Event-triggered distributed state estimation with randomly occurring uncertainties and nonlinearities over sensor networks: A delay-fractioning approach
This paper is concerned with the problem of event-triggered distributed state estimation for a class of discrete nonlinear stochastic systems with time-varying delays, randomly occurring uncertainties and randomly occurring nonlinearities. Both the uncertainties and nonlinearities enter into the sys...
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| Published in | Journal of the Franklin Institute Vol. 352; no. 9; pp. 3750 - 3763 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.09.2015
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| Online Access | Get full text |
| ISSN | 0016-0032 1879-2693 |
| DOI | 10.1016/j.jfranklin.2014.12.006 |
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| Abstract | This paper is concerned with the problem of event-triggered distributed state estimation for a class of discrete nonlinear stochastic systems with time-varying delays, randomly occurring uncertainties and randomly occurring nonlinearities. Both the uncertainties and nonlinearities enter into the system in a random way characterized by random variables obeying the Bernoulli distribution. An event-triggered scheme is introduced to reduce the number of excessive executions of the signal transmissions. The aim of this paper is to design a distributed state estimator such that the estimation error dynamics is asymptotically mean-square stable. By constructing a Lyapunov–Krasovskii functional and employing the delay-fractioning approach, sufficient conditions are established to guarantee the desired performance requirements and then the explicit form of the distributed estimator gains is parameterized. An illustrative example is finally provided to demonstrate the effectiveness of the developed distributed state estimation scheme with the event-triggered communication mechanism. |
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| AbstractList | This paper is concerned with the problem of event-triggered distributed state estimation for a class of discrete nonlinear stochastic systems with time-varying delays, randomly occurring uncertainties and randomly occurring nonlinearities. Both the uncertainties and nonlinearities enter into the system in a random way characterized by random variables obeying the Bernoulli distribution. An event-triggered scheme is introduced to reduce the number of excessive executions of the signal transmissions. The aim of this paper is to design a distributed state estimator such that the estimation error dynamics is asymptotically mean-square stable. By constructing a Lyapunov–Krasovskii functional and employing the delay-fractioning approach, sufficient conditions are established to guarantee the desired performance requirements and then the explicit form of the distributed estimator gains is parameterized. An illustrative example is finally provided to demonstrate the effectiveness of the developed distributed state estimation scheme with the event-triggered communication mechanism. |
| Author | Hu, Jun Liang, Jinling Dong, Hongli Wang, Zidong |
| Author_xml | – sequence: 1 givenname: Jun surname: Hu fullname: Hu, Jun organization: Department of Mathematics, Southeast University, Nanjing 210096, China – sequence: 2 givenname: Zidong surname: Wang fullname: Wang, Zidong organization: Department of Computer Science, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom – sequence: 3 givenname: Jinling surname: Liang fullname: Liang, Jinling email: jinlliang@gmail.com organization: Department of Mathematics, Southeast University, Nanjing 210096, China – sequence: 4 givenname: Hongli surname: Dong fullname: Dong, Hongli organization: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China |
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