Robust weighted H∞ filtering for networked systems with intermittent measurements of multiple sensors

In this paper, we investigate the robust weighted H∞ filtering problem for networked systems with intermittent measurements under the discrete-time framework. Multiple outputs of the plant are measured by separate sensors, each of which has a specific failure rate. Network-induced delay, packet dropouts and network-induced disorder phenomena are all incorporated in the modeling of the network link. The resulting closed-loop system involves both delayed noise and non-delayed noise. In order to make full use of the delayed information, we define a weighted H∞ performance index. Sufficient delay-dependent and parameter-dependent conditions for the existence of the filter and the solvability of the addressed problem are given via a set of linear matrix inequalities. Two simulation examples are presented to illustrate the relationship between the minimal performance level and the weighting factor, which show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.

[1]  Huazhen Fang,et al.  Kalman filter‐based adaptive control for networked systems with unknown parameters and randomly missing outputs , 2009 .

[2]  Yang Shi,et al.  Improved robust energy-to-peak filtering for uncertain linear systems , 2010, Signal Process..

[3]  Sirish L. Shah,et al.  Optimal Hinfinity filtering in networked control systems with multiple packet dropouts , 2008, Syst. Control. Lett..

[4]  Huijun Gao,et al.  ${\cal H}_{\infty}$ Estimation for Uncertain Systems With Limited Communication Capacity , 2007, IEEE Transactions on Automatic Control.

[5]  I. Petersen,et al.  Model validation and state estimation for uncertain continuous-time systems with missing discrete-continuous data , 1999 .

[6]  Peng Shi,et al.  Central Suboptimal H∞ Filter Design for Linear Time-Varying Systems with State or Measurement Delay , 2009, Circuits Syst. Signal Process..

[7]  Shengyuan Xu,et al.  Robust H ∞ filtering for a class of non-linear systems with state delay and parameter uncertainty , 2002 .

[8]  Yang Shi,et al.  Output Feedback Stabilization of Networked Control Systems With Random Delays Modeled by Markov Chains , 2009, IEEE Transactions on Automatic Control.

[9]  Jing Wu,et al.  Design of Networked Control Systems With Packet Dropouts , 2007, IEEE Transactions on Automatic Control.

[10]  Edwin Engin Yaz,et al.  Robust minimum variance linear state estimators for multiple sensors with different failure rates , 2007, Autom..

[11]  P. Gahinet,et al.  A convex characterization of gain-scheduled H∞ controllers , 1995, IEEE Trans. Autom. Control..

[12]  M. Yan,et al.  Robust discrete-time sliding mode control for uncertain systems with time-varying state delay , 2008 .

[13]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[14]  Fuwen Yang,et al.  Robust H/sub /spl infin// filtering for stochastic time-delay systems with missing measurements , 2006, IEEE Transactions on Signal Processing.

[15]  W. McEneaney Robust/ H ∞ filtering for nonlinear systems , 1998 .

[16]  Long Wang,et al.  An LMI approach to networked control systems with data packet dropout and transmission delays , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[17]  Huijun Gao,et al.  Stabilization of Networked Control Systems With a New Delay Characterization , 2008, IEEE Transactions on Automatic Control.

[18]  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..

[19]  Andrey V. Savkin,et al.  The problem of state estimation via asynchronous communication channels with irregular transmission times , 2003, IEEE Trans. Autom. Control..

[20]  Huazhen Fang,et al.  Kalman filter-based identification for systems with randomly missing measurements in a network environment , 2010, Int. J. Control.

[21]  Fuwen Yang,et al.  Robust finite-horizon filtering for stochastic systems with missing measurements , 2005, IEEE Signal Processing Letters.

[22]  Tongwen Chen,et al.  Optimal ${\cal H}_{2}$ Filtering in Networked Control Systems With Multiple Packet Dropout , 2007, IEEE Transactions on Automatic Control.

[23]  Zidong Wang,et al.  Robust filtering with stochastic nonlinearities and multiple missing measurements , 2009, Autom..

[24]  Philippe Neveux,et al.  Robust filtering for uncertain systems , 2001, Signal Process..

[25]  Reinaldo M. Palhares,et al.  Robust filtering with guaranteed energy-to-peak performance - an LM1 approach , 2000, Autom..

[26]  Daniel W. C. Ho,et al.  Variance-constrained filtering for uncertain stochastic systems with missing measurements , 2003, IEEE Trans. Autom. Control..

[27]  Uri Shaked,et al.  H/sub infinity /-minimum error state estimation of linear stationary processes , 1990 .

[28]  Yang Shi,et al.  l2–l∞ Filtering for Multirate Systems Based on Lifted Models , 2008 .

[29]  Donghua Zhou,et al.  Robust $H_{\infty}$ Filtering for Time-Delay Systems With Probabilistic Sensor Faults , 2009, IEEE Signal Processing Letters.

[30]  X. Guan,et al.  State Feedback Controller Design of Networked Control Systems with Time Delay in the Plant , 2006, 2006 Chinese Control Conference.

[31]  Shengyuan Xu,et al.  Robust H∞ filtering for uncertain Markovian jump systems with mode‐dependent distributed delays , 2009 .

[32]  Alexandre Trofino,et al.  Robust H2 filtering for uncertain linear systems: LMI based methods with parametric Lyapunov functions , 2005, Syst. Control. Lett..

[33]  Nasser E. Nahi,et al.  Optimal recursive estimation with uncertain observation , 1969, IEEE Trans. Inf. Theory.

[34]  James Lam,et al.  A new delay system approach to network-based control , 2008, Autom..