Suboptimal Event-Triggered Consensus of Multiagent Systems

In this paper the suboptimal event-triggered consensus problem of Multiagent systems is investigated. Using the combinational measurement approach, each agent only updates its control input at its own event time instants. Thus the total number of events and the amount of controller updates can be significantly reduced in practice. Then, based on the observation of increasing the consensus rate and reducing the number of triggering events, we have proposed the time-average cost of the agent system and developed a suboptimal approach to determine the triggering condition. The effectiveness of the proposed strategy is illustrated by numerical examples

Dynamic event-triggered-based human-in-the-loop formation control for stochastic nonlinear MASs

The dynamic event-triggered (DET) formation control problem of a class of stochastic nonlinear multi-agent systems (MASs) with full state constraints is investigated in this article. Supposing that the human operator sends commands to the leader as control input signals, all followers keep formation through network topology communication. Under the command-filter-based backstepping technique, the radial basis function neural networks (RBF NNs) and the barrier Lyapunov function (BLF) are utilized to resolve the problems of unknown nonlinear terms and full state constraints, respectively. Furthermore, a DET control mechanism is proposed to reduce the occupation of communication bandwidth. The presented distributed formation control strategy guarantees that all signals of the MASs are semi-globally uniformly ultimately bounded (SGUUB) in probability. Finally, the feasibility of the theoretical research result is demonstrated by a simulation example

Event-based synchronisation of linear discrete-time dynamical networks

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Dynamic quantized consensus under DoS attacks: Towards a tight zooming-out factor

This paper deals with dynamic quantized consensus of dynamical agents in a general form under packet losses induced by Denial-of-Service (DoS) attacks. The communication channel has limited bandwidth and hence the transmitted signals over the network are subject to quantization. To deal with agent's output, an observer is implemented at each node. The state of the observer is quantized by a finite-level quantizer and then transmitted over the network. To solve the problem of quantizer overflow under malicious packet losses, a zooming-in and out dynamic quantization mechanism is designed. By the new quantized controller proposed in the paper, the zooming-out factor is lower bounded by the spectral radius of the agent's dynamic matrix. A sufficient condition of quantization range is provided under which the finite-level quantizer is free of overflow. A sufficient condition of tolerable DoS attacks for achieving consensus is also provided. At last, we study scalar dynamical agents as a special case and further tighten the zooming-out factor to a value smaller than the agent's dynamic parameter. Under such a zooming-out factor, it is possible to recover the level of tolerable DoS attacks to that of unquantized consensus, and the quantizer is free of overflow