4.7 Article

Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability

Journal

AUTOMATICA
Volume 62, Issue -, Pages 284-291

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2015.09.037

Keywords

Multi-agent systems; Consensus in probability; Event-triggered control; Input-to-state stability in probability; Discrete-time stochastic nonlinear systems

Funding

  1. Royal Society of the UK
  2. National Natural Science Foundation of China [61329301, 61203139, 61473076]
  3. Hujiang Foundation of China [C14002, D15009]
  4. Shanghai Rising-Star Program of China [13QA1400100]
  5. ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation [13SG34]
  6. Fundamental Research Funds for the Central Universities
  7. DHU Distinguished Young Professor Program
  8. Alexander von Humboldt Foundation of Germany

Ask authors/readers for more resources

This paper is concerned with the event-triggered consensus control problem for a class of discrete-time stochastic multi-agent systems with state-dependent noises. A novel definition of consensus in probability is proposed to better describe the dynamics of the consensus process of the addressed stochastic multi-agent systems. The measurement output available for the controller is not only from the individual agent but also from its neighboring ones according to the given topology. An event-triggered mechanism is adopted with hope to reduce the communication burden, where the control input on each agent is updated only when a certain triggering condition is violated. The purpose of the problem under consideration is to design both the output feedback controller and the threshold of the triggering condition such that the closed-loop system achieves the desired consensus in probability. First of all, a theoretical framework is established for analyzing the so-called input-to-state stability in probability (ISSiP) for general discrete-time nonlinear stochastic systems. Within such a theoretical framework, some sufficient conditions on event-triggered control protocol are derived under which the consensus in probability is reached. Furthermore, both the controller parameter and the triggering threshold are obtained in terms of the solution to certain matrix inequalities involving the topology information and the desired consensus probability. Finally, a simulation example is utilized to illustrate the usefulness of the proposed control protocol. (C) 2015 Elsevier Ltd. All rights reserved.

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