A Twin-Delayed Deep Deterministic Policy Gradient Approach for UAV Formation Control-Reference-Cited by-同舟云学术

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A Twin-Delayed Deep Deterministic Policy Gradient Approach for UAV Formation Control

Published:2024-07-10 Issue: Volume: Page:2393-2398
ISSN:
Container-title:2024 American Control Conference (ACC)
language:
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Author:

Zhang Yintao¹,Zhang Youmin¹,Yu Ziquan²,Li Jin¹,Qin Qiaomeng¹,Gao Chenxi³

Affiliation:

1. Concordia University,Department of Mechanical, Industrial and Aerospace Engineering,Montreal,Canada

2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing,China

3. University of Liverpool,Fac of Science & Engineering,Liverpool,United Kingdom

Funder

Natural Sciences and Engineering Research Council of Canada

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province of China

Industry-University Research Innovation Foundation for the Chinese Ministry of Education

Aeronautical Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10644130/10644150/10644770.pdf?arnumber=10644770

Reference11 articles.

1. Composite Adaptive Disturbance Observer-Based Decentralized Fractional-Order Fault-Tolerant Control of Networked UAVs

2. Fractional-Order Adaptive Fault-Tolerant Synchronization Tracking Control of Networked Fixed-Wing UAVs Against Actuator-Sensor Faults via Intelligent Learning Mechanism

3. Time-Varying Formation Control for Unmanned Aerial Vehicles: Theories and Applications

4. Path Following Control for UAV Using Deep Reinforcement Learning Approach

5. A Simple Scheme for Formation Control Based on Weighted Behavior Learning

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