Local Model Predictive Control for T–S Fuzzy Systems
针对Takagi-Sugeno模糊系统描述的离散时间非线性系统，提出一种基于线性矩阵不等式的模型预测控制方法，通过局部稳定性分析提升性能，并证明吸引域估计和可行性。
In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, and feasibility of the proposed MPC are proved. Examples are given to demonstrate the advantages of the suggested MPC over existing approaches.