Study on Robust Fault Detection For Linear Discrete Time-Varying Systems With Measurement Missing
Chun-peng Wang, Jian Guo
Available Online July 2017.
- https://doi.org/10.2991/iccse-17.2017.6How to use a DOI?
- Robust fault detection filter, Missing measurements, filtering, Linear discrete time-varying systems, Linear matrix inequality
- In this study, the robust fault detection problem is investigated for a class of linear discrete time-varying systems with multiple measurement packet dropouts. The missing measurements are modeled as a linear function of the stochastic variable satisfying Bernounlli random binary distribution. A robust fault detection filter based on filtering is designed to make residual error system be exponentially mean-square stable and satisfy a prescribed disturbance attenuation level. A sufficient condition is derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed method. The simulation result has showed the effectiveness and applicability of the obtained approach.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Chun-peng Wang AU - Jian Guo PY - 2017/07 DA - 2017/07 TI - Study on Robust Fault Detection For Linear Discrete Time-Varying Systems With Measurement Missing BT - 2017 International Conference on Computational Science and Engineering(ICCSE 2017) PB - Atlantis Press SP - 30 EP - 35 SN - 2352-538X UR - https://doi.org/10.2991/iccse-17.2017.6 DO - https://doi.org/10.2991/iccse-17.2017.6 ID - Wang2017/07 ER -