Abstract
This paper is concerned with the mixed-time fuzzy optimal estimator for the target tracking. The proposed method takes account of behaviour for target motion in continuous time and system measurement in discrete time. The overall dynamic of system in continuous-time is discretised by using Takagi-Sugeno(T-S) fuzzy models. Based on the fuzzy model the fuzzy estimation is studied. Then the error state of the filtering process is means square bounded. A basis dependent Lyapunov function approach is developed to design the fuzzy filter and a filter gain is minimized by using some linear matrix inequalities(LMIs) constraints. A numerical example is provided to demonstrate various aspects of theoretical results.
| Original language | English |
|---|---|
| Title of host publication | FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings |
| Pages | 1994-1998 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 Sep 27 |
| Event | 2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan, Province of China Duration: 2011 Jun 27 → 2011 Jun 30 |
Other
| Other | 2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 |
|---|---|
| Country | Taiwan, Province of China |
| City | Taipei |
| Period | 11/6/27 → 11/6/30 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
- Applied Mathematics
- Theoretical Computer Science
Cite this
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Mixed-time T-S fuzzy optimal estimator for target tracking. / Noh, Sun Young; Park, Jin Bae; Joo, Young Hoon.
FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. 2011. p. 1994-1998 6007671.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Mixed-time T-S fuzzy optimal estimator for target tracking
AU - Noh, Sun Young
AU - Park, Jin Bae
AU - Joo, Young Hoon
PY - 2011/9/27
Y1 - 2011/9/27
N2 - This paper is concerned with the mixed-time fuzzy optimal estimator for the target tracking. The proposed method takes account of behaviour for target motion in continuous time and system measurement in discrete time. The overall dynamic of system in continuous-time is discretised by using Takagi-Sugeno(T-S) fuzzy models. Based on the fuzzy model the fuzzy estimation is studied. Then the error state of the filtering process is means square bounded. A basis dependent Lyapunov function approach is developed to design the fuzzy filter and a filter gain is minimized by using some linear matrix inequalities(LMIs) constraints. A numerical example is provided to demonstrate various aspects of theoretical results.
AB - This paper is concerned with the mixed-time fuzzy optimal estimator for the target tracking. The proposed method takes account of behaviour for target motion in continuous time and system measurement in discrete time. The overall dynamic of system in continuous-time is discretised by using Takagi-Sugeno(T-S) fuzzy models. Based on the fuzzy model the fuzzy estimation is studied. Then the error state of the filtering process is means square bounded. A basis dependent Lyapunov function approach is developed to design the fuzzy filter and a filter gain is minimized by using some linear matrix inequalities(LMIs) constraints. A numerical example is provided to demonstrate various aspects of theoretical results.
UR - http://www.scopus.com/inward/record.url?scp=80053083295&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053083295&partnerID=8YFLogxK
U2 - 10.1109/FUZZY.2011.6007671
DO - 10.1109/FUZZY.2011.6007671
M3 - Conference contribution
SN - 9781424473175
SP - 1994
EP - 1998
BT - FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
ER -