Abstract
In this note, the fault detection filtering problem is solved for nonlinear switched stochastic system in the T-S fuzzy framework. Our attention is concentrated on the construction of a robust fault detection technique to the nonlinear switched system with Brownian motion. Based on observer-based fault detection fuzzy filter as a residual generator, the proposed fault detection is formulated as a fuzzy filtering problem. By the utilization of the average dwell time technique and the piecewise Lyapunov function technique, the fuzzy-parameter-dependent fault detection filters are designed that guarantee the resulted error system to be mean-square exponential stable with a weighted H∞ error performance. Then, the corresponding solvability condition for the fault detection fuzzy filter is also established by the linearization procedure technique. Finally, simulation has been presented to show the effectiveness of the proposed fault detection technique.
| Original language | English |
|---|---|
| Pages (from-to) | 1310-1315 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Automatic Control |
| Volume | 61 |
| Issue number | 5 |
| Early online date | 5 Aug 2015 |
| DOIs | |
| Publication status | Published - May 2016 |
| Externally published | Yes |
Funding
This work was supported in part by the National Key Basic Research Program (973) of China (2012CB215202, 2014CB249200), the National Natural Science Foundation of China (61403048, 61134001, 61573112, and 61525303), the Australian Research Council (DP140102180, LP140100471), the Heilongjiang Outstanding Youth Science Fund (JC201406), the Fok Ying Tung Education Foundation (141059), the Basic and Frontier Research Project of Chongqing (cstc2015jcyjA40005), and the Fundamental Research Funds for the Central Universities (106112015CDJXY170001, HIT.BRETIV.201303).
Keywords
- fault detection
- fuzzy filtering
- stochastic systems
- Switched systems