Sensor fault detection based on fuzzy singularly perturbed model

Chunxiao He, Jinxiang Chen and Xisheng Li

International Journal of Systems Science, 2022, vol. 53, issue 8, 1690-1705

Abstract: Fuzzy singularly perturbed modelling and sensor fault detection for nonlinear singularly perturbed systems (NSPSs) are investigated. A continuous-time fuzzy singularly perturbed model with superimposed faults on state variables and external disturbances are established to describe NSPSs with sensor faults. Based on the model, a novelty $ H_\infty $ H∞ fuzzy fault detector (FFD) is designed, and the sufficient conditions for $ H_\infty $ H∞ performance are derived. The above approaches are applied to a CE150 helicopter with abrupt and intermittent faults on sensors. The innovations of this paper are as follows: (i) The nonlinear and slow–fast time-scales are described by a united continuous-time fuzzy singularly perturbed model, and based-it a FFD is designed, which can avoid the incomplete decoupling problem caused by decomposition methods; (ii) The sensor faults are expressed by the superimposed faults on state variables when the continuous-time fuzzy singularly perturbed model is constructed, which is less conservative than existing methods; (iii) In the FFD design, the first-order derivative model of the estimate function for sensor faults is established, and it is combined with a fuzzy observer, which can improve the detection accuracy of the FFD; (iv) $ H_\infty $ H∞ control technology is introduced into the FFD design process to suppress external disturbances.

Date: 2022
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DOI: 10.1080/00207721.2021.2020368

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