Tuning of PID Controller Based on Tasmanian Devil Optimization for Unmanned Vehicles

This paper addresses the problem of disturbances experienced by unmanned aerial vehicles and unmanned underwater vehicles. It aims to achieve speed tracking and disturbance rejection using an efficient control method. To manage speed under various disturbance conditions, a novel metaheuristic bio-inspired algorithm known as Tasmanian Devil Optimization (TDO) is used to optimize the parameters of the Proportional Integral Derivative (PID) controller. The performance of TDO is compared to that of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). According to the simulation results obtained using MATLAB/Simulink, the TDO outperforms the PSO and ACO in terms of the characteristics of speed response.