Adaptive Model Predictive Control for DC-DC Power Converters With Parameters’ Uncertainties

This research investigates the Adaptive Model Predictive Controller (AMPC) and Linear Parameter-Varying (LPV) control system for a direct current (dc-dc) buck-boost converter, considering parameters’ uncertainty. The LPV model AMPC are explicitly constructed to perform robust design proposed dc-dc converter. was created out of set linearized systems at different operating conditions Time-Invariant (LTI) models. Due converter’s nonlinear characteristic, performed LTI models might have declination, which can perfectly address by adapting prediction changes in conditions. implemented simulation environment as well real-time on an Arduino Mega 2560 microcontroller test its robustness quality. works compared with some existing algorithms horizons. Also, comparison considers designed Gain Scheduling Proportional Integral (G.S-PI) regular (reg-MPC) Controllers were without using their performance against parameters uncertainties.