Abstract
This work studies the fault detection problem for continuous-time asynchronous switched systems. For residual signal generation, we design a fault detection sliding mode observer such that residual characterizes the fault sensitivity level by H_ performance, and its robustness to process disturbance is determined by H∞ performance. Specifically, the challenge entails addressing the phenomenon of asynchronous switching between the controlled object and the observer, where there is a delay between the switching of the subsystems and the observer. A piece-wise Lyapunov function and average dwell time approach are applied to resolve the asynchronous switching stability within matched and unmatched periods. A feasible solution is derived based on linear matrix inequalities. For effective fault detection, a residual evaluation scheme is provided with a threshold. Finally, simulation results on a buck-boost converter are furnished to validate the usefulness of the proposed approach.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
S. X. Ding, Model-based Fault Diagnosis Techniques, vol. Second, Springer-Verlag London, pp. 13–116, 2013.
Z. Gao, C. Cecati, and S. X. Ding, “A survey of fault diagnosis and fault-tolerant techniques Part II: Fault diagnosis with knowledge-based and hybrid/active approaches,” IEEE Transactions on Industrial Electronics, vol. 62, pp. 3768–3774, 2015.
R. Busch and I. K. Peddle, “Active fault detection for open loop stable LTI SISO systems,” International Journal of Control, Automation, and Systems, vol. 12, pp. 324–332, 2014.
S. X. Ding, Advanced Methods for Fault Diagnosis and Fault-tolerant Control, vol. third, Springer-Verlag Germany, Part of Springer Nature, 2021.
Y. Jiang, S. Yin, and O. Kaynak, “Optimized design of parity relation based residual generator for fault detection: Data-driven approaches,” IEEE Transaction on Industrial Informatics, vol. 17, pp. 1449–1458, 2020.
J. C. L. Chan, W. S. Chua, T. H. Lee, and C. P. Tan, “Descriptor observers for robust fault reconstruction in a class of nonlinear descriptor systems,” International Journal of Control, Automation, and Systems, vol. 21, pp. 1–14, 2022.
M. Kordestani, M. Saif, M. E. Orchard, R. Razavi-Far, and K. Khorasani, “Failure prognosis and applications - A survey of recent literature,” IEEE Transaction on Reliability, vol. 70, pp. 728–748, 2021.
H. Luo, S. Yin, T. Liu, and A. Q. Khan, “A data-driven realization of the control-performance-oriented process monitoring system,” IEEE Transaction on Industrial Electronics, vol. 67, pp. 521–530, 2019.
W. Li, H. Li, S. Gu, and T. Chen, “Process fault diagnosis with model-and knowledge-based approaches: Advances and opportunities,” Control Engineering Practice, 2020.
Y. Jiang, S. Wu, and H. Yang, “Secure data transmission and trustworthiness judgement approaches against cyber-physical attacks in an integrated data-driven framework,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 52, pp. 7799–7809, 2022.
D. Zhai, A. Lu, J. Dong, and Q. Zhang, “Event triggered H_/H∞ fault detection and isolation for T-S fuzzy systems with local nonlinear models,” Signal Processing, vol. 138, pp. 244–255, 2017.
H. Sang, H. Nie, and J. Zhao, “Dwell-time-dependent asynchronous H∞ filtering for discrete-time switched systems with missing measurements,” Signal Processing, vol. 151, pp. 56–65, 2018.
Z. Wang, P. Shi, and C. Lim, “H_/H∞ fault detection observer in finite frequency domain for linear parameter-varying descriptor systems,” Automatica, vol. 86, pp. 38–45, 2017.
J. Xiong, X. H. Chang, and X. Yi, “Design of robust non-fragile fault detection filter for uncertain dynamic systems with quantization,” Applied Mathematics and Computation, vol. 338, pp. 774–788, 2018.
X. Xiao, L. Zhou, and G. Lu, “Event-triggered H∞ filtering of continuous-time switched linear systems,” Signal Processing, vol. 141, pp. 343–349, 2017.
D. Liberzon, Switching in Systems and Control, Springer Science & Business Media, 2012.
J. Harikumaran, G. Buticchi, G. Migliazz, V. Madonna, P Giangrande, A. Costabeber, P. Wheeler, and Mochael Galea, “Failure modes and reliability oriented system design for aerospace power electronic converters,” IEEE Open Journal of the Industrail Electronic Society, vol. 2, pp. 53–64, 2020.
H. Zhu, “Output regulation with prescribed performance control of switched strict-feedback systems,” International Journal of Control, Automation, and Systems, vol. 21, pp. 1–8, 2023.
