State estimation for complex networks with randomly varying nonlinearities and sensor failures. (23rd September 2016) - Lu, Renquan; Chen, Sheng‐Ge; Xu, Yong; Peng, Hui; Xie, Kan
Abstract : The current study is focused on the l 2 − l ∞ 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 l 2 − l ∞ 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