Abstract
This paper presents an output-feedback exponential stabilization condition of sampled-data polynomial fuzzy control systems under variable sampling rates. Compared with previous work, the proposed method is less conservative because of the newly developed time-dependent fuzzy Lyapunov-Krasovskii functional that is based on the conventional fuzzy Lyapunov function. Moreover, the controller is allowed to contain polynomial gain matrices, thereby improving the control performance and design flexibility. This is realized by assuming the difference between the continuous- and discrete-time state vectors as time-varying norm-bounded uncertainties, which are manipulated using a robust control technique. A new sufficient condition is introduced to cast the stability condition containing the integral term as the sum-of-square conditions. Finally, the effectiveness of the proposed method is validated by simulations.
| Original language | English |
|---|---|
| Article number | 7778118 |
| Pages (from-to) | 366-373 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Fuzzy Systems |
| Volume | 26 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2018 Feb 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics
Cite this
}
A Fuzzy Lyapunov-Krasovskii Functional Approach to Sampled-Data Output-Feedback Stabilization of Polynomial Fuzzy Systems. / Kim, Han Sol; Park, Jin Bae; Joo, Young Hoon.
In: IEEE Transactions on Fuzzy Systems, Vol. 26, No. 1, 7778118, 01.02.2018, p. 366-373.Research output: Contribution to journal › Article
TY - JOUR
T1 - A Fuzzy Lyapunov-Krasovskii Functional Approach to Sampled-Data Output-Feedback Stabilization of Polynomial Fuzzy Systems
AU - Kim, Han Sol
AU - Park, Jin Bae
AU - Joo, Young Hoon
PY - 2018/2/1
Y1 - 2018/2/1
N2 - This paper presents an output-feedback exponential stabilization condition of sampled-data polynomial fuzzy control systems under variable sampling rates. Compared with previous work, the proposed method is less conservative because of the newly developed time-dependent fuzzy Lyapunov-Krasovskii functional that is based on the conventional fuzzy Lyapunov function. Moreover, the controller is allowed to contain polynomial gain matrices, thereby improving the control performance and design flexibility. This is realized by assuming the difference between the continuous- and discrete-time state vectors as time-varying norm-bounded uncertainties, which are manipulated using a robust control technique. A new sufficient condition is introduced to cast the stability condition containing the integral term as the sum-of-square conditions. Finally, the effectiveness of the proposed method is validated by simulations.
AB - This paper presents an output-feedback exponential stabilization condition of sampled-data polynomial fuzzy control systems under variable sampling rates. Compared with previous work, the proposed method is less conservative because of the newly developed time-dependent fuzzy Lyapunov-Krasovskii functional that is based on the conventional fuzzy Lyapunov function. Moreover, the controller is allowed to contain polynomial gain matrices, thereby improving the control performance and design flexibility. This is realized by assuming the difference between the continuous- and discrete-time state vectors as time-varying norm-bounded uncertainties, which are manipulated using a robust control technique. A new sufficient condition is introduced to cast the stability condition containing the integral term as the sum-of-square conditions. Finally, the effectiveness of the proposed method is validated by simulations.
UR - http://www.scopus.com/inward/record.url?scp=85041645064&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041645064&partnerID=8YFLogxK
U2 - 10.1109/TFUZZ.2016.2637368
DO - 10.1109/TFUZZ.2016.2637368
M3 - Article
AN - SCOPUS:85041645064
VL - 26
SP - 366
EP - 373
JO - IEEE Transactions on Fuzzy Systems
JF - IEEE Transactions on Fuzzy Systems
SN - 1063-6706
IS - 1
M1 - 7778118
ER -