State estimation for complex networks with randomly varying nonlinearities and sensor failures |
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| Authors: | Renquan Lu Sheng‐Ge Chen Yong Xu Hui Peng Kan Xie |
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| Affiliation: | 1. Key Lab for IOT and Information Fusion Technology of Zhejiang, the Institute of Information and Control, Hangzhou Dianzi University, Zhejiang, Hangzhou, China;2. Key Laboratory of IOT Information Processing, School of Automation, Guangdong University of Technology, and Guangdong, Guangzhou, China |
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| Abstract: | The current study is focused on the  state estimator design for the discrete‐time complex networks with sensor failures and randomly varying nonlinearities. Bernoulli process is adopted to describe the randomly varying nonlinearities, and the norm‐bounded uncertain model is used to deal with the sensor failures. Then, a set of sufficient conditions are provided to guarantee that the estimation error system is stochastically stable with the prescribed  property. Then, using the linear matrix inequality method, the estimator gains are obtained. Finally, the effectiveness of the proposed new design method is illustrated through a numerical example. © 2016 Wiley Periodicals, Inc. Complexity 21: 507–517, 2016 |
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| Keywords: |
state estimation complex networks sensor failures randomly varying nonlinearities |
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