Event‐triggered mean square consensus of linear multiagent systems with measurement noises

Abstract

Summary This article investigates mean square consensus of linear multiagent systems with measurement noises based on event‐triggered control. Considering various uncertain factors in the communication environment, multiplicative noises exists in the information that each agent measures from its neighbors. In order to save limited resources and to exclude the Zeno phenomenon, the update of the controller for each agent is driven by properly defined event‐triggered condition. Sufficient conditions are given to ensure exponential mean square consensus of multiagent systems with multiplicative noises by utilizing static and dynamic event‐triggered scheme. The interevent times of static event‐triggered mechanism is less than those of corresponding dynamic case for each agent. Finally, validity of the theoretical results is illustrated through a simulation example.

Adaptive guaranteed‐performance consensus for high‐order nonlinear multi‐agent systems with switching topologies

“…In the past decade, the applications of multi-agent systems (MASs) in various fields have attracted more and more researchers' extensive attention, such as tracking, cluster, formation, [1][2][3][4][5] and so on. Among the results mentioned above, the consensus problem denotes the process in which the dynamics of each agent eventually converges to a common value by exchanging local information.…”

Distributed event‐triggered tracking consensus control for privacy preservation in multi‐agent systems with denial‐of‐service attacks

“…On the other hand, as the importance of reducing the wastage of communication resources increases, event‐triggered (ET) control strategies play an increasingly important role in the development of MASs control compared with time‐triggered control strategies 33‐35 . The original thought of ET scheme 36 was provided by a feedback parameter based on the state of the plant.…”

“…On the other hand, as the importance of reducing the wastage of communication resources increases, event-triggered (ET) control strategies play an increasingly important role in the development of MASs control compared with time-triggered control strategies. [33][34][35] The original thought of ET scheme 36 was provided by a feedback parameter based on the state of the plant. Subsequently, the result was extended into MASs in Reference 37, where the controller updating scheme depended on the ratio of the norm of state function to measurement error.…”