A hybrid firefly algorithm for optimizing fractional proportional-integral-derivative controller in ship steering

In this paper, a new algorithm which integrates the powerful firefly algorithm (FA) and the ant colony optimization (ACO) has been used in tracking control of ship steering for optimization of fractional-order proportional-integral-derivative (FOPID) controller gains. Particle swarm optimization (PSO) algorithm is also used to optimize FOPID controllers, and their performances are compared. It is found that FA optimized FOPID controller gives better performance than others. Sensitivity analysis has been carried out to see the robustness of optimum FOPID gains obtained at nominal conditions to wide changes in system parameters, and the optimum FOPID gains need not be reset for wide changes in system parameters.