Fault estimation for nonlinear systems with sensor gain degradation and stochastic protocol based on strong tracking filtering

• Published in: Systems science & control engineering Vol. 9; no. S2; pp. 60 - 70
• Main Authors: Xu, Jie, Sheng, Li, Gao, Ming
• Format: Journal Article
• Language: English
• Published: Macclesfield Taylor & Francis 03.05.2021; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Degradation; fault estimation; Nonlinear systems; sensor gain degradation; Sensors; Signal transmission; State vectors; stochastic protocol; strong tracking filter; Tracking filters
• ISSN: 2164-2583; 2164-2583
• DOI: 10.1080/21642583.2020.1833789

This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol (SP) based on strong tracking filtering. The phenomenon of the sensor gain degradation is described by sequences of stochastic variables in a known interval. The stochastic protocol (SP) is used to deal with possible data conflicts in multi-signal transmission. The augmented system is constructed by combining the original system state vectors and the related faults into an augmented state vectors. The strong tracking filter (STF) is designed by introducing a fading factor into the filter structure to solve the problem of burst faults. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed filter.