Boost converter optimal control based on MFAC and FPSOA under model mismatch

An optimal control of boost converter based on model-free adaptive controller (MFAC) and fuzzy particle swarm optimization algorithm (FPSOA) is proposed to realize a better response performance and robustness under model mismatch and the parameter time variation. The data-based MFAC is investigated to design the boost converter, which avoids the precise modeling and greatly reduces the influence of model mismatch. Additionally, the FPSOA is used for online optimization of the controller parameters to improve the response performance and robustness. Comparing with the traditional optimal control methods of boost converter, the proposed method avoids the contradiction of establishing accurate model and complex systems design. It inhibits the influences of the parameter time variation and model mismatch, and has a better dynamic and static performance. Finally, the test is implemented on a semi-physical simulation platform for power electronic control systems. The comparison of MFAC and classic state feedback exact linearization control in various model mismatch situations are used to show the effectiveness of the obtained results.