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- Title
Fault diagnosis for sensors in a class of nonlinear systems.
- Authors
Guo, Run-Xia; Guo, Kai; Dong, Jian-Kang
- Abstract
Sensors are important parts of various control systems and their faults can cause degradation of systems. The problem of fault diagnosis for sensors is considered specially in this article. A time-varying and antidisturbance fault diagnosis algorithm based on the fault detection observer and the adaptive control theory has been proposed for a class of nonlinear systems that are influenced by disturbances and measurement noise. When external disturbances, measurement noise and faults of sensors exist simultaneously, the designed fault diagnosis algorithm is able to give specific estimated values of state variables and faults, respectively. The asymptotical stability of the fault detection observer in the diagnosis algorithm for sensors is guaranteed by setting a well-designed adaptive adjusting law of the fault vector. Moreover, a theoretically rigorous proof based on Lyapunov stability theory has been given. Two experiments have been carried out to evaluate the performance of the proposed fault diagnosis algorithm.
- Subjects
OBSERVABILITY (Control theory); NONLINEAR systems; ADAPTIVE control systems; DEBUGGING; LYAPUNOV stability
- Publication
IMA Journal of Mathematical Control & Information, 2018, Vol 35, Issue 2, p375
- ISSN
0265-0754
- Publication type
Article
- DOI
10.1093/imamci/dnw053