Intermittent sensor fault detection for stochastic LTV systems with parameter uncertainty and limited resolution |
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| Authors: | Junfeng Zhang Panagiotis D Christofides Xiao He Fahad Albalawi Yinghong Zhao |
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| Affiliation: | 1. Department of Automation, BNRist, Tsinghua University, Beijing, People's Republic of China;2. Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA, USA;3. Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA;4. Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA |
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| Abstract: | ABSTRACTThis paper considers the detection problem of intermittent sensor faults in stochastic linear time-varying systems with both parameter uncertainty and limited resolution. By introducing the soft measurement model, a state estimator is designed whose upper bound of estimation error covariance is obtained and minimised at each time step. Based on it, the residual is generated and its relationship with the fault is analysed quantitatively. Then the evaluation function and corresponding detection threshold is given. Our proposed method is recursive and therefore suitable for real-time online applications. At last, two simulation studies are carried out to illustrate the validity of our proposed method. |
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| Keywords: | Intermittent fault detection robust fault detection parameter uncertainty limited resolution |
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