cluster formation control was addressed in [10]
Erefore, most existing results on formation control mainly rely on the ideal hypothesis [13,14,15], e.g., each agent is modeled as having unlimited communication capabilities, unlimited power, and unlimited processing capabilities, which allows arbitrary information to exchange pattern
Summary
Many research efforts have been devoted to controlling of multiagent systems (MASs) due to both its practical potentials in a variety of applications [1,2,3] and theoretical challenges of physical constraints [4,5,6]. In comparison to the literature, we have three main contributions: (i) different from [22] concerning the first-order model, combining with a distributed asynchronous event-triggered control algorithm, a more concise form of the event-triggered condition is designed to solve circle formation problems for both first- and second-order dynamics MASs; (ii) different from taking a complex-coordinate system transformation method in [29], the proposed strategy allows for a reduction of the number of control actions without significantly degrading performance using the simple-coordinate system transformation; and (iii) the resulting asynchronous model achieves the desired equilibrium points asymptotically while at least one agent with a positive event interval exists, i.e., no trajectory generates in a finite time interval.
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