R. Wang, L. Hou, G. Zong, S. Fei, and D. Yang, “Stability and stabilization of continuous-time switched systems: A multiple discontinuous convex Lyapunov function approach,” International Journal of Robust and Nonlinear Control, vol. 29, pp. 1499–1514, 2018.
W. Xiang, “Stabilization for continuous-time switched linear systems: A mixed switching scheme,” Nonlinear Analysis: Hybrid Systems, vol. 36, pp. 1–16, 2020.
S. Zhang, J. Zhang, X. Jia, and P. Lin, “Event-triggered asynchronous filter of switched nonlinear positive systems,” International Journal of Control, Automation, and Systems, vol. 21, pp. 536–552, 2023.
X. Lu, G. Jing, H. Sun, X. Lyu, A. Wen, Y. Guo, and Q. Zheng, “Dynamic event-triggered quantitative feedback control for switched affine systems,” International Journal of Control, Automation, and Systems, vol. 21, pp. 1861–1870, 2022.
J. Li, F. Jia, and X. He, “On fault detection of discrete-time switched systems via designing time-varying residual generators,” Journal of the Franklin Institute, vol. 358, pp. 1122–1135, 2021.
Q. Su, Z. Fan, and J. Li, “Observer-based fault detection for switched systems with all unstable subsystems.” Journal of Control and Decision, vol. 8, no. 2, pp. 116–123, 2019.
Q. Su, C. Li, X. Guo, X. Zhang, and J. Li, “Robust fault diagnosis for DC-DC Boost converters via switched systems,” Control Engineering Practice, vol. 112, 2021.
G. X. Zhong and G. H. Yang, “Simultaneous fault detection and control for discrete-time switched systems,” Circuits, Systems, and Signal Processing, vol. 34, pp. 3811–3831, 2015.
Y. Zhu and W. X. Zheng, “An integrated design approach for fault-tolerant control of switched LPV systems with actuator faults,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, 2023.
T. Sun, D. Zhou, Y. Zhu, and M. V. Basin, “Stability, l2-gain analysis, and parity space-based fault detection for discrete-time switched systems under dwell-time switching,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, pp. 3358–3368, 2020.
M. T. Raza, A. Q. Khan, G. Mustafa, and M. Abid, “Design of fault detection and isolation filter for switched control systems under asynchronous switching,” IEEE Transaction on control systems technology, vol. 24, pp. 13–23, 2016.
Y. Eddoukali, A. Benzaouia, and M. Ouladsine, “Integrated fault detection and control design for continuous-time switched systems under asynchronous switching,” ISA Transaction, vol. 84, pp. 12–19, 2019.
H. S. Nejad, A. R. Ghiasi, M. A. Badamchizadeh, and S. Pezeshki, “H∞/H_ Simultaneous fault detection and control for continuous-time linear switched delay systems under asynchronous switching,” Transaction of the Institute of Measurement and Control, vol. 41, pp. 263–275, 2019.
H. Azmi and A. Yazdizadeh, “Robust adaptive fault detection and diagnosis observer design for a class of nonlinear systems with uncertainty and unknown time-varying internal delay,” ISA Transaction, 2022.
J. Huang, X. Hao, and X. Pan, “Asynchronous switching control of discrete-time linear system based on mode-dependent average dwell time,” International Journal of Control, Automation and Systems, vol. 18, pp. 1705–1714, 2020.
A. Akhenak, M. Chadli, J. Ragot, and D. Maquin, “Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model,” Proc. of the 16th Mediterranean Conference on Control and Automation, pp. 286–291, 2021.
Y. Liu, X. Chen, J. Lu, and W. Gui, “Non-weighted l2/L2 gain of asynchronously switched systems,” Nonlinear Analysis: Hybrid Systems, vol. 43, 2021.
G. X. Zhong and G. H. Yang, “Asynchronous fault detection and robust control for switched systems with state reset strategy,” Journal of the Franklin Institute, vol. 355, pp. 250–272, 2018.
S. Shi, Z. Shi, and Z. Fei, “Asynchronous control for switched systems by using persistent dwell time modeling,” Systems Control Letter, vol. 133, 104523, 2019.
M. Chadli and M. Darouach, “Robust admissibility of uncertain switched singular systems,” International Journal of Control, vol. 84, pp. 1587–1600, 2011.
F. Zhu, Y. Shan, and Y. Tang, “Actuator and sensor fault detection and isolation for uncertain switched nonlinear system based on sliding mode observers,” International Journal of Control, Automation and Systems, vol. 19, pp. 3075–3086, 2021.
S. Shi, Z. Fei, and K. H. Reza, “Event-triggered control for switched T-S fuzzy systems with general asynchronism,” IEEE Transaction on Fuzzy Systems, vol. 30, pp. 27–38, 2020.
