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 |
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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 |
Bibliographical note
Funding Information:Manuscript received May 4, 2016; revised September 27, 2016; accepted November 14, 2016. Date of publication December 8, 2016; date of current version February 1, 2018. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1A6A1A03013567) and by the Korea government (MEST) (NRF-2015R1A2A2A05001610).
Funding Information:
This work was supported by the Basic ScienceResearch Program through the National Research Foundation of Korea (NRF)funded by the Ministry of Education (NRF-2016R1A6A1A03013567) and bythe Korea government (MEST) (NRF-2015R1A2A2A05001610).
Publisher Copyright:
© 1993-2012 IEEE.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics