期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 26, 期 5, 页码 2967-2980出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2018.2809686
关键词
Agmon's inequality; distributed parameter systems (DPSs); exponential stability; sampled-data control; Takagi-Sugeno (TS) fuzzy partial differential equation (PDE) model
资金
- National Natural Science Foundation of China [61403026]
- National Science Council of Taiwan, R.O.C. [MOST-106-2221-E-027-009]
- National Taipei University of Technology University of Science and Technology Beijing (NTUT-USTB) Joint Research Program [NTUT-USTB-106-09]
- Fundamental Research Funds for the Central Universities [FRF-TW201707]
- Research Grants Council of Hong Kong SAR [CityU: 11205615]
- Hong Kong Scholars Program
This paper employs a Takagi-Sugeno (T-S) fuzzy partial differential equation (PDE) model to solve the problem of sampled-data exponential stabilization in the sense of spatial L-infinity norm parallel to center dot parallel to(infinity) for a class of nonlinear parabolic distributed parameter systems (DPSs), where only a few actuators and sensors are discretely distributed in space. Initially, a T-S fuzzy PDE, model is assumed to he derived by the sector nonlinearity method to accurately describe complex spatiotemporal dynamics of the nonlinear DPSs. Subsequently, a static sampled-data fuzzy local state feedback controller is constructed based on the T-S fuzzy PDE model. By constructing an appropriate Lyapunov-Krasovskii functional candidate and employing vector-valued Wirtinger's inequalities, a variation of vector-valued Poincare-Wirtinger inequality in one-dimensional spatial domain, as well as a vector-valued Agmon's inequality, it is shown that the suggested sampled-data fuzzy controller exponentially stabilizes the nonlinear DPSs in the sense of parallel to center dot parallel to(infinity), if sufficient conditions presented in term of standard linear matrix inequalities (LMIs) are fulfilled. Moreover, an LMI relaxation technique is utilized to enhance exponential stabilization ability of the suggested sampled-data fuzzy controller. Finally, the satisfactory and better performance of the suggested sampled-data fuzzy controller are demonstrated by numerical simulation results of two examples.
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