Robust Control Method Based on μ-Synthesis Theory and Genetic Algorithm for Grid-Connected Inverter to Cope With Multiple Uncertainties Under Weak Grid

Abstract

In the renewable energy-based distributed power generation system (DPGS), the grid-connected inverter is the interface between the generation unit and the grid. Thus, the stable operation of the grid-connected inverter system is crucial. However, the stability of the grid-connected inverter system is often affected by many aspects simultaneously, such as uncertain grid impedance and control delay. To improve the robustness of the system with the multiple uncertainties, the $\mu $ -synthesis theory is adopted in this article. By intelligently constructing the weighting functions, the robustness, dynamic performance, and power quality of the grid-connected inverter system can be taken into account at the same time when designing the controller. Furthermore, to avoid the designed controller being too high to be realized in practice, this article proposes to use a third-order controller, which is optimally designed by engaging the genetic algorithm (GA). Finally, a prototype is fabricated and tested. The experimental results verify the theoretical analysis and merits of the controller designed by the proposed method compared to the controller designed by the traditional method.