IET Control Theory and Applications · 2023 · 10 citations · 25 references
EngineeringAerospace EngineeringRobotics EngineeringAerial RoboticsRobot ControlRoboticsAdaptive ControlAircraft ControlPolicy LearningQuadrotor DynamicsReinforcement LearningAutonomous Flight ControlLyapunov ControlLyapunov FunctionsLyapunov StabilityLyapunov-based LearningRobust Reinforcement LearningUnmanned Aerial Vehicle Control
Abstract The control of unmanned aerial vehicle quadrotor is challenging because of non‐linearities, coupling and disturbance. Here, a novel control method which includes reinforcement learning (RL) component and robust component is proposed. In this method, the RL component only relies on collected data instead of modelling to handle coupling and disturbance from aerodynamics and model. To ensure safety during training and improve training speed, the robust component is used to reduce the disturbance .The stability of the system with our controller is proven by Lyapunov method. The results of the simulation exhibit advanced performance of our controller.
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