Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

This article introduces a novel robust reinforcement learning (RL) control scheme for a quadrotor unmanned aerial vehicle (QUAV) under external disturbances and model uncertainties. First, the translational and rotational motions of the QUAV are decoupled and trained separately to mitigate the compu...

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Bibliographic Details
Main Authors: Yu Cai, Yefeng Yang, Tao Huang, Boyang Li
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:Advanced Intelligent Systems
Subjects:
proximal policy optimization
quadrotor unmanned aerial vehicles
reinforcement learning control
robust compensations
Online Access:https://doi.org/10.1002/aisy.202400427
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