Current-Sensorless Finite-Set Model Predictive Control for LC-Filtered Voltage Source Inverters

Abstract

A typical finite-set model predictive control (FS-MPC) scheme for LC-filtered voltage source inverters (VSIs) requires measurements of capacitor voltage and inductor current as well as load current measurement or estimation, which increases the system complexity and cost. To reduce the number of sensors in typical FS-MPC, this paper proposes a new current-sensorless FS-MPC scheme for LC-filtered VSIs. First, based on the inner relationship of the predictive matrices, the predictive model is exactly simplified with the capacitor voltage and its current as the state variables, making it suitable for current-sensorless control. Then, to eliminate the current sensors for cost reduction and reliability enhancement, the dynamic model is reconstructed and an easily implemented capacitor current estimator is designed, which can achieve a comparable performance with typical FS-MPC scheme. Considering the inevitable control delay in digital implementation, the delay compensation is inherently obtained by using the proposed estimator. In addition, the proposed control scheme is flexible to various cost functions and can also reduce the computational cost. The feasibility of the presented control scheme under load variations and model mismatches are verified by the comparative simulation and experimental results with typical FS-MPC.