Model Predictive Control of DC-DC Buck-Boost Converter with Various Resistive Load Values

Direct current (DC-DC) converters are the most popular devices for power supply circuits. The pulse width modulation has significant influences on their operations to manage their output power. Control theory is required to be applied to these converters to govern their inherent nonlinearity and non-minimum phase behaviors to maximize their efficiency and effectiveness. This research studies theory of a constrained Model Predictive Controller (MPC) applied to a DC-DC Buck-Boost converter with various values of a resistive load. The Quadratic Programming (QP) optimization algorithm subjected to unequal input constraint solved to predict the input control signal at every sampling time interval. This approach can be implemented at a faster time with robust and stability. MATLAB, Simulink, and the optimization process were used to achieve this goal.

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