Distributed sensor fault diagnosis in a class of interconnected nonlinear uncertain systems |
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| Authors: | Qi Zhang Xiaodong Zhang |
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| Affiliation: | 1. Department of Chemical Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1;2. Department of Chemical Engineering, Ryerson University, Toronto, ON, Canada M5B 2K3;1. Research Center of Satellite Technology, Harbin Institute of Technology, Harbin 150001, China;2. Department of Computing and Mathematical Sciences, University of Glamorgan, Pontypridd, CF37 1DL, UK;3. School of Engineering and Science, Victoria University, Melbourne, Vic. 3000, Australia;1. Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, 400044, China;2. School of Automation, Chongqing University, Chongqing, 400044, China;3. Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla CA 92093, USA;4. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore, Singapore |
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| Abstract: | In this paper, a distributed sensor fault detection and isolation (FDI) method is developed for a class of interconnected nonlinear uncertain systems. In the distributed FDI architecture, a FDI component is designed for each subsystem in the interconnected system. For each subsystem, its corresponding local FDI component is designed by utilizing local measurements and certain communicated information from neighboring FDI components associated with subsystems that are directly interconnected to the particular subsystem under consideration. Under certain assumptions, adaptive thresholds for distributed sensor fault detection and isolation in each subsystem are derived, ensuring robustness with respect to interactions among subsystems and system modeling uncertainty. Moreover, the fault detectability condition is rigorously investigated, characterizing the class of sensor faults in each subsystem that is detectable by the proposed distributed FDI method. Additionally, the stability and learning capability of the distributed adaptive fault isolation estimators is established. A simulation example of interconnected inverted pendulums mounted on carts is used to illustrate the effectiveness of the distributed FDI method. |
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