Output feedback fuzzy model predictive control applied to 3ssc boost converter

The recent advance in the computational capacity of microprocessors has triggered an expansion of research and various applications of advanced control techniques. Considering this scenario, Model Predictive Control (MPC) and fuzzy control approaches gain prominence and popularity due to their attractive characteristics. These methods are capable of treating systems with con- straints, uncertainties in the model, non-linearities and external disturbances. Thus, considering the good attributes of these control methods, the objective of this work is to propose and analyze a control law which merge the characteristics of MPC and fuzzy control. The proposed method consists of an output fuzzy model predictive control (FMPC), in addition a Takagi-Sugeno (TS) fuzzy model and the Parallel-Distributed Compensation (PDC) method is used to define the con- trol law. In order to analyze the performance of the controller, two applications are run through computer simulation. First, the FMPC controller with output feedback is applied to a numerical example and then to a boost converter. Furthermore, the analysis is performed for the online and offline methodologies, with the online approach being compared with output feedback MPC found in the literature. The controllers are evaluated in terms of time response, pole allocation, performance indices and stability ellipsoids. For both applications the obtained results showed that the proposed controller solves the control problems efficiently, guaranteeing the stability and performance of the system even in the face of limiting situations such as: non-linearities, change in the operation point, input constraint and non-minimum phase