Salp Swarm Algorithm Based Fractional Order PID Controller Design for Trajectory Tracking Simulation of an Underactuated Underwater Vehicle Model

Autonomous Underwater Vehicles (AUVs) are used in many fields, primarily in scientific, commercial, and military areas. These vehicles require various guidance and control systems to autonomously perform tasks underwater. The modeling, system identification, and control of AUVs remain active areas of research and development. In this study, modelling and trajectory tracking simulation of a low-speed, modular, symmetrical and underactuated underwater vehicle with 4DOF are evaluated. The vehicle, named RedFin is developed in Kocaeli University Laboratories. Dynamical model parameters of the AUV's are estimated by Computational Fluid Dynamics (CFD) and analytical calculation techniques and the AUV mathematical model is obtained. Model validation was carried out through static and dynamic pool tests. control algorithm has been developed, offering more precise solutions. For dynamic models described by fractional differential equations, a Fractional Order PID (FOPID) control algorithm was developed, offering more precise solutions. In the study, a PID controller and a FOPID controller were designed for the trajectory tracking control of the AUV. The Salp Swarm Algorithm (SSA), one of the heuristic optimization algorithms, is used to optimize the gain parameters of both controllers. The integral of the absolute value of the position error (IAE) is selected as the fitness function. “Band Limited White Noise” with 0.5 W power and 200 Hz frequency was added to the system model control inputs. During the orbit tracking, the RMS values of depth control errors are very small, such as 0.021 m for SSA-PID, 0.0032 m for GA-KDPID, and 0.00118 m for SSA-KDPID.