An intelligent drone testbed for control systems and verification
Abstract This research develops a drone testbed that enables the rapid development, validation, and qualification of novel spacecraft and drone control algorithms, control hardware, and remote sensing technologies. The drone testbed facilitates advanced navigation and control research by emulating a multitude of dynamic environments, which provides an easily accessible framework for using new technologies in industrial applications. This research introduces an intelligent system identification method to determine the dynamics and aerodynamic parameters of the drone using Particle Swarm Optimization (PSO), a metaheuristic algorithm. This method provides the knowledge of the system's dynamics that is needed for the environment emulation.
drone, control, feed-forward, system identification, particle swarm optimization, PSO, intelligent, testbed, verification, aviation, metaheuristic, space