Linear quadratic regulator based Takagi-Sugeno model for multivariable nonlinear processes

In this work, a fuzzy based linear quadratic regulator (FLC-LQR) is developed. The main aim is to obtain an improved performance of non-linear multivariable systems. In this work, the well known weighting parameters approach is applied to optimize local and global approximation and modelling capability of Takagi-Sugeno (T-S) fuzzy model. A multi-input multi-output (MIMO) thermal mixing process system is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of estimation approach and the proposed controller. The results obtained show a robust, smooth and well damped response using the proposed FLC-LQR of the system under study.