Optimized design of fractional-order PID controllers for autonomous underwater vehicle using genetic algorithm

Efficient control schemes of Autonomous underwater vehicle (AUV) are challenging due to uncertainties and highly nonlinearities. In this paper, improved fractional order PID controller is proposed for the control of AUV motion with six degrees of freedom (DOF). Genetic algorithm and Particle Swarm Optimization (PSO) are employed to find suboptimal coefficients of FOPID controller to improve performance of the AUV motion. These optimal adjusted coefficients of FOPID controllers minimize the step response characteristics such as maximum deviation and settling time. Simulation results are presented to verify the advantages of the FOPID with respect to the previous works specially proportional-integral-derivative controller (PID).