Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2006.07d
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- Pages.1854-1855
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- 2006
Robust Kalman filtering for the TS Fuzzy State Estimation
TS 퍼지 상태 추정에 관한 강인 칼만 필터
- Noh, Sun-Young (Yonsei University) ;
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Joo, Young-Hoon
(Kunsan National University) ;
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Park, Jin-Bae
(Yonsei University)
- Published : 2006.07.12
Abstract
In this paper, the Takagi-Sugeno (TS) fuzzy state estimation scheme, which is suggested for a steady state estimator using standard Kalman filter theory with uncertainties. In that case, the steady state with uncertain can be represented by the TS fuzzy model structure, which is further rearranged to give a set of uncertain linear model using standard Kalman filter theory. And then the unknown uncertainty is regarded as an additive process noise. To optimize fuzzy system, we utilize the genetic algorithm. The steady state solutions can be found for proposed linear model then the linear combination is used to derive a global model. The proposed state estimator is demonstrated on a truck-trailer.
Keywords