The aim of this paper is to design a nonlinear model predictive control for DC-DC buck converters to track constant reference signals with zero steady-state error. The online trained neural network (NN) model is employed as the predictor and the steady-state error, which is called the offset, is studied in the presence of the changes in system parameters and the external disturbances. The stability of the closed-loop system is investigated using the Lyapunov direct theory. The proposed method can provide offset-free behavior in the presence of constant disturbances. For rejecting nonconstant disturbances, a nonlinear disturbance observer based on the NN inverse model is proposed. Due to wide applications of the DC-DC converter in power electronics, control of its output voltage is considered in this paper. The effectiveness of the proposed control method is demonstrated by experimental results.
VATANKHAH, BAHAREH and FARROKHI, MOHAMMAD
"Offset-free adaptive nonlinear model predictive control with disturbance observer for DC-DC buck converters,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25:
3, Article 47.
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss3/47