In this paper, a sampled-data fuzzy control problem is addressed for a class of nonlinear coupled systems, which are described by a parabolic partial differential equation (PDE) and an ordinary differential equation (ODE). Initially, the nonlinear coupled system is accurately represented by the Takagi-Sugeno (T-S) fuzzy coupled parabolic PDE-ODE model. Then, based on the T-S fuzzy model, a novel time-dependent Lyapunov functional is used to design a sampled-data fuzzy controller such that the closed-loop coupled system is exponentially stable, where the sampled-data fuzzy controller consists of the ODE state feedback and the PDE static output feedback under spatially averaged measurements. The stabilization condition is presented in terms of a set of linear matrix inequalities. Finally, simulation results on the control of a hypersonic rocket car are given to illustrate the effectiveness of the proposed design method.
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http://dx.doi.org/10.1109/TCYB.2017.2690798 | DOI Listing |
ISA Trans
December 2024
School of Electrical Engineering, Yanshan University, Qinghuangdao, Hebei 066004, China. Electronic address:
In this paper, the sampled-data-based event-triggered tracking control for the positive nonlinear system is discussed. The event-triggered mechanism naturally causes a mismatch between the membership functions of the system model and the fuzzy controller. Meanwhile, the positive constraint and tracking behavior increase the complexity of system analysis and bring conservative analysis results.
View Article and Find Full Text PDFNeural Netw
December 2024
Department of Mathematics, Vellore Institute of Technology, Vellore, 632014, Tamilnadu, India. Electronic address:
This paper designs the sampled-data control (SDC) scheme to delve into the synchronization problem of fuzzy inertial cellular neural networks (FICNNs). Technically, the rate at which the information or activation of cellular neuronal transmission made can be described in a first-order differential model, but the network response concerning the received information may be dependent on time that can be modeled as a second-order (inertial) cellular neural network (ICNN) model. Generally, a fuzzy cellular neural network (FCNN) is a combination of fuzzy logic and a cellular neural network.
View Article and Find Full Text PDFMath Biosci Eng
May 2024
Navigation College, Jimei University, Xiamen 361021, China.
This article considered the sampled-data control issue for a dynamic positioning ship (DPS) with the Takagi-Sugeno (T-S) fuzzy model. By introducing new useful terms such as second-order term of time, an improved Lyapunov-Krasovskii function (LKF) was constructed. Additionally, the reciprocally convex method is introduced to bound the derivative of LKF.
View Article and Find Full Text PDFFor a nonlinear parabolic distributed parameter system (DPS), a fuzzy boundary sampled-data (SD) control method is introduced in this article, where distributed SD measurement and boundary SD measurement are respected. Initially, this nonlinear parabolic DPS is represented precisely by a Takagi-Sugeno (T-S) fuzzy parabolic partial differential equation (PDE) model. Subsequently, under distributed SD measurement and boundary SD measurement, a fuzzy boundary SD control design is obtained via linear matrix inequalities (LMIs) on the basis of the T-S fuzzy parabolic PDE model to guarantee exponential stability for closed-loop parabolic DPS by using inequality techniques and a acrlong LF.
View Article and Find Full Text PDFEntropy (Basel)
September 2022
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
This paper concentrates on the study of logic-based switching adaptive control. Two different cases will be considered. In the first case, the finite time stabilization problem for a class of nonlinear system is studied.
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