Model Predictive Control Based on a Takagi–Sugeno Fuzzy Model for Nonlinear Systems

2018 ◽  
Vol 21 (2) ◽  
pp. 556-570 ◽  
Author(s):  
Yong-Lin Kuo ◽  
Ilmiyah Elrosa Citra Resmi
Keyword(s):  
Nonlinear Systems ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Fuzzy Model ◽  
Takagi Sugeno

Takagi–Sugeno Fuzzy Predictive Control for a Class of Nonlinear System With Constrains and Disturbances

2015 ◽  
Vol 10 (5) ◽  
Author(s):  
Bin Wang ◽  
Jianwei Zhang ◽  
Delan Zhu ◽  
Diyi Chen
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Predictive Control ◽  
Three Dimensional ◽  
Fuzzy Model ◽  
Control Input ◽  
Chen System ◽  
External Disturbances ◽  
Takagi Sugeno ◽  
Fuzzy Predictive Control

This paper investigates the fuzzy predictive control for a class of nonlinear system with constrains under the condition of noise. Based on the fuzzy linearization theory, a class of nonlinear systems can be described by the Takagi–Sugeno (T–S) fuzzy model. The T–S fuzzy model and predictive control are combined to stabilize the proposed class of nonlinear system, and the detailed mathematical derivation is given. Moreover, the designed controller has been optimized even if the system is constrained by output and control input, or perturbed by external disturbances. Finally, numerical simulations including three-dimensional Lorenz system, four-dimensional Chen system and five-dimensional nonlinear system with external disturbances are presented to demonstrate the universality and effectiveness of the proposed scheme. The approach proposed in this paper is simple and easy to implement and also provides reference for relevant nonlinear systems.

scholarly journals Decentralized robust interval type-2 fuzzy model predictive control for Takagi–Sugeno large-scale systems

Automatika ◽  
2021 ◽  
Vol 63 (1) ◽  
pp. 49-63
Author(s):  
Mohammad Sarbaz ◽  
Iman Zamani ◽  
Mohammad Manthouri ◽  
Asier Ibeas
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Large Scale ◽  
Fuzzy Model ◽  
Large Scale Systems ◽  
Interval Type ◽  
Takagi Sugeno

Fuzzy Based Model Predictive Control for Uncertain Nonlinear System

2011 ◽  
Vol 383-390 ◽  
pp. 2404-2410
Author(s):  
Li Xu ◽  
Fei Liu
Keyword(s):  
Nonlinear System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Uncertain Nonlinear System ◽  
Predictive Controller ◽  
The Stability ◽  
Takagi Sugeno ◽  
Parameter Dependent

In this paper, a model predictive control (MPC) scheme is investigated for uncertain nonlinear system with time delay and input constraint. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the dynamics of nonlinear processes and the parallel distributed compensation (PDC) controllers which are parameter dependent and mirror the structure of the T-S plant model are proposed. Then a novel feedback PDC predictive controller obtained from the linear matrix inequality (LMI) solutions which can guarantee the stability of the closed-loop overall fuzzy system is put forward. Finally, a numerical example is provided to demonstrate the effectiveness and feasibility of the proposed method.

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