S. Shi, Z. Fei, and M. Dai, “Asynchronously bounded filtering for discrete-time switched positive systems,” Nonlinear Analysis: Hybrid Systems, vol. 44, pp. 101–121, 2022.
H. Habibi, I. Howard, S. Simani, and A. Fekih, “Decoupling adaptive sliding mode observer design for wind turbines subject to simultaneous faults in sensors and actuators,” IEEE/CAA Journal ofAutomatica Sinica, vol. 8, pp. 837–847, 2021.
P. Huang, F. Qi, Y. Chai, and L. Chen, “Intermittent sensor faults detection based on fractional-order transient chaotic system,” IEEE Transaction on Instrumentation and Measurement, vol. 71, 2020.
H. A. Khani and N. Meskin, “Event-triggered robust fault diagnosis and control of linear Roesser systems: A unified framework,” Automatica, vol. 128, 109575, 2021.
A. Akhenak, M. Chadli, D. Maquin, and J. Ragot, “Sliding mode multiple observer for fault detection and isolation,” Proc. of the 42nd IEEE International Conference on Decision and Control, vol. 90, pp. 230–238, 2004.
J. Li, K. Pan, and Q. Su, “Sensor fault detection and estimation for switched power electronics systems based on sliding mode observer,” Applied Mathematics and Computation∣, vol. 353, pp. 282–294, 2019.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
The authors declare that there is no potential conflict of interest possibly influencing the interpretation of data in the paper. Also, there is no competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.
Additional information
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work was supported in part by Natural Science Foundation of Heilongjiang Province under Grant LH2022F024, National Natural Science Foundation of China under Grant 62203143, Heilongjiang Province Postdoctoral Foundation under Grant LBH-Z22130.
Shafqat Ali received his B.E. degree in electronic engineering from Dawood University of Engineering and Technology Karachi, Pakistan and an M.Sc. degree in electrical engineering specialized in control systems from University of Engineering and Technology Lahore, Pakistan, in 2013 and 2017, respectively. Currently he is working toward a Ph.D. degree in control science and engineering from Harbin Institute of Technology Harbin, China. His research interests include robust control, fault diagnosis, switched systems, and sliding mode observer.
Yuchen Jiang received his B.E. degree in automation and a Ph.D. degree in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 2016 and 2021, respectively. He is currently with the School of Astronautics, Harbin Institute of Technology. His research interests include data-driven process monitoring, fault diagnosis and prognosis, industrial cyber-physical systems, and artificial intelligence.
Hao Luo received his B.E. degree in electrical engineering from Xi’an Jiaotong University, Xi’an, China, in 2007, and his M.Sc. and Ph.D. degrees in electrical engineering and information technology from the University of Duisburg-Essen, Duisburg, Germany, in 2012 and 2016, respectively. He is currently a Professor with the School of Astronautics, Harbin Institute of Technology, Harbin, China. His research interests include model-based and data-driven fault diagnosis, fault-tolerant systems, and their plug-and-play application on industrial systems.
Muhammad Taskeen Raza received his B.Sc. and M.Sc. degrees in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan, in 2004 and 2011, respectively, and a Ph.D. degree from the Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan, in 2016. He is currently working as an Assistant Professor with the Department of Electrical Engineering, Lahore College for Women University (LCWU), Lahore. His current research interests include fault diagnosis, fault tolerant control, autonomous systems, system modeling, and system identification.
Shah Faisal received his B.E. (first-class Hons) and M.E. degrees in electrical power from the Sarhad University of Science and IT Peshawar, Pakistan, in 2012 and 2017, respectively. He is pursuing a doctoral degree in control science and engineering at the Harbin Institute of Technology in Harbin, China. His research interests include fault diagnosis in industrial processes, multi-agent systems, distributed control, and cyber-physical systems.
Faizan Shahid received his B.S. degree in electronic engineering from Sir Syed University of Engineering and Technology Karachi, Pakistan and an M.S. degree in electrical engineering specialized in control systems from the National University of Science and Technology Karachi, Pakistan in 2011 and 2014, respectively. Currently, he is working toward a Ph.D. degree in control science and engineering from Harbin Institute of Technology Harbin, China. His research interests include artificial intelligence, robust control, fault diagnosis, and optimization using neural network.
Rights and permissions
About this article
Cite this article
Ali, S., Jiang, Y., Luo, H. et al. Robust Fault Detection Scheme for Asynchronous Switched Systems via Sliding Mode Observer. Int. J. Control Autom. Syst. 22, 1186–1200 (2024). https://doi.org/10.1007/s12555-023-0121-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12555-023-0121-4