Finite-horizon quantized H∞ filter design for a class of time-varying systems under event-triggered transmissions

Abstract This paper is concerned with the finite-horizon quantized H ∞ filter design problem for a class of time-varying systems with quantization effects and event-triggered measurement transmissions. A componentwise event-triggered transmission strategy is put forward to reduce the unnecessary communication burden for the purpose of energy efficiency. The transmitted measurements triggered according to prespecified events are quantized by a logarithmic quantizer. Special attention is paid to the design of the filter such that a prescribed H ∞ performance can be guaranteed over a given finite horizon in the presence of nonlinearities, quantization effects and event-triggered transmissions. Two sets of Riccati difference equations are introduced to ensure the H ∞ estimation performance of the designed filter. The filter design algorithm is recursive and thus suitable for online computation. A simulation example is illustrated to show the effectiveness of the proposed algorithm applied to the fault detection problem.

[1]  Young Soo Suh,et al.  Improving Estimation Performance in Networked Control Systems Applying the Send-on-delta Transmission Method , 2007, Sensors.

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

[3]  Mircea Lazar,et al.  On Event Based State Estimation , 2009, HSCC.

[4]  Ling Shi,et al.  Event-Based Sensor Data Scheduling: Trade-Off Between Communication Rate and Estimation Quality , 2013, IEEE Transactions on Automatic Control.

[5]  Hamid Reza Karimi,et al.  Robust L1 fixed-order filtering for switched LPV systems with parameter-dependent delays , 2015, J. Frankl. Inst..

[6]  Ling Shi,et al.  On Set-Valued Kalman Filtering and Its Application to Event-Based State Estimation , 2015, IEEE Transactions on Automatic Control.

[7]  Xingyu Wang,et al.  Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems , 2015 .

[8]  Young Soo Suh,et al.  Networked Estimation with an Area-Triggered Transmission Method , 2008, Sensors.

[9]  H. Karimi Robust H 1 Filter Design for Uncertain Linear Systems Over Network with Network-Induced Delays and Output Quantization , 2009 .

[10]  Dong Yue,et al.  Event-based fault detection for networked systems with communication delay and nonlinear perturbation , 2013, J. Frankl. Inst..

[11]  Zidong Wang,et al.  A survey of event-based strategies on control and estimation , 2014 .

[12]  Dong Yue,et al.  Event-based H∞ filtering for networked system with communication delay , 2012, Signal Process..

[13]  Hamid Reza Karimi,et al.  Finite-Time $H_{\infty }$ Filtering for T–S Fuzzy Discrete-Time Systems With Time-Varying Delay and Norm-Bounded Uncertainties , 2015, IEEE Transactions on Fuzzy Systems.

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

[15]  Tongwen Chen,et al.  Event triggered robust filter design for discrete-time systems , 2014 .

[16]  H. Karimi,et al.  Quantized ℋ∞ Filtering for Continuous‐Time Markovian Jump Systems with Deficient Mode Information , 2015 .

[17]  Isaac Yaesh,et al.  H-Control and Estimation of State-multiplicative Linear Systems , 2005 .

[18]  Huijun Gao,et al.  Finite-Horizon $H_{\infty} $ Filtering With Missing Measurements and Quantization Effects , 2013, IEEE Transactions on Automatic Control.

[19]  Xing Xing,et al.  Event-Triggered Filtering for Nonlinear Networked Discrete-Time Systems , 2015, IEEE Transactions on Industrial Electronics.

[20]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[21]  Minyue Fu,et al.  State estimation for linear discrete-time systems using quantized measurements , 2009, Autom..

[22]  Nan Xiao,et al.  Stabilization of Markov jump linear systems using quantized state feedback , 2010, Autom..

[23]  Young Soo Suh,et al.  Modified Kalman filter for networked monitoring systems employing a send-on-delta method , 2007, Autom..

[24]  Choon Ki Ahn,et al.  Novel Results on Generalized Dissipativity of Two-Dimensional Digital Filters , 2016, IEEE Transactions on Circuits and Systems II: Express Briefs.