LQG Controller in Cascade Loop Tuned by PSO Applied to a DC–DC Converter

This work presents a Linear Quadratic Gaussian (LQG) controller in cascade loop applied to a Two‐Switch Forward Converter (2SFC). This arrange is suitable for low power battery chargers and provides both performance for reference tracking and disturbance rejection. Once the weighting matrices of the LQG have several parameters to be selected, they are here adjusted by Particle Swarm Optimization (PSO), in a strategy called LQG‐PSO. This allows working intuitively with complex characteristics, such as noise, uncertainties and saturation, just by inserting them into the simulation used for PSO. Since this algorithm is a metaheuristic, this work shows a convergence analysis of PSO for this LQG‐problem. The obtained solutions from different trials resulted in LQG gains contained in a well‐defined region, suggesting that optimality was reached. Simulation results have also shown good dynamic behavior with LQG‐PSO strategy, which has outperformed a cascade PI controller for different scenarios. Experimental results comparing the LQG‐PSO and PI controllers applied to the 2SFC confirmed that LQG‐PSO provided superior performance.