Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering

Autor: Yanyan Hu, Xiaoling Xue, Zengwang Jin, Kaixiang Peng
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Journal of Control Science and Engineering, Vol 2018 (2018)
Druh dokumentu: article
ISSN: 1687-5249
1687-5257
DOI: 10.1155/2018/5205698
Popis: A fault detection, isolation, and estimation approach is proposed in this paper based on Interactive Multimodel (IMM) fusion filtering and Strong Tracking Filtering (STF) for asynchronous multisensors dynamic systems. Time-varying fault is considered and a candidate fault model is built by augmenting the unknown fault amplitude directly into the system state for each kind of possible fault mode. By doing this, the dilemma of predetermining the fault extent as model design parameters in traditional IMM-based approaches is avoided. After that, the time-varying fault amplitude is estimated based on STF using its strong ability to track abrupt changes and robustness against model uncertainties. Through fusing information from multiple sensors, the performance of fault detection, isolation, and estimation is approved. Finally, a numerical simulation is performed to demonstrate the feasibility and effectiveness of the proposed method.
Databáze: Directory of Open Access Journals
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