Slime Mould Optimization-Based Integral-LQR Control for Grid Following Inverters

Efficient control of grid following inverters (GFIs) is crucial for seamless integration of distributed energy resources (DERs) with the existing grid infrastructure. This paper proposes an Integral-Linear Quadratic Regulator (LQR) control optimized using the Slime Mould Optimization (SMO) algorithm for GFI control. The LQR enhances transient response and disturbance rejection, while integral control ensures steady-state accuracy. SMO efficiently tunes LQR weight matrices, improving system robustness and reducing steady-state error. Simulation results validate the proposed approach, demonstrating superior dynamic performance and enhanced robustness compared to conventional methods. This study lays the foundation for advanced and optimal control of inverters, enabling seamless integration of DERs with existing utility grid thereby paving the way for sustainable energy integration.