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\(H_{\infty }\) State Estimation for Delayed Stochastic GRNs

  • Xian ZhangEmail author
  • Yantao Wang
  • Ligang Wu
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 207)

Abstract

This chapter addresses the problem of robust \(H_\infty \) filter for a class of uncertain stochastic GRNs with mixed delays. The uncertain stochastic GRNs under consideration are extended to involve Itô-type stochastic disturbance, norm-bounded uncertainties, time-varying discrete delays and distributed delays. By constructing an appropriate LKF and using reciprocal convex technique, LMIs-based sufficient conditions were presented to guarantee that the filtering error systems are robustly asymptotically mean square stable with pre-specified disturbance attenuation level. Furthermore, two numerical examples are given to illustrate the effectiveness of the proposed approach.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Mathematical ScienceHeilongjiang UniversityHarbinChina
  2. 2.School of AstronauticsHarbin Institute of TechnologyHarbinChina

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