Detection of intermittent faults for nonuniformly sampled multi-rate systems with dynamic quantisation and missing measurements

ABSTRACT This paper is concerned with the fault detection problem for a class of networked multi-rate systems with nonuniform sampling and dynamic quantization. The sampling interval of the measurements is allowed to be nonuniform that is governed by a time-homogenous Markov process with partly unknown and uncertain transition probabilities. The measured output is quantized by a dynamic quantizer and then transmitted through communication network subject to data missing. The main purpose of the problem under consideration is to design sampling-interval-dependent fault detection filters such that, in the simultaneous presence of nonuniform sampling, dynamic quantization, intermittent faults as well as missing measurements, the robustness of residuals with respect to the disturbance and the sensitivity of the residuals against the fault are guaranteed. Finally, a three-tank system is utilized to illustrate the effectiveness of the proposed fault detection scheme.

[1]  Steven X. Ding,et al.  Finite-time-convergent fault-tolerant control for dynamical systems and its experimental verification for DTS200 three-tank system , 2015 .

[2]  Ron J. Patton,et al.  A Mixed H/H∞ LPV Approach to Adaptive Fault Compensation for a Nonlinear UAV , 2012 .

[3]  Steven Liu,et al.  Fusion Estimation for Sensor Networks With Nonuniform Estimation Rates , 2014, IEEE Transactions on Circuits and Systems I: Regular Papers.

[4]  Lei Zou,et al.  Event-Based Finite-Time Filtering for Multirate Systems With Fading Measurements , 2017, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Huajing Fang,et al.  Takagi-sugeno fuzzy-model-based fault detection for networked control systems with Markov delays , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[7]  Cheng-Chew Lim,et al.  Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems , 2017, IEEE Transactions on Cybernetics.

[8]  Donghua Zhou,et al.  A New Scheme of Fault Detection for Linear Discrete Time-Varying Systems , 2016, IEEE Transactions on Automatic Control.

[9]  Zidong Wang,et al.  Fault detection filter design for networked multi-rate systems with fading measurements and randomly occurring faults , 2016 .

[10]  Tongwen Chen,et al.  Hinfinity filtering for nonuniformly sampled systems: A Markovian jump systems approach , 2011, Syst. Control. Lett..

[11]  Zidong Wang,et al.  H∞ state estimation with fading measurements, randomly varying nonlinearities and probabilistic distributed delays , 2015 .

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

[13]  Daniel Liberzon,et al.  Hybrid feedback stabilization of systems with quantized signals , 2003, Autom..

[14]  Han Ding,et al.  Bayesian Learning-Based Model-Predictive Vibration Control for Thin-Walled Workpiece Machining Processes , 2017, IEEE/ASME Transactions on Mechatronics.

[15]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[16]  Li Qiu,et al.  Model validation of multirate systems from time-domain experimental data , 2002, IEEE Trans. Autom. Control..

[17]  Sirish L. Shah,et al.  Generalized predictive control for non-uniformly sampled systems , 2002 .

[18]  Yang Song,et al.  Parity space-based fault detection for linear discrete time-varying systems with unknown input , 2015, Autom..

[19]  Qing-Long Han,et al.  Variance-Constrained Distributed Filtering for Time-Varying Systems With Multiplicative Noises and Deception Attacks Over Sensor Networks , 2017, IEEE Sensors Journal.

[20]  Carlos E. de Souza,et al.  Robust stability and stabilization of uncertain discrete-time Markovian jump linear systems , 2006, IEEE Transactions on Automatic Control.

[21]  Peng Shi,et al.  Adjustable Parameter-Based Distributed Fault Estimation Observer Design for Multiagent Systems With Directed Graphs , 2017, IEEE Transactions on Cybernetics.

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

[23]  Panos J. Antsaklis,et al.  Static and dynamic quantization in model-based networked control systems , 2007, Int. J. Control.

[24]  Tongwen Chen,et al.  H∞ filtering for nonuniformly sampled systems , 2010, CCECE 2010.

