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

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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Bibliographic Details
Main Authors: Ali Barzegar, Deok-Jin Lee
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Applied Sciences
Subjects:
RL robot control
RL model predictive control
reinforcement learning for vehicle control
PID reinforcement learning
RL adaptive PID
reinforcement learning drone control
Online Access:https://www.mdpi.com/2076-3417/12/9/4764

Internet

https://www.mdpi.com/2076-3417/12/9/4764

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