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DC Field | Value | Language |
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dc.contributor.author | Ding, D | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Shen, B | - |
dc.contributor.author | Wei, G | - |
dc.date.accessioned | 2016-01-05T13:20:47Z | - |
dc.date.available | 2015-12 | - |
dc.date.available | 2016-01-05T13:20:47Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Automatica, 62 pp. 284 - 291, (2015) | en_US |
dc.identifier.issn | 0005-1098 | - |
dc.identifier.uri | http://www.sciencedirect.com/science/article/pii/S0005109815004008 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/11796 | - |
dc.description.abstract | 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 multiagent 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 discretetime 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. | en_US |
dc.description.sponsorship | Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61203139 and 61473076, the Hujiang Foundation of China under Grants C14002 and D15009, the Shanghai Rising- Star Program of China under Grant 13QA1400100, the ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Fundamental Research Funds for the Central Universities, DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of Germany | en_US |
dc.format.extent | 284 - 291 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Multi-agent systems | en_US |
dc.subject | Consensus in probability | en_US |
dc.subject | Event-triggered control | en_US |
dc.subject | Input-to-state stability in probability | en_US |
dc.subject | Discrete-time stochastic nonlinear systems | en_US |
dc.title | Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.automatica.2015.09.037 | - |
dc.relation.isPartOf | Automatica | - |
pubs.notes | publisher: Elsevier articletitle: Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability journaltitle: Automatica articlelink: http://dx.doi.org/10.1016/j.automatica.2015.09.037 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved. | - |
pubs.notes | publisher: Elsevier articletitle: Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability journaltitle: Automatica articlelink: http://dx.doi.org/10.1016/j.automatica.2015.09.037 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved. | - |
pubs.publication-status | Published | - |
pubs.publication-status | Published | - |
pubs.volume | 62 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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