[25]  Baocang Ding,et al.  Stabilization of linear systems over networks with bounded packet loss and its use in model predictive control , 2011, Autom..

[26]  Hao Ye,et al.  Integrated design of residual generation and evaluation for fault detection of networked control systems , 2016 .

[27]  Zidong Wang,et al.  Variance-constrained state estimation for networked multi-rate systems with measurement quantization and probabilistic sensor failures , 2016 .

[28]  Fuwen Yang,et al.  Robust $H_{\infty}$ Control for Networked Systems With Random Packet Losses , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[29]  Zehui Mao,et al.  H/sub /spl infin// fault detection filter design for networked control systems modelled by discrete Markovian jump systems , 2007 .

[30]  Zidong Wang,et al.  Variance‐constrained state estimation for networked multi‐rate systems with measurement quantization and probabilistic sensor failures , 2016 .

[31]  H. Karimi,et al.  Discrete‐time H −  ∕ H ∞  sensor fault detection observer design for nonlinear systems with parameter uncertainty , 2015 .

[32]  Karl Henrik Johansson,et al.  Quantized Control Under Round-Robin Communication Protocol , 2016, IEEE Transactions on Industrial Electronics.

[33]  Zidong Wang,et al.  Sampled-Data Synchronization Control of Dynamical Networks With Stochastic Sampling , 2012, IEEE Transactions on Automatic Control.

[34]  Peng Shi,et al.  Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System , 2016, IEEE Transactions on Cybernetics.

[35]  Ke Zhang,et al.  Analysis and Design of Robust $H_\infty $ Fault Estimation Observer With Finite-Frequency Specifications for Discrete-Time Fuzzy Systems , 2015, IEEE Transactions on Cybernetics.

[36]  Hao Ye,et al.  Observer-Based Fast Rate Fault Detection for a Class of Multirate Sampled-Data Systems , 2007, IEEE Transactions on Automatic Control.

[37]  Lennart Ljung,et al.  Identification of Nonlinear State-Space Systems From Heterogeneous Datasets , 2018, IEEE Transactions on Control of Network Systems.

[38]  Yang Liu,et al.  Event-triggered filtering and fault estimation for nonlinear systems with stochastic sensor saturations , 2017, Int. J. Control.

[39]  Huijun Gao,et al.  On H-infinity Estimation of Randomly Occurring Faults for A Class of Nonlinear Time-Varying Systems With Fading Channels , 2016, IEEE Transactions on Automatic Control.

[40]  E. Boukas,et al.  H∞ control for discrete‐time Markovian jump linear systems with partly unknown transition probabilities , 2009 .

[41]  Ying Zheng,et al.  Normalized Relative RBC-Based Minimum Risk Bayesian Decision Approach for Fault Diagnosis of Industrial Process , 2016, IEEE Transactions on Industrial Electronics.

[42]  Steven X. Ding,et al.  Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools , 2008 .

[43]  Yang Liu,et al.  Least-Squares Fault Detection and Diagnosis for Networked Sensing Systems Using A Direct State Estimation Approach , 2013, IEEE Transactions on Industrial Informatics.

[44]  Min Wu,et al.  State Estimation for Discrete Time-Delayed Genetic Regulatory Networks With Stochastic Noises Under the Round-Robin Protocols , 2018, IEEE Transactions on NanoBioscience.

[45]  Yugang Niu,et al.  Control strategy with adaptive quantizer's parameters under digital communication channels , 2014, Autom..

[46]  Jun Hu,et al.  Dissipative control for state-saturated discrete time-varying systems with randomly occurring nonlinearities and missing measurements , 2013, Int. J. Control.

[47]  C.E. de Souza,et al.  Robust stability and stabilization of uncertain discrete-time Markovian jump linear systems , 2006, IEEE Transactions on Automatic Control.

[48]  Donghua Zhou,et al.  Detection of intermittent faults for linear stochastic systems subject to time-varying parametric perturbations , 2016 .

[49]  Ron J. Patton,et al.  A time-domain LPV H_/H∞ fault detection filter , 2017 .