LAUSR

This study presents a new approach to modeling and control the current-fed Dickson voltage multiplier (CF-DVM). The capacitor voltage relation and the input current are obtained. As all switching intervals are considered in detail, a highly accurate dynamic model is obtained, which can be easily extended for a CF-DVM with an arbitrary number of stages. Using the precise extracted model, the Takagi-Sugeno fuzzy model (TSFM) of the CF-DVM is provided, which is an exact equivalent representation of the CF-DVM nonlinear model. Then, a highly accurate and responsive model predictive controller (MPC) is designed based on an obtained TSFM of the CF-DVM to control the output voltage in an optimal and constrained manner. To obtain the control signal, the suggested optimization problem is converted to a quadratic programming (QP)-based problem which has a low online computational burden. Moreover, the performance of the proposed MPC is compared with the PI controller and the linear MPC. Finally, the simulation and experimental results demonstrate the promising merits of the proposed model and control approaches.