Neighborhood-Based Event-Triggered Distributed Fault Estimation Observer for Multi-Agent Systems

Document Type : Research Article


Department of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.


This study addresses the distributed Fault Estimation control problem for linear multi-agent systems with an event-triggered communication mechanism. In multi-agent systems, a substantial challenge is to find out the size and shape of the occurred faults and how to reduce the wastage of communication bandwidth and unnecessary executions. In order to address these concerns, we proposed a distributed Fault Estimation observer, where each agent employs an augmented system based on a predefined communication graph, and with consideration of its neighbors, to estimate the fault and states both in itself as well as its neighbors, simultaneously. In addition, an event-triggering scheme was implemented in this approach in order to effectively reduce unnecessary signal transmission between the agents and attain a reasonable allocation of resources. Sufficient conditions are presented to guarantee that the closed-loop system is asymptotically stable with prescribed disturbance attenuation, and the parameter matrices of the event-triggered mechanism and observer can be obtained simultaneously by solving a set of Linear Matrix Inequities (LMIs). Eventually, some simulations are included to demonstrate the performance of the introduced Fault Estimation and effectively of the event-triggered mechanism.


Main Subjects

[1] M. Dunbabin, L. Marques, Robots for environmental monitoring: Significant advancements and applications, IEEE Robotics & Automation Magazine, 19(1) (2012) 24-39.
[2] H. Rezaei, R.M. Esfanjani, M.H. Sedaaghi, Improved robust finite-horizon Kalman filtering for uncertain networked time-varying systems, Information Sciences, 293 (2015) 263-274.
[3] M.A. Kamel, X. Yu, Y. Zhang, Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: A review, Annual reviews in control, 49 (2020) 128-144.
[4] F. Chen, W. Ren, On the control of multi-agent systems: A survey, Foundations and Trends® in Systems and Control, 6(4) (2019) 339-499.
[5] F. Rahimi, R.M. Esfanjani, Distributed predictive control for formation of networked mobile robots, in:  2018 6th RSI International Conference on Robotics and Mechatronics (IcRoM), IEEE, 2018, pp. 70-75.
[6] V. Loia, A. Vaccaro, Decentralized economic dispatch in smart grids by self-organizing dynamic agents, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(4) (2013) 397-408.
[7] J. Qin, Q. Ma, Y. Shi, L. Wang, Recent advances in consensus of multi-agent systems: A brief survey, IEEE Transactions on Industrial Electronics, 64(6) (2016) 4972-4983.
[8] J. Qin, G. Zhang, W.X. Zheng, Y. Kang, Adaptive sliding mode consensus tracking for second-order nonlinear multiagent systems with actuator faults, IEEE Transactions on Cybernetics, 49(5) (2018) 1605-1615.
[9] A. Qiu, J. Gu, C. Wen, J. Zhang, Self-triggered Fault Estimation and fault tolerant control for networked control systems, Neurocomputing, 272 (2018) 629-637.
[10] S.X. Ding, Advanced methods for fault diagnosis and fault-tolerant control, Springer, 2021.
[11] P. Dhanalakshmi, S. Senpagam, R.M. Priya, Robust Fault Estimation controller for fractional-order delayed system using quantized measurement, International Journal of Dynamics and Control, 8(1) (2020) 326-336.
[12] N. Torabi, M.R. Motavalli, A. Mihankhah, S. Rastani, Fault tolerant sliding mode intelligent control based on fault hiding for a nonlinear induction furnace system, International Journal of Dynamics and Control, 9(2) (2021) 636-644.
[13] I. Hwang, S. Kim, Y. Kim, C.E. Seah, A survey of fault detection, isolation, and reconfiguration methods, IEEE transactions on control systems technology, 18(3) (2009) 636-653.
[14] J. Zhang, D.W. Ding, X. Sun, Y. Wang, Cooperative fault‐tolerant control for heterogeneous nonlinear multiagent systems via distributed output regulation, International Journal of Robust and Nonlinear Control, 31(3) (2021) 855-872.
[15] J.-W. Zhu, Q.-Q. Zhou, L.-B. Wu, J.-M. Xu, X. Wang, Topology reconstruction based fault identification for uncertain multi-agent systems with application to multi-axis motion control system, Applied Mathematics and Computation, 399 (2021) 126000.
[16] K. Zhang, B. Jiang, P. Shi, Observer-based Fault Estimation and accomodation for dynamic systems, Springer, 2012.
[17] Q.T. Nguyen, N. Messai, N. Manamanni, S. Martinez-Martinez, Fault Estimation for networks of non-homogeneous agents with switching topologies, European Journal of Control, 56 (2020) 191-205.
[18] K. Zhang, B. Jiang, S.X. Ding, D. Zhou, Robust asymptotic Fault Estimation of discrete-time interconnected systems with sensor faults, IEEE transactions on cybernetics,  (2020).
[19] H. Dong, N. Hou, Z. Wang, Fault Estimation for complex networks with randomly varying topologies and stochastic inner couplings, Automatica, 112 (2020) 108734.
[20] F. Rahimi, H. Rezaei, A distributed Fault Estimation approach for a class of continuous-time nonlinear networked systems subject to communication delays, IEEE Control Systems Letters, 6 (2021) 295-300.
[21] K. Zhang, B. Jiang, V. Cocquempot, Distributed Fault Estimation observer design for multi-agent systems with switching topologies, IET Control Theory & Applications, 11(16) (2017) 2801-2807.
[22] W. Han, H.L. Trentelman, Z. Wang, Y. Shen, Distributed Fault Estimation for linear systems with actuator faults, International Journal of Robust and Nonlinear Control, 30(16) (2020) 6853-6878.
[23] X. Zhao, Q. Zong, B. Tian, W. Liu, Integrated Fault Estimation and fault-tolerant tracking control for Lipschitz nonlinear multiagent systems, IEEE transactions on cybernetics, 50(2) (2018) 678-688.
[24] C. Zhang, H. Yang, B. Jiang, Fault Estimation and accommodation of fractional-order nonlinear, switched, and interconnected systems, IEEE transactions on cybernetics,  (2020).
[25] H. Yang, C. Huang, B. Jiang, M.M. Polycarpou, Fault Estimation and accommodation of interconnected systems: a separation principle, IEEE transactions on cybernetics, 49(12) (2018) 4103-4116.
[26] X. Ge, Q.-L. Han, L. Ding, Y.-L. Wang, X.-M. Zhang, Dynamic event-triggered distributed coordination control and its applications: A survey of trends and techniques, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(9) (2020) 3112-3125.
[27] S. Li, Y. Chen, J. Zhan, Event-triggered consensus control and Fault Estimation for time-delayed multi-agent systems with Markov switching topologies, Neurocomputing, 460 (2021) 292-308.
[28] H. Li, J. Pan, X. Zhang, J. Yu, Integral-based event-triggered Fault Estimation and impulsive fault-tolerant control for networked control systems applied to underwater vehicles, Neurocomputing, 442 (2021) 36-47.
[29] X. Liu, X. Gao, J. Han, Distributed Fault Estimation for a class of nonlinear multiagent systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(9) (2018) 3382-3390.
[30] F. Rahimi, S. Ahmadpour, Neighborhood‐based distributed robust unknown input observer for Fault Estimation in nonlinear networked systems, IET Control Theory & Applications,  (2022).
[31] X. Liu, J. Han, X. Wei, H. Zhang, X. Hu, Distributed fault detection for non-linear multi-agent systems: an adjustable dimension observer design method, IET Control Theory & Applications, 13(15) (2019) 2407-2415.
[32] J. Shi, X. He, Z. Wang, D. Zhou, Distributed fault detection for a class of second-order multi-agent systems: an optimal robust observer approach, IET Control Theory & Applications, 8(12) (2014) 1032-1044.
[33] K. Zhang, B. Jiang, V. Cocquempot, Adaptive technique-based distributed Fault Estimation observer design for multi-agent systems with directed graphs, IET Control Theory & Applications, 9(18) (2015) 2619-2625.
[34] X. Wang, Z. Fei, T. Wang, L. Yang, Dynamic event-triggered actuator Fault Estimation and accommodation for dynamical systems, Information Sciences, 525 (2020) 119-133.
[35] F. Rahimi, H. Rezaei, An event-triggered recursive state estimation approach for time-varying nonlinear complex networks with quantization effects, Neurocomputing, 426 (2021) 104-113.
[36] H. Rezaei, A. Farnam, F. Rahimi, G. Crevecoeur, Scalable distributed state estimation for a class of state-saturated systems subject to quantization effects, IEEE Access, 9 (2021) 138724-138733.
[37] C. Chen, K. Xie, F.L. Lewis, S. Xie, R. Fierro, Adaptive synchronization of multi-agent systems with resilience to communication link faults, Automatica, 111 (2020) 108636.