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Drones
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A UAV Platform for Flight Dynamics and Control System
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A UAV Platform for Flight Dynamics and Control System

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".

Deadline for manuscript submissions: closed (15 January 2024) | Viewed by 32392

Special Issue Editors

Prof. Dr. Zhaokui Wang

E-Mail Website
Guest Editor
School of Aerospace Engineering, Tsinghua University, Haidian, Beijing 100084, China
Interests: distributed space systems; space system engineering; space intelligence; multi-agent control of spacecraft
Dr. Xiumin Diao

E-Mail Website
Guest Editor
School of Engineering Technology, Purdue Polytechnic Institute, Purdue University, Knoy Hall of Technology, Room 105, 401 N. Grant Street, West Lafayette, IN 47907-2021, USA
Interests: robotic system design, analysis, and control; artificial intelligence and human–robot interaction
Dr. Lin Zhang

E-Mail Website
Guest Editor
Department of Physics & Astronomy, University of Central Arkansas, Conway, AR 72035, USA
Interests: deep reinforcement learning; convolutional neural networks; variational autoencoders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit manuscripts to the MDPI Drones Special Issue entitled “A UAV Platform for Flight Dynamics and Control System”.

There is a wide range of applications based on UAV platforms for flight dynamics and control systems, leading to more flexible and efficient mission modes. Typically, flight dynamics and control systems are the basis for UAV platforms or swarms to perform tasks.

This Special Issue is aims to collect and review papers presenting any problems encountered and solved during the use of UAV platforms for flight dynamics and control systems: 1) studying the UAV platform flight dynamics and control system for different applications; 2) providing UAV platforms for flight dynamics and control approaches based on multi-agent intelligent control; 3) providing new methods for data analysis, highlighting their strengths and weaknesses; 4) intelligent control of UAV platforms with computer vision payload; and 5) other original miscellaneous approaches. Generally, only papers concerning the successful application of a methodology in its final version will be published. However, papers devoted to problem analysis will also be welcome in this Special Issue if they are of interest to researchers and practitioners. Contributions describing new methods for improving task efficiency and reducing cost are particularly encouraged.

Any type of application of interest for research and practice is welcome under the condition that it is based on the UAV platform’s flight dynamics and control system. The areas of interest for the applications can vary from architectural to environmental, volcanic, geological, civil engineering and agricultural fields, including, for example, autonomous tracking and rescue based on UAV platforms.

Prof. Dr. Zhaokui Wang
Dr. Xiumin Diao
Dr. Lin Zhang
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

  • UAV platform
  • flight dynamics and control
  • UAV swarms control
  • intelligent control approaches for UAV

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Published Papers (9 papers)

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Research

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25 pages, 5181 KiB  
Article
Optimization-Based Control for a Large-Scale Electrical Vertical Take-Off and Landing during an Aircraft’s Vertical Take-Off and Landing Phase with Variable-Pitch Propellers
by Luyuhang Duan, Yunhan He, Li Fan, Wei Qiu, Guangwei Wen and Yun Xu
Drones 2024, 8(4), 121; https://doi.org/10.3390/drones8040121 - 26 Mar 2024
Cited by 1 | Viewed by 1788
Abstract
The UAV industry has witnessed an unprecedented boom in recent years. Among various kinds of UAV platforms, the vertical take-off and landing (VTOL) aircraft with fixed-wing configurations has received more and more attention due to its flexibility and long-distance flying abilities. However, due [...] Read more.
The UAV industry has witnessed an unprecedented boom in recent years. Among various kinds of UAV platforms, the vertical take-off and landing (VTOL) aircraft with fixed-wing configurations has received more and more attention due to its flexibility and long-distance flying abilities. However, due to the fact that the advance ratio of regular propeller systems during the cruise phase is significantly higher than that during the VTOL phase, a variable-pitch propeller system is proposed and designed which can be applied without additional propulsion mechanisms during both flying stages. Thus, a VTOL aircraft platform is proposed based on the propulsion system constructed of variable-pitch propellers, and appropriate control manners are precisely analyzed, especially during its VTOL phase. As a basic propulsion system, a nonlinear model for variable-pitch propellers is constructed, and an optimization-based control allocation module is developed because of its multi-solution and high-order characteristics. Finally, the objective function is designed according to the stability and energy consumption requirements. Simulation experiments demonstrate that the proposed controller is able to lower energy consumption and