On designing a distributed event‐triggered output feedback consensus protocol for nonlinear multiagent systems

Abstract

In this article, the leader-follower consensus problem is considered for a class of nonlinear multiagent systems with event-triggered inputs. A novel time-varying gain compensator is designed for each follower by only utilizing the output information of the follower and its neighbors. Based on a time-varying threshold strategy and a directed communication topology, a distributed event-triggered output feedback controller is designed for each follower. It is proved by the Lyapunov theory that the leader-follower consensus of the multiagent systems is achieved and the Zeno-behavior is avoided. Compared with the existing results, it is the first time that a time-varying gain control algorithm is proposed for the multiagent systems subject to event-triggered inputs. The effectiveness of the proposed consensus protocol is validated by the chemical reactor systems.

Distributed consensus control of nonlinear multi‐agent systems with sensor uncertainty

“…Due to the fact that system (1) has unknown constants, this article cannot accurately obtain the information of the nonlinear functions. Similar to References 23 and 24, system (1) is unknown. Since the constant $$$ \vartheta $$$ in Assumption 1 is unknown, the time‐varying gain controller designed here does not need to know the specific information of the constant $$$ \vartheta $$$.…”

“…With the help of logarithmic function, the gain r 1 is designed to deal with the unknown growth rate. Based on (24), we have ̇r1…”

“…First, the time-varying gains can effectively deal with the unknown growth rate. In (24), the time-varying gains r i , i = 1, 2, tend to infinity. From (26), one has that the consensus errors converge to zero exponentially.…”

“…Since the constant $$$ \vartheta $$$ in Assumption 1 is unknown, the time‐varying gain controller designed here does not need to know the specific information of the constant $$$ \vartheta $$$. Many practical systems, such as the pendulum systems 16 and the chemical reactors, 24 can be modeled as system (1) with Assumption 1.…”

“…Remark The system dynamics studied in this article are more general than most existing models. Specifically, system (1) satisfying Assumption 1 contains the following special cases: (i) system (1) with $$$ N=1 $$$ is a single agent case investigated in Reference 15, in which the growth rate of nonlinear terms is required to be known; (ii) the leader‐follower consensus problem was solved in Reference 24 for nonlinear multi‐agent systems with $$$ \theta (t)=1 $$$ and conditions (4); (iii) multi‐agent systems satisfying conditions (4) were considered in Reference 25, where $$$ \vartheta $$$ was a known constant and $$$ \theta (t)=1 $$$.…”