Distributed fault detection and estimation in cyber-physical systems subject to actuator faults.

The fault detection and estimation problems for the physical layer network in the cyber-physical systems with unknown external disturbances are investigated in this study. Both bias fault and loss of efficiency scenarios are considered for the actuators. Based on the adaptive threshold method and sliding mode observer approach, a distributed fault detection observer (DFDO) is constructed for each physical layer node to detect the occurrence of actuator faults. Then a relative global estimation error system is defined for the distributed fault estimation observer (DFEO). Compared with the existing results, the proposed DFEO can provide the estimation for not only the actuator bias faults but also the actuators' efficiency factors under the impact of exogenous disturbance with two gain dynamic update processes. Finally, the feasibility and effectiveness of the given DFDO and the DFEO are examined by Lyapunov stability method and the simulation results.

[1]  Luigi Glielmo,et al.  A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids , 2018, IEEE Transactions on Sustainable Computing.

[2]  Haibo Zhang,et al.  Multifunctional cyber-physical system testbed based on a source-grid combined scheduling control simulation system , 2017 .

[3]  Florian Dörfler,et al.  Attack Detection and Identification in Cyber-Physical Systems -- Part II: Centralized and Distributed Monitor Design , 2012, ArXiv.

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

[5]  Marios M. Polycarpou,et al.  Distributed Sensor Fault Diagnosis for a Network of Interconnected Cyberphysical Systems , 2015, IEEE Transactions on Control of Network Systems.

[6]  Yue Wang,et al.  Control of cyberphysical systems using passivity and dissipativity based methods , 2013, Eur. J. Control.

[7]  Zhu Wang,et al.  Distributed optimization for multi-agent systems with constraints set and communication time-delay over a directed graph , 2018, Inf. Sci..

[8]  Friedrich Wilhelm Fuchs,et al.  Doubly Fed Induction Generator Model-Based Sensor Fault Detection and Control Loop Reconfiguration , 2009, IEEE Transactions on Industrial Electronics.

[9]  Christopher Edwards,et al.  Robust decentralized actuator fault detection and estimation for large-scale systems using a sliding mode observer , 2008, Int. J. Control.

[10]  Qi Zhang,et al.  Distributed fault diagnosis in a class of interconnected nonlinear uncertain systems , 2012, Int. J. Control.

[11]  Guang-Hong Yang,et al.  Robust Distributed Fault Estimation for a Network of Dynamical Systems , 2018, IEEE Transactions on Control of Network Systems.

[12]  Guang-Hong Yang,et al.  End to end communication rate-based adaptive fault tolerant control of multi-agent systems under unreliable interconnections , 2018, Inf. Sci..

[13]  Necmiye Ozay,et al.  Guaranteed model-based fault detection in cyber-physical systems: A model invalidation approach , 2016, Autom..

[14]  Choon Ki Ahn,et al.  Robust Simultaneous Fault Estimation and Nonfragile Output Feedback Fault-Tolerant Control for Markovian Jump Systems , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[15]  Dan Ye,et al.  A co-design methodology for cyber-physical systems under actuator fault and cyber attack , 2019, J. Frankl. Inst..

[16]  Jianchang Liu,et al.  A consensus-based multi-agent approach for estimation in robust fault detection. , 2014, ISA transactions.

[17]  Yue Quan,et al.  Distributed Fault Detection for Second-Order Delayed Multi-Agent Systems With Adversaries , 2017, IEEE Access.

[18]  Sarangapani Jagannathan,et al.  Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems , 2016, Autom..

[19]  Christopher Edwards,et al.  A sliding mode observer for monitoring and fault estimation in a network of dynamical systems , 2014 .

[20]  Peng Shi,et al.  Active fault tolerant control design for reusable launch vehicle using adaptive sliding mode technique , 2012, J. Frankl. Inst..

[21]  Edward A. Lee,et al.  Modeling Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[22]  Mashor Housh,et al.  Model-based approach for cyber-physical attack detection in water distribution systems. , 2018, Water research.

[23]  Yongduan Song,et al.  Robust fault-tolerant cooperative control of multi-agent systems: A constructive design method , 2015, J. Frankl. Inst..

[24]  Yuanqing Xia,et al.  Fuzzy Adaptive Fault-Tolerant Output Feedback Attitude-Tracking Control of Rigid Spacecraft , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[25]  Lakshminarayanan Samavedham,et al.  A mechanistic fault detection and isolation approach using Kalman filter to improve the security of cyber physical systems , 2018, Journal of Process Control.

[26]  Christopher Edwards,et al.  Robust Fault Estimation Using Relative Information in Linear Multi-Agent Networks , 2014, IEEE Transactions on Automatic Control.

[27]  Rasim M. Alguliyev,et al.  Cyber-physical systems and their security issues , 2018, Comput. Ind..

[28]  Guang-Hong Yang,et al.  Secure Luenberger-like observers for cyber-physical systems under sparse actuator and sensor attacks , 2018, Autom..

[29]  Henrik Sandberg,et al.  Distributed Fault Detection and Isolation Resilient to Network Model Uncertainties , 2014, IEEE Transactions on Cybernetics.

[30]  Guang-Hong Yang,et al.  Secure state estimation for cyber-physical systems under sparse sensor attacks via a switched Luenberger observer , 2017, Inf. Sci..