Event-triggered distributed ℋ∞ state estimation with packet dropouts through sensor networks
- Author(s): Derui Ding 1 ; Zidong Wang 2, 3 ; Bo Shen 4 ; Hongli Dong 5
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View affiliations
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Affiliations:
1:
Shanghai Key Laboratory of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China;
2: Department of Computer Science, Brunel University London, Uxbridge, Middlesex UB8 3PH, UK;
3: Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia;
4: School of Information Science and Technology, Donghua University, Shanghai 200051, People's Republic of China;
5: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, People's Republic of China
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Affiliations:
1:
Shanghai Key Laboratory of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China;
- Source:
Volume 9, Issue 13,
27 August 2015,
p.
1948 – 1955
DOI: 10.1049/iet-cta.2014.1055 , Print ISSN 1751-8644, Online ISSN 1751-8652
This study is concerned with the event-triggered distributed ℋ∞ state estimation problem for a class of discrete-time stochastic non-linear systems with packet dropouts in a sensor network. An event-triggered communication mechanism is adopted over the sensor network with hope to reduce the communication burden and the energy consumption, where the measurements on each sensor are transmitted only when a certain triggering condition is violated. Furthermore, a novel distributed state estimator is designed where the available innovations are not only from the individual sensor, but also from its neighbouring ones according to the given topology. The purpose of the problem under consideration is to design a set of distributed state estimators such that the dynamics of estimation errors is exponentially mean-square stable and also the prespecified ℋ∞ disturbance rejection attenuation level is guaranteed. By utilising the property of the Kronecker product and the stochastic analysis approaches, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimisation one that can be easily solved via available software packages. Finally, a simulation example is utilised to illustrate the usefulness of the proposed design scheme of event-triggered distributed state estimators.
Inspec keywords: stochastic systems; telecommunication network topology; state estimation; convex programming; error statistics; packet radio networks; H∞ control; nonlinear systems; discrete time systems; wireless sensor networks
Other keywords: exponentially mean square stable; event triggered distributed ℋ∞ state estimation; event triggered communication mechanism; H∞ disturbance rejection attenuation level; estimation errors; network topology; sensor network; stochastic analysis approach; discrete time stochastic nonlinear system; sufficient conditions; packet dropout; convex optimisation; Kronecker product; software packages
Subjects: Time-varying control systems; Discrete control systems; Optimisation techniques; Control applications in radio and radar; Optimal control; Nonlinear control systems; Other topics in statistics; Communication network design, planning and routing; Optimisation techniques; Other topics in statistics; Wireless sensor networks
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