PSO Optimal Tracking Control for a DC-AC Power Converter

This contribution presents an infinite-horizon optimal tracking controller for nonlinear systems based on the state-dependent Riccati equation approach. The synthesized optimal control law comes from solving the Hamilton-Jacobi-Bellman equation for state-dependent coefficient factorized nonlinear systems. The proposed controller results in a state feedback optimal control law, which minimizes a quadratic performance index, whose entries are determined by the particle swarm optimization (PSO) algorithm in order to improve the performance of the control system by fulfilling with design specifications such as bound of the control input expenditure and steady-state tracking error. The effectiveness of the proposed PSO optimal tracking controller is applied via simulation for a DCAC converter.