Robust filtering of extended stochastic genetic regulatory networks with parameter uncertainties, disturbances, and time-varying delays

Authors:
Seyed Mohsen Mousavi;Vahid Johari Majd
Affiliations:
Intelligent Control Systems Laboratory, School of Electrical and Computer Engineering, Tarbiat Modares University, P.O. Box 14115-194, Tehran, Iran;Intelligent Control Systems Laboratory, School of Electrical and Computer Engineering, Tarbiat Modares University, P.O. Box 14115-194, Tehran, Iran
Venue:
Neurocomputing
Year:
2011

Citing 12
Cited 1

Asymptotic and robust stability of genetic regulatory networks with time-varying delays

Neurocomputing
Brief paper: H∞ filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities

Automatica (Journal of IFAC)
A survey of linear matrix inequality techniques in stability analysis of delay systems

International Journal of Systems Science
Stochastic stability for uncertain genetic regulatory networks with interval time-varying delays

Neurocomputing
Robust stability of stochastic genetic regulatory networks with discrete and distributed delays

Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on ICNC-FSKD’2008;Guest Editors: Liang Zhao, Maozu Guo, Lipo Wang
Stability and stabilization of delayed T-S fuzzy systems: a delay partitioning approach

IEEE Transactions on Fuzzy Systems
Exponential stability of genetic regulatory networks with random delays

Neurocomputing
Robust state estimation for stochastic genetic regulatory networks

International Journal of Systems Science - Dynamics Analysis of Gene Regulatory Networks
On the transient and steady-state estimates of interval genetic regulatory networks

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On robust stability of stochastic genetic regulatory networks with time delays: a delay fractioning approach

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays

Neurocomputing
Brief Filtering on nonlinear time-delay stochastic systems

Automatica (Journal of IFAC)

Robust stability analysis of Markov jump standard genetic regulatory networks with mixed time delays and uncertainties

Neurocomputing

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper addresses robust H"~ filtering problem for a nonlinear genetic regulatory network (GRN), which is extended to include noise and disturbances, parameter uncertainties, and time-varying delays simultaneously. It is assumed that the nonlinear function that describes the feedback regulation satisfies the sector-bounded condition, the stochastic state perturbation is in the form of a scalar Brownian motion, and the time-varying delays enter into both the translation process and the feedback regulation process. To account for the unavoidable modeling errors and parameter fluctuations, the network parameters are assumed to be time-varying but norm-bounded values. We aim to estimate the true concentrations of mRNAs and proteins by designing a linear filter such that, for all admissible uncertainties, nonlinearities, stochastic perturbations and time delays, the dynamics of the filtering error is guaranteed to be robustly asymptotically stable in the mean square sense while achieving the prescribed H"~ disturbance attenuation level. By using the Lyapunov stability theory and Ito@? formula, sufficient conditions for the existence of the filter are obtained in the form of a linear matrix inequality (LMI). Then, explicit expressions for the desired filter gains are provided. Finally, a simulation example is given in order to illustrate the effectiveness of the proposed design procedure.