Aihua Hu

Event-triggered consensus of multi-agent systems with noises

Abstract This paper investigates the issue of mean square consensus for multiple agents affected by noises over directed networks. The centralized and decentralized event-triggered protocols are adopted for driving the agents to converge to the average value of their initial states eventually. Each agent in the network is supposed to update the state according to the information from the neighbors, while the control actuation updates are decided by the proposed event-triggered scheme. The corresponding conditions for guaranteeing the consensus are derived based on the graph theory, the Lyapunov functional approach, and the stochastic theory. Additionally, the consensus for agents in networks with switching topologies is also analyzed. Some numerical examples are presented to demonstrate the effectiveness of the theoretical results.

Mean square exponential stability for discrete-time stochastic switched static neural networks with randomly occurring nonlinearities and stochastic delay

A class of discrete-time stochastic switched static neural networks model is presented with the introduction of randomly occurring nonlinearities and stochastic delay. The mean square exponential stability is investigated for such kind of neural networks. In terms of linear matrix inequality (LMI) approach, a delay-dependent stability criterion is derived for the considered neural networks via a Lyapunov-Krasovskii functional. An example with simulation results is given to illustrate the effectiveness of the theoretical result.

Leader-following consensus of linear multi-agent systems with randomly occurring nonlinearities and uncertainties and stochastic disturbances

For the multi-agent community, one of the key challenges is the agents operating in open environments, in which stochastic noises affect the dynamics of agents. This paper deals with the leader-following consensus problem for a class of linear multi-agent systems model with randomly occurring nonlinearities and uncertainties, and stochastic disturbances. The communication topology is assumed to be undirected and fixed. The stochastic Brownian motions are used to describe the source of extrinsic disturbances. The randomly occurring nonlinearities are introduced to describe the nonlinear intrinsic dynamics occurring in a probabilistic way. The randomly occurring uncertainties are adopted to reflect more realistic dynamical behaviors of the agent systems that are caused by noisy environment. Sufficient conditions are derived to make all follower agents asymptotically reach the state of leader in the mean square sense. Simulation results illustrate the theoretical results.

A Novel Finite-Time Stability Criterion for Linear Discrete-Time Stochastic System with Applications to Consensus of Multi-Agent System

This paper is concerned with the finite-time stability of linear discrete-time stochastic system with time-varying delays and its applications to the consensus problem of multi-agent system. A novel finite-time stability criterion is presented to guarantee that the state of the system does not exceed a prescribed bound during a fixed time interval using the piecewise-like delay method. Then, a corollary is derived for the case without stochastic perturbations. Numerical examples are provided to show the less conservatism and effectiveness of the proposed linear matrix inequality conditions. Finally, the stability results are directly applied to develop the finite-time consensus conditions for the linear multi-agent system with time-varying communication delays. An illustrative example is given to validate the effectiveness of the theoretical results.

Distributed control of cluster synchronisation in networks with randomly occurring non-linearities

This paper is concerned with the issue of mean square cluster synchronisation in complex networks, which consist of non-identical nodes with randomly occurring non-linearities. In order to guarantee synchronisation, distributed controllers depending on the information from the neighbours in the same cluster are applied to each node, meanwhile, the control gains are supposed to be updated according to the given laws. Based on the Lyapunov stability theory, the sufficient synchronisation conditions are derived and proved theoretically. Finally, a numerical example is presented to demonstrate the effectiveness of the results.

Event-triggered group consensus for multi-agent systems subject to input saturation

Abstract This paper investigates group consensus for leaderless multi-agent systems with non-identical dynamics. The consensus protocol is put forward in the form of the distributed event-triggered control subject to saturation, which depends on information from neighboring agents at event-triggered instants. In order to exclude the Zeno behavior and save resources, the given event-triggered condition is detected only at discrete sampling times, where the sampling intervals can be variable. Based on the graph theory, Lyapunov–Krasovskii functional method and by adopting the free-weighting matrix technique, some sufficient group consensus criteria in terms of linear matrix inequalities are derived. Furthermore, optimization problems aiming at maximizing the event-triggered parameter and the consensus region are proposed. Finally, numerical simulations illustrate the effectiveness of the theoretical results.