Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4947152 | Neurocomputing | 2017 | 29 Pages |
Abstract
In this study, the state estimation and Hâ control problem for discrete-time switched neural networks with mode-dependent time-varying delays has been studied with persistent dwell time (PDT) switching regularities. The phenomenon of PDT, existing for the designed estimator of underlying switched neural networks are characterized by introducing a Bernoulli distributed white sequence. The main aim of the addressed problem is to design mode dependent state estimators such that the dynamics of the estimation error is exponentially stable with an expected decay rate and satisfies the prescribed Hâ performance constraint. Sufficient conditions are established for the occurence of the desired filter to ensure the mean-square exponential stability of the augmented system by using the generalized Finsler's lemma and then the full-order filter parameters are presented in terms of solutions to a set of linear matrix inequality (LMI) conditions. Finally, simulation results are given to explain the usefulness of the proposed design procedure.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
R. Rakkiyappan, K. Maheswari, K. Sivaranjani,