Robust Fuzzy Predictive Control of DC-DC Buck-Boost Converter

This study investigates the problem of model predictive control (MPC) for the voltage tracking control of a DC-DC Buck-Boost converter. The system is represented into a Takagi-Sugeno (T-S) discrete fuzzy model. Based on the Lyapunov functions theory, some required sufficient conditions are established in terms of linear-matrix inequalities (LMIs), which can be easily solved by an efficient convex optimization algorithm. The provided conditions are obtained through a fuzzy Lyapunov function candidate and a non-PDC control law, to maintain a robust performance against load variation of a buck-boost DC-DC power converter system. The results obtained are compared with the ones achieved with Fuzzy model predictive control (MPC) in terms of robustness to disturbances.