Non-fragile H∞ filtering for discrete-time networked systems with multiple communication delays

This paper is concerned with the non-fragile H∞ filtering for a class of discrete-time networked systems with multiple communication delays. We model such a complex delay system as a switched system. For the filtering implementation uncertainty, a stochastic variable is employed to describe the phenomenon of the randomly occurring filter gain change, and a norm bound is used to measure the change size. With the switched system theory and the stochastic system analysis, a new sufficient condition is obtained such that the filtering error system is exponentially stable in the mean square sense and achieves a prescribed H∞ performance level. A numerical example is given to show the effectiveness of the proposed design.

[1]  Fei Liu,et al.  H∞ Filtering for Discrete-Time Systems With Stochastic Incomplete Measurement and Mixed Delays , 2012, IEEE Trans. Ind. Electron..

[2]  Fuchun Sun,et al.  Gain-Scheduling-Based State Feedback Integral Control for Networked Control Systems , 2011, IEEE Transactions on Industrial Electronics.

[3]  E. Boukas,et al.  Exponential H∞ filtering for uncertain discrete‐time switched linear systems with average dwell time: A µ‐dependent approach , 2008 .

[4]  Huajing Fang,et al.  H∞ fault detection for nonlinear networked systems with multiple channels data transmission pattern , 2013, Inf. Sci..

[5]  Ya-Jun Pan,et al.  Robust H∞ filtering for networked stochastic systems with randomly occurring sensor nonlinearities and packet dropouts , 2013, Signal Process..

[6]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[7]  Guang-Hong Yang,et al.  Non-fragile Hinfinity filter design for linear continuous-time systems , 2008, Autom..

[8]  Huijun Gao,et al.  Network-Induced Constraints in Networked Control Systems—A Survey , 2013, IEEE Transactions on Industrial Informatics.

[9]  Biao Huang,et al.  A new method for stabilization of networked control systems with random delays , 2005, Proceedings of the 2005, American Control Conference, 2005..

[10]  Qing-Long Han,et al.  Network-based H∞H∞ filtering using a logic jumping-like trigger , 2013, Autom..

[11]  Magdi S. Mahmoud,et al.  Resilient linear filtering of uncertain systems , 2004, Autom..

[12]  Lihua Xie,et al.  The sector bound approach to quantized feedback control , 2005, IEEE Transactions on Automatic Control.

[13]  Huijun Gao,et al.  Fault Detection for Markovian Jump Systems With Sensor Saturations and Randomly Varying Nonlinearities , 2012, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  Daniel W. C. Ho,et al.  Robust H∞ control for a class of nonlinear discrete time-delay stochastic systems with missing measurements , 2009, Autom..

[15]  James Lam,et al.  Feedback control with signal transmission after-effects , 2008 .

[16]  Guang-Hong Yang,et al.  Non-fragile fuzzy H∞ filter design for nonlinear continuous-time systems with D stability constraints , 2012, Signal Process..

[17]  Jianliang Wang,et al.  H∞ Controller Design of Networked Control Systems with Markov Packet Dropouts , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[18]  João Pedro Hespanha,et al.  A Survey of Recent Results in Networked Control Systems , 2007, Proceedings of the IEEE.

[19]  Wei Xing Zheng,et al.  Weighted H∞ model reduction for linear switched systems with time-varying delay , 2009, Autom..

[20]  Wen-an Zhang,et al.  Hinfinity filtering of networked discrete-time systems with random packet losses , 2009, Inf. Sci..

[21]  Jun Hu,et al.  Robust Sliding Mode Control for Discrete Stochastic Systems With Mixed Time Delays, Randomly Occurring Uncertainties, and Randomly Occurring Nonlinearities , 2012, IEEE Transactions on Industrial Electronics.

[22]  Qing-Guo Wang,et al.  Fuzzy-Model-Based Fault Detection for a Class of Nonlinear Systems With Networked Measurements , 2013, IEEE Transactions on Instrumentation and Measurement.