Deep Reinforcement Learning-Based Adaptive Controller for Trajectory Tracking and Altitude Control of an Aerial Robot

This research study presents a new adaptive attitude and altitude controller for an aerial robot. The proposed controlling approach employs a reinforcement learning-based algorithm to actively estimate the controller parameters of the aerial robot. In dealing with highly nonlinear systems and parame...

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Detalles Bibliográficos

Autores principales:	Ali Barzegar, Deok-Jin Lee
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2022-05-01
Colección:	Applied Sciences
Materias:	RL robot control RL model predictive control reinforcement learning for vehicle control PID reinforcement learning RL adaptive PID reinforcement learning drone control
Acceso en línea:	https://www.mdpi.com/2076-3417/12/9/4764
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