An Improved Model Predictive Control for DC-DC Boost Converter

DC-DC boost converter acts as one of the common interfaces in renewable energy systems. Considering its non-linear characteristics, several nonlinear control methods have been adopted. Among them, the model predictive control (MPC) is widely used. However, the common finite-set (FCS)-MPC algorithm yields a variable switching frequency. Besides, a long prediction horizon MPC is needed for the boost converter to alleviate the non-minimum phase characteristics' influence, which leads to a high computational burden. To address these issues, this paper proposes an improved MPC algorithm to guarantee stable operation. The proposed algorithm transforms the original control variable which is the switching signal into the duty cycle to generate a fixed switching frequency. Besides, by changing the prediction model, the proposed MPC algorithm performs guaranteed stability with one prediction horizon. Moreover, a Jacobian matrix is utilized to assess the stability of the proposed algorithm by determining whether its eigenvalues are in the unit cycle. Simulations are provided to prove the effectiveness of the controller.