Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.6
4.4
Journals
Drones
Special Issues
Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles...
share announcement

Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles 2nd Edition

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: 30 April 2025 | Viewed by 3602

Special Issue Editors

Prof. Dr. Mou Chen

grade E-Mail Website
Guest Editor
Department of Automatic Control, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: control systems engineering; electrical engineering; aerospace engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Bin Jiang

E-Mail Website
Guest Editor
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: intelligent fault diagnosis; fault tolerant control; helicopters; satellites; high-speed trains
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Youmin Zhang

E-Mail Website
Guest Editor
Department of Mechanical, Industrial and Aerospace Engineering, Concordia Institute of Aerospace Design and Innovation, Concordia University, Montreal, QC H3G 1M8, Canada
Interests: guidance, navigation, and control; fault detection and diagnosis; fault-tolerant control; remote sensing with applications to unmanned aerial/space/ground/marine vehicles; smart grids; smart cities; cyber-physical systems
Special Issues, Collections and Topics in MDPI journals
Dr. Zixuan Zheng

E-Mail Website
Guest Editor
School of Astronautics, Northwestern Polytechnical University, Xi’an 710129, China
Interests: intelligent decision-making; flight control; path planning
Special Issues, Collections and Topics in MDPI journals
Dr. Shuyi Shao

E-Mail Website
Guest Editor
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: intelligent control; flight control; path planning; discrete control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the extensive integration of unmanned aerial vehicles (UAVs) with intelligent computing and other information technologies, an intelligent unmanned system has evolved, integrating information perception, autonomous decision making, and dynamic control. Such a system will gradually replace manned aircraft in performing military and civil tasks in the complex environments of the future. To successfully accomplish these tasks, UAVs must have not only intelligent decision-making abilities so as to adapt to unknown environments but also good flight control performance in complex dynamic environments. Therefore, intelligent decision-making technologies and safe flight control schemes of UAVs in complex dynamic environments need to be fully considered in the future research on UAVs.

This journal focuses on the design and applications of drones, including research into control systems, artificial intelligence, mission planning, performance analysis, etc. This Special Issue on the “Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles” will cover a broad spectrum of topics related to advanced, intelligent decision making and flight control, focusing on new problems encountered in the research on UAVs.

Topics of interest for research papers include, but are not limited to, the following:

  • Artificial Intelligence
  • Unmanned System Command and Control
  • Guidance Law Design
  • Active Vibration Control
  • Neural/Fuzzy Control
  • Fault-Tolerant Control
  • Discrete Controller Design
  • Novel Disturbance Rejection Control
  • Adaptive Estimation and Control
  • Path Planning
  • Cooperative Control of UAVs
  • UAV Modeling and Simulation
  • Decision Making
  • Task Assignment
  • Health Management

Prof. Dr. Mou Chen
Prof. Dr. Bin Jiang
Prof. Dr. Youmin Zhang
Dr. Zixuan Zheng
Dr. Shuyi Shao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent decision-making
  • intelligent control
  • learning control
  • discrete control
  • fault-tolerant control
  • position/orientation control
  • disturbance observer
  • cooperative control
  • neural networks
  • adaptive control

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 5672 KiB  
Article
Online Safe Flight Control Method Based on Constraint Reinforcement Learning
by Jiawei Zhao, Haotian Xu, Zhaolei Wang and Tao Zhang
Drones 2024, 8(9), 429; https://doi.org/10.3390/drones8090429 - 26 Aug 2024
Viewed by 726
Abstract
UAVs are increasingly prominent in the competition for space due to their multiple characteristics, such as strong maneuverability, long flight distance, and high survivability. A new online safe flight control method based on constrained reinforcement learning is proposed for the intelligent safety control [...] Read more.
UAVs are increasingly prominent in the competition for space due to their multiple characteristics, such as strong maneuverability, long flight distance, and high survivability. A new online safe flight control method based on constrained reinforcement learning is proposed for the intelligent safety control of UAVs. This method adopts constrained policy optimization as the main reinforcement learning framework and develops a constrained policy optimization algorithm with extra safety budget, which introduces Lyapunov stability requirements and limits rudder deflection loss to ensure flight safety and improves the robustness of the controller. By efficiently interacting with the constructed simulation environment, a control law model for UAVs is trained. Subsequently, a condition-triggered meta-learning online learning method is used to adjust the control raw online ensuring successful attitude angle tracking. Simulation experimental results show that using online control laws to perform aircraft attitude angle control tasks has an overall score of 100 points. After introducing online learning, the adaptability of attitude control to comprehensive errors such as aerodynamic parameters and wind improved by 21% compared to offline learning. The control law can be learned online to adjust the control policy of UAVs, ensuring their safety and stability during flight. Full article
(This article belongs to the Special Issue Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles 2nd Edition)
►▼ Show Figures

Figure 1

10 pages, 2528 KiB  
Article
Event-Triggered Collaborative Fault Diagnosis for UAV–UGV Systems
by Runze Li, Bin Jiang, Yan Zong, Ningyun Lu and Li Guo
Drones 2024, 8(7), 324; https://doi.org/10.3390/drones8070324 - 13 Jul 2024
Viewed by 1073
Abstract
The heterogeneous unmanned system, which is composed of unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV), has been broadly applied in many domains. Collaborative fault diagnosis (CFD) among UAVs and UGVs has become a key technology in these unmanned systems. However, collaborative [...] Read more.
The heterogeneous unmanned system, which is composed of unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV), has been broadly applied in many domains. Collaborative fault diagnosis (CFD) among UAVs and UGVs has become a key technology in these unmanned systems. However, collaborative fault diagnosis in unmanned systems faces the challenges of the dynamic environment and limited communication bandwidth. This paper proposes an event-triggered collaborative fault diagnosis framework for the UAV–UGV system. The framework aims to achieve autonomous fault monitoring and cooperative diagnosis among unmanned systems, thus enhancing system security and reliability. Firstly, we propose a fault trigger mechanism based on broad learning systems (BLS), which utilizes sensor data to accurately detect and identify faults. Then, under the dynamic event triggering mechanism, the network communication topology between the UAV–UGV system and BLS is used to achieve cooperative fault diagnosis. To validate the effectiveness of our proposed scheme, we conduct experiments on a software-in-the-loop (SIL) simulation platform. The experimental results demonstrate that our method achieves high diagnosis accuracy for the UAV–UGV system. Full article
(This article belongs to the Special Issue Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles 2nd Edition)
►▼ Show Figures

Figure 1

30 pages, 16574 KiB  
Article
Dynamics Event-Triggered-Based Time-Varying Bearing Formation Control for UAVs
by Can Ding, Zhe Zhang and Jing Zhang
Drones 2024, 8(5), 185; https://doi.org/10.3390/drones8050185 - 8 May 2024
Cited by 1 | Viewed by 1077
Abstract
This article addresses the leader-follower formation maneuver control problem of multiple unmanned aerial vehicles (UAVs), taking into account the time-varying velocity and time-varying relative bearing. An event-triggered bearing-based distributed velocity observer was designed, using only the desired position and velocity of the leaders. [...] Read more.
This article addresses the leader-follower formation maneuver control problem of multiple unmanned aerial vehicles (UAVs), taking into account the time-varying velocity and time-varying relative bearing. An event-triggered bearing-based distributed velocity observer was designed, using only the desired position and velocity of the leaders. Furthermore, a dynamic event-triggered mechanism was introduced to reduce continuous communication between UAVs, thus effectively saving communication bandwidth and resources. Building on this, a bearing-only formation maneuver control strategy was proposed, integrating the event-triggered velocity observer with the backstepping control approach. To conclude, numerical simulations have been conducted to confirm the effectiveness of the proposed scheme in accomplishing formation maneuver control objectives, including translation, scaling, and rotation control. Furthermore, the advantages of the dynamic event-triggering strategy have been demonstrated through comparative simulations with traditional event-triggering strategies. Additionally, the effectiveness of the proposed observer and controller has been demonstrated by a comprehensive hardware-in-the-loop (HITL) simulation example. Full article
(This article belongs to the Special Issue Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles 2nd Edition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop