Distributed consensus control for networked linear agents via event‐triggered communications

This paper focuses on the average consensus problem for delayed nonlinear multi‐agent systems. To reduce unnecessary energy consumption, a novel event‐triggered impulsive control mechanism is adopted, in which the impulsive time series is determined by some pre‐designed events. Simultaneously, the Zeno‐behavior of the event‐triggering time series is excluded. By using Lyapunov–Krasovskii functional method as well as impulsive control theory, an easy‐to‐check sufficient criterion is derived to ensure the average consensus of the considered nonlinear multi‐agent systems. Finally, the applications and effectiveness of the obtained results is validated with a simulation example.

Section: Theorem 1 Suppose That the Graph G Is Strongly Connected And...mentioning

confidence: 99%

“…It was first proposed by

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Section: Introductionmentioning

confidence: 99%

Event‐based impulsive consensus for delayed multi‐agent systems

Wang

Cao

2021

“…How to ensure the stability of the system and reduce network load is a hot research topic in network communication. Many different types of triggering schemes have been put forward to overcome the limited bandwidth resources [16][17][18][19]. There are time-triggered and event-triggered scheme (ETS).…”

Section: Introductionmentioning

confidence: 99%

Dynamic event‐triggered dissipative control of nonlinear networked control systems with deception attacks

Zhan

et al. 2023

For nonlinear networked control systems with deception attacks, the problem of dynamic event‐triggered dissipative control is researched in this article. First, on the basis of nonlinear networked control systems model, a dynamic event triggered scheme is proposed to save impact of network bandwidth. Second, considering the impact of time delay, a networked time‐delay system model under deception attacks is established. Third, by constructing a new and less conservative Lyapunov function, using linear matrix inequality and unilateral Lipschitz condition, we derive some new sufficient conditions to guarantee the asymptotically stability of nonlinear networked control systems and strictly ‐dissipative performance. Besides, a cooperative design strategy of dynamic event triggered scheme parameters and controller gain is put forward. Finally, a simulation example is given to prove feasibility and rationality of the proposed strategy.

“…In contrast, distributed event-triggered control depends on the states of each agent and their neighbors, resulting in inconsistent execution of control policy and triggering instants. For example, [30,31] propose a distributed control protocol for linear MASs to investigate the event-triggered consensus problem. And these control protocols do not require continuous communication between neighboring agents, and the update time for control strategies of each agent are dependent on its own state and the states of its neighboring agents.…”

Section: Introductionmentioning

confidence: 99%

Distributed event‐triggered optimal bipartite consensus control for multiagent systems with input delay via reinforcement learning method

Zhang,

Ma,

Zhang

et al. 2023

In this article, an optimal bipartite consensus control (OBCC) scheme is proposed for heterogeneous multiagent systems (MASs) with input delay by reinforcement learning (RL) algorithm. A directed signed graph is established to construct MASs with competitive and cooperative relationships, and model reduction method is developed to tackle input delay problem. Then, based on the Hamilton–Jacobi–Bellman (HJB) equation, policy iteration method is utilized to design the bipartite consensus controller, which consists of value function and optimal controller. Further, a distributed event‐triggered function is proposed to increase control efficiency, which only requires information from its own agent and neighboring agents. Based on the input‐to‐state stability (ISS) function and Lyapunov function, sufficient conditions for the stability of MASs can be derived. Apart from that, RL algorithm is employed to solve the event‐triggered OBCC problem in MASs, where critic neural networks (NNs) and actor NNs estimate value function and control policy, respectively. Finally, simulation results are given to validate the feasibility and efficiency of the proposed algorithm.