Receding Horizon Estimation and Model Predictive Control for Basic Power Module with High Performance

A receding horizon estimation (RHE) method is designed in combination with model predictive control (MPC) to improve the dynamic performance of LC-Based Power Module with low cost. Symmetrically mirrored to the MPC, the RHE is configured as a constrained finite time optimal estimation (CFTOE) problem to solve the quadratic cost function based on the past sampling information. An integrated RHE-MPC control method is designed for LC-based power module to formulate power conversion system with high performance. With the designed RHE, the sensor count is reduced with less noise. And the highly accurate RHE contributes to the correction of possible modeling parameters or sampling errors. The integration of RHE and MPC improves the steady state and dynamic performances with less noise, more robust behavior and higher control bandwidth. The proposed methods have been validated experimentally on the power module testbench.