Model-reduced fault detection for multi-rate sensor fusion with unknown inputs
•We use model reduction to implement fault detection of multi-rate sensor systems.•A novel UI-decoupled and fault-related multi-rate observer is designed.•The proposed method gives fast and computation-efficient fault detection. In multi-sensor fusion, it is hard to guarantee that all sensors work a...
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| Veröffentlicht in: | Information fusion Jg. 33; S. 1 - 14 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.01.2017
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| ISSN: | 1566-2535, 1872-6305 |
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| Abstract | •We use model reduction to implement fault detection of multi-rate sensor systems.•A novel UI-decoupled and fault-related multi-rate observer is designed.•The proposed method gives fast and computation-efficient fault detection.
In multi-sensor fusion, it is hard to guarantee that all sensors work at the single sampling rate, especially in the distributive and/or heterogeneous case, and fault detection (FD) in multi-rate sensor fusion may face the existence of unknown inputs (UIs) in complex environment. Meanwhile, model reduction often refers to propose a possible lower-dimensional model to replace the original model without adding significant error in practical applications. By the fact that FD in dynamic systems should only focus on the fault-related controllability and observability characteristics, it is a good idea to obtain the fault-related controllable and observable subsystem via system decomposition (i.e., model reduction) for FD. Such a kind of model reduction not only guarantee the FD performance, but also reduce the system dimensions. To this end, we propose the model-reduced fault detection (MRFD) problem for multi-rate sensor fusion subject to UIs and faults imposed on the actuator and sensors. Our aim is to design a fast and computation-effective FD scheme based on the reduced model. We use the singular decomposition for UI decoupling, and then obtain the fault-related subsystem via controllability and observability decomposition. And then the multi-rate observer (MRO) with causality constraints is designed. Different from the traditional observer used for FD, the proposed MRO outputs the fault-related partial state estimate as soon as any a sensor measurement is received, resulting in fast and computation-effective FD. Furthermore, conditions for the existence of a stable MRO, fault-to-state controllability, and fault detectability are explored. A simulation example for simplified longitudinal flight control system and method comparison with the existing multi-rate FD algorithms show the effectiveness of the proposed MRFD method. |
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| AbstractList | •We use model reduction to implement fault detection of multi-rate sensor systems.•A novel UI-decoupled and fault-related multi-rate observer is designed.•The proposed method gives fast and computation-efficient fault detection.
In multi-sensor fusion, it is hard to guarantee that all sensors work at the single sampling rate, especially in the distributive and/or heterogeneous case, and fault detection (FD) in multi-rate sensor fusion may face the existence of unknown inputs (UIs) in complex environment. Meanwhile, model reduction often refers to propose a possible lower-dimensional model to replace the original model without adding significant error in practical applications. By the fact that FD in dynamic systems should only focus on the fault-related controllability and observability characteristics, it is a good idea to obtain the fault-related controllable and observable subsystem via system decomposition (i.e., model reduction) for FD. Such a kind of model reduction not only guarantee the FD performance, but also reduce the system dimensions. To this end, we propose the model-reduced fault detection (MRFD) problem for multi-rate sensor fusion subject to UIs and faults imposed on the actuator and sensors. Our aim is to design a fast and computation-effective FD scheme based on the reduced model. We use the singular decomposition for UI decoupling, and then obtain the fault-related subsystem via controllability and observability decomposition. And then the multi-rate observer (MRO) with causality constraints is designed. Different from the traditional observer used for FD, the proposed MRO outputs the fault-related partial state estimate as soon as any a sensor measurement is received, resulting in fast and computation-effective FD. Furthermore, conditions for the existence of a stable MRO, fault-to-state controllability, and fault detectability are explored. A simulation example for simplified longitudinal flight control system and method comparison with the existing multi-rate FD algorithms show the effectiveness of the proposed MRFD method. |
| Author | Liang, Yan Pan, Quan Xu, Linfeng Geng, Hang Yang, Feng |
| Author_xml | – sequence: 1 givenname: Hang surname: Geng fullname: Geng, Hang email: genghang@mail.nwpu.edu.cn organization: School of Automation, Northwestern Polytechnical University, Xi’an, PR China – sequence: 2 givenname: Yan surname: Liang fullname: Liang, Yan email: liangyan@nwpu.edu.cn organization: School of Automation, Northwestern Polytechnical University, Xi’an, PR China – sequence: 3 givenname: Feng surname: Yang fullname: Yang, Feng email: yangfeng@nwpu.edu.cn organization: School of Automation, Northwestern Polytechnical University, Xi’an, PR China – sequence: 4 givenname: Linfeng surname: Xu fullname: Xu, Linfeng email: xulinfeng@nwpu.edu.cn organization: School of Automation, Northwestern Polytechnical University, Xi’an, PR China – sequence: 5 givenname: Quan surname: Pan fullname: Pan, Quan email: quanpan@nwpu.edu.cn organization: School of Automation, Northwestern Polytechnical University, Xi’an, PR China |
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| Keywords | Model reduction Fault detection Multi-rate sensor fusion Unknown input decoupling |
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| Title | Model-reduced fault detection for multi-rate sensor fusion with unknown inputs |
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