Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5004072 | ISA Transactions | 2017 | 9 Pages |
Abstract
This paper is concerned with the problem of extended dissipativity-based state estimation for uncertain discrete-time Markov jump neural networks with finite piecewise homogeneous Markov chain and mixed time delays. The aim of this paper is to present a Markov switching estimator design method, which ensures that the resulting error system is extended stochastically dissipative. A triple-summable term is introduced in the constructed Lyapunov function and the reciprocally convex approach is utilized to bound the forward difference of the triple-summable term. The extended dissipativity criterion is derived in form of linear matrix inequalities. Numerical simulations are conducted to demonstrate the effectiveness of the proposed method.
Keywords
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Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Qian Li, Qingxin Zhu, Shouming Zhong, Fuli Zhong,