Local condition-based finite-horizon distributed H∞-consensus filtering for random parameter system with event-triggering protocols

This paper investigates the distributed H ∞ - consensus filtering problem for a class of discrete time-varying systems with random parameters and event-triggering protocols. An event-triggering protocol for each node is employed to reduce the burden of the network communication. A novel matrix named by information matrix is proposed to describe the complicated correlations among the elements of random matrix. By virtue of the presented information matrix, a weighted covariance matrix can be easily obtained to analyze the system with random parameters. With the aid of the newly constructed dissipation matrix and vector supplied rate functions, a set of local coupled conditions for each node is obtained such that the stochastic vector dissipativity-like over the finite-horizon of the filtering error dynamics can be guaranteed. As well, these sufficient conditions together could effectively solve the distributed H ∞ - consensus filtering problem. Notably, the designed filtering algorithm can be implemented on each node to obtain the desirable distributed filter gains. Finally, the effectiveness and applicability of the proposed algorithm is illustrated by a numerically simulative example.

[1]  Donghua Zhou,et al.  Event-Based Recursive Distributed Filtering Over Wireless Sensor Networks , 2015, IEEE Transactions on Automatic Control.

[2]  Zidong Wang,et al.  Distributed H∞ state estimation with stochastic parameters and nonlinearities through sensor networks: The finite-horizon case , 2012, Autom..

[3]  Fuad E. Alsaadi,et al.  Robust filtering for a class of nonlinear stochastic systems with probability constraints , 2016, Autom. Remote. Control..

[4]  Valery A. Ugrinovskii,et al.  Distributed robust filtering with Hinfinity consensus of estimates , 2011, Autom..

[5]  Songlin Hu,et al.  Event-triggered control design of linear networked systems with quantizations. , 2012, ISA transactions.

[6]  Qing-Long Han,et al.  Event-based H∞ filtering for sampled-data systems , 2015, Autom..

[7]  Jan Lunze,et al.  A state-feedback approach to event-based control , 2010, Autom..

[8]  Qing-Long Han,et al.  A Novel Event-Triggered Transmission Scheme and ${\cal L}_{2}$ Control Co-Design for Sampled-Data Control Systems , 2013, IEEE Transactions on Automatic Control.

[9]  Wenwu Yu,et al.  Distributed Consensus Filtering in Sensor Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Zidong Wang,et al.  Distributed State Estimation for Discrete-Time Sensor Networks With Randomly Varying Nonlinearities and Missing Measurements , 2011, IEEE Transactions on Neural Networks.

[11]  Yeung Sam Hung,et al.  Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case , 2010, Autom..

[12]  Dong Yue,et al.  To Transmit or Not to Transmit: A Discrete Event-Triggered Communication Scheme for Networked Takagi–Sugeno Fuzzy Systems , 2013, IEEE Transactions on Fuzzy Systems.

[13]  Marek Miskowicz,et al.  Send-On-Delta Concept: An Event-Based Data Reporting Strategy , 2006, Sensors (Basel, Switzerland).

[14]  Jun Hu,et al.  Gain-Constrained Recursive Filtering With Stochastic Nonlinearities and Probabilistic Sensor Delays , 2013, IEEE Transactions on Signal Processing.

[15]  Donghua Wang,et al.  Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications , 2008, Sensors.

[16]  Jun Hu,et al.  Recursive filtering with random parameter matrices, multiple fading measurements and correlated noises , 2013, Autom..

[17]  Valery A. Ugrinovskii,et al.  Distributed robust estimation over randomly switching networks using H∞ consensus , 2015, Autom..

[18]  Jun Hu,et al.  State estimation for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays , 2014, Int. J. Gen. Syst..

[19]  Hak-Keung Lam,et al.  Distributed Event-Based Set-Membership Filtering for a Class of Nonlinear Systems With Sensor Saturations Over Sensor Networks , 2017, IEEE Transactions on Cybernetics.

[20]  Zidong Wang,et al.  Event-triggered distributed ℋ ∞ state estimation with packet dropouts through sensor networks , 2015 .

[21]  Dong Yue,et al.  A Delay System Method for Designing Event-Triggered Controllers of Networked Control Systems , 2013, IEEE Transactions on Automatic Control.

[22]  Nanning Zheng,et al.  Event-triggered fuzzy H∞ control for a class of nonlinear networked control systems using the deviation bounds of asynchronous normalized membership functions , 2014, Inf. Sci..

[23]  Eloy García,et al.  Model-Based Event-Triggered Control for Systems With Quantization and Time-Varying Network Delays , 2013, IEEE Transactions on Automatic Control.

[24]  Jun Hu,et al.  Quantised recursive filtering for a class of nonlinear systems with multiplicative noises and missing measurements , 2013, Int. J. Control.

[25]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[26]  Hongli Dong,et al.  Distributed filtering in sensor networks with randomly occurring saturations and successive packet dropouts , 2014 .

[27]  Willem L. De Koning,et al.  Optimal estimation of linear discrete-time systems with stochastic parameters , 1984, at - Automatisierungstechnik.

[28]  VijaySekhar Chellaboina,et al.  Vector dissipativity theory and stability of feedback interconnections for large-scale non-linear dynamical systems , 2004 .

[29]  Huijun Gao,et al.  Distributed H∞ Filtering for a Class of Markovian Jump Nonlinear Time-Delay Systems Over Lossy Sensor Networks , 2013, IEEE Transactions on Industrial Electronics.

[30]  Yan Song,et al.  Distributed H∞-consensus filtering for piecewise discrete-time linear systems , 2015, J. Frankl. Inst..

[31]  Feng Wang,et al.  Networked Wireless Sensor Data Collection: Issues, Challenges, and Approaches , 2011, IEEE Communications Surveys & Tutorials.

[32]  Carlos Vivas,et al.  Event-based H2/H∞ controllers for networked control systems , 2014, Int. J. Control.

[33]  Jun Hu,et al.  A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements , 2016, Autom..

[34]  Qing-Long Han,et al.  Distributed event-triggered H1 filtering over sensor networks with communication delays , 2014 .

[35]  Ge Guo,et al.  Distributed event-triggered H∞ consensus filtering in sensor networks , 2015, Signal Process..

[36]  Kerim Demirbaş.  Fast state estimation scheme for multidimensional dynamic systems , 1988 .

[37]  Jun Hu,et al.  Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects , 2016, Inf. Fusion.

[38]  Wen-an Zhang,et al.  Distributed Fusion Estimation With Missing Measurements, Random Transmission Delays and Packet Dropouts , 2014, IEEE Transactions on Automatic Control.

[39]  Wei Wang,et al.  Distributed H∞ filtering in sensor networks with randomly occurred missing measurements and communication link failures , 2013, Inf. Sci..