Fault detection for networked control systems with quantization and Markovian packet dropouts

In this paper, the problem of fault detection is investigated for networked control systems with signal quantization and random packet dropouts. In the study, the packet dropouts are modeled by a time-homogeneous Markov process. A residual generator is constructed, and the corresponding fault detection problem is converted into an H ∞ filtering problem. A sufficient condition for the design of fault detection is derived, which makes the resulting residual system to be stochastically stable with a prescribed H ∞ performance level. Finally, a numerical example is given to illustrate the effectiveness and efficiency of the proposed design method. HighlightsWe presented a new approach on H-infinity fault detection problem for network control system with quantization and packet dropouts.A two state Markov chain is used to characterize the packet dropout phenomenon of the network.A residual generator is constructed and the corresponding fault detection problem is formulated as an H-infinity filtering problem.A numerical example shows the effectiveness of the obtained design techniques.

[1]  Huiping Li,et al.  Network-Based Predictive Control for Constrained Nonlinear Systems With Two-Channel Packet Dropouts , 2014, IEEE Transactions on Industrial Electronics.

[2]  Peng Shi,et al.  H∞ CONTROL FOR NETWORK CONTROL SYSTEMS WITH PARTIALLY KNOWN TRANSITION PROBABILITIES , 2012 .

[3]  Fei Liu,et al.  Stabilization of Networked Control Systems With Random Delays , 2011, IEEE Transactions on Industrial Electronics.

[4]  Yugang Niu,et al.  Stabilization of Markovian jump linear system over networks with random communication delay , 2009, Autom..

[5]  James Lam,et al.  Analysis and Synthesis of Markov Jump Linear Systems With Time-Varying Delays and Partially Known Transition Probabilities , 2008, IEEE Transactions on Automatic Control.

[6]  RATHINASAMY SAKTHIVEL,et al.  Observer-based dissipative control for networked control systems: A switched system approach , 2015, Complex..

[7]  Yongduan Song,et al.  A novel approach to output feedback control of fuzzy stochastic systems , 2014, Autom..

[8]  Heidar Ali Talebi,et al.  Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems , 2014, IEEE Transactions on Control Systems Technology.

[9]  Sun Shuli,et al.  Linear optimal state and input estimators for networked control systems with multiple packet dropouts , 2012 .

[10]  Guo-Ping Liu,et al.  Filtering for Discrete-Time Networked Nonlinear Systems With Mixed Random Delays and Packet Dropouts , 2011, IEEE Transactions on Automatic Control.

[11]  Lihua Xie,et al.  Mean square stability for Kalman filtering with Markovian packet losses , 2011, Autom..

[12]  Guotao Hui,et al.  STABILIZATION OF NETWORKED CONTROL SYSTEMS WITH PIECEWISE CONSTANT GENERALIZED SAMPLED-DATA HOLD FUNCTION , 2013 .

[13]  Wang Zhi-quan.  Fault detection for networked control system with random packet dropout , 2011 .

[14]  Ju H. Park,et al.  Robust mixed H∞ and passive filtering for networked Markov jump systems with impulses , 2014, Signal Process..

[15]  Qing Zhao,et al.  Closed-loop design of fault detection for networked non-linear systems with mixed delays and packet losses , 2013 .

[16]  Peng Shi,et al.  Control of Markovian jump discrete-time systems with norm bounded uncertainty and unknown delay , 1999, IEEE Trans. Autom. Control..

[17]  Qingling Zhang,et al.  Memoryless variable structure control for affine nonlinear systems using only output information , 2015 .

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

[19]  Wei Xing Zheng,et al.  Fault Detection Filter Design for Markovian Jump Singular Systems With Intermittent Measurements , 2011, IEEE Transactions on Signal Processing.

[20]  Huijun Gao,et al.  State Estimation and Sliding-Mode Control of Markovian Jump Singular Systems , 2010, IEEE Transactions on Automatic Control.

[21]  D. Yue,et al.  Quantised control design for networked control systems , 2007 .

[22]  Khashayar Khorasani,et al.  Fault Detection and Isolation of discrete-time Markovian jump linear systems with application to a network of multi-agent systems having imperfect communication channels , 2009, Autom..

[23]  Hongye Su,et al.  Delay-dependent H∞ filtering for singular Markovian jump time-delay systems , 2010, Signal Process..

[24]  Guanghui Sun,et al.  Fault detection of switched linear systems with its application to turntable systems , 2011 .

[25]  Xingyu Wang,et al.  Output-feedback control design for NCSs subject to quantization and dropout , 2009, Inf. Sci..

[26]  Donghua Zhou,et al.  Robust fault detection for networked systems with communication delay and data missing , 2009, Autom..

[27]  Ligang Wu,et al.  Reliable Filtering With Strict Dissipativity for T-S Fuzzy Time-Delay Systems , 2014, IEEE Transactions on Cybernetics.

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

[29]  Hamid Reza Karimi,et al.  Fault detection for discrete-time Markov jump linear systems with partially known transition probabilities , 2010, Int. J. Control.

[30]  Peng Shi,et al.  Robust quantized H∞ control for network control systems with Markovian jumps and time delays , 2013 .

[31]  Lixian Zhang,et al.  Stability and stabilization of Markovian jump linear systems with partly unknown transition probabilities , 2009, Autom..

[32]  Lihua Xie,et al.  Finite-Level Quantized Feedback Control for Linear Systems , 2009, Proceedings of the 45th IEEE Conference on Decision and Control.

[33]  Zehui Mao,et al.  $H_\infty$-Filter Design for a Class of Networked Control Systems Via T–S Fuzzy-Model Approach , 2010, IEEE Transactions on Fuzzy Systems.