This paper deals with the leader‐following consensus for nonlinear stochastic multi‐agent systems. To save communication resources, a new centralized/distributed hybrid event‐triggered mechanism (HETM) is proposed for nonlinear multi‐agent systems. HETMs can be regarded as a synthesis of continuous event‐triggered mechanism and time‐driven mechanism, which can effectively avoid Zeno behavior. To model the multi‐agent systems under centralized HETM, the switched system method is applied. By utilizing the property of communication topology, low‐dimensional consensus conditions are obtained. For the distributed hybrid event‐triggered mechanism, due to the asynchronous event‐triggered instants, the time‐varying system method is applied. Meanwhile, the effect of network‐induced time‐delay on the consensus is also considered. To further reduce the computational resources by constantly testing whether the broadcast condition has been violated, self‐triggered implementations of the proposed event‐triggered communication protocols are also derived. A numerical example is given to show the effectiveness of the proposed method.

This paper deals with the cooperative tracking problem of nonlinear multiagent systems. Compared with the existing works, both the uncertainties in model and switching topology are considered. Two control laws, the adaptive distributed controller based on state information and the adaptive distributed controller based on output information, are proposed using the neural networks.The advantage of the proposed controller is that we no longer require the exact knowledge of follower agents' parameters and the precise switching signal of communication topology by taking advantages of neural networks approximation and the property of transition probabilities. It is proved that all followers can track the leader with permitted bounded errors under the proposed controller.An illustration is given to testify the efficacy of the proposed approach. KEYWORDS adaptive cooperative control, Markov switching, nonlinear multiagent systems, uncertain parameter Abbreviations: TPs, transition probabilities 1506

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Summary In this paper, we investigate the mean square exponential synchronization of stochastic nonlinear complex dynamical networks with or without communication delays. A new self‐triggered mechanism is proposed to reduce the amount of communication while preserving the desired system's performance. Under this mechanism, the next sampling instant is dynamically determined by the latest transmitted state rather than the online detection of the event‐triggered condition. Meanwhile, we show that the inter‐execution time of self‐triggered mechanism is bounded by a strictly positive constant, and the maximal allowable delay of the underlying system is given. A simulation is provided to illustrate the effectiveness of the proposed self‐triggered scenario. Copyright © 2016 John Wiley & Sons, Ltd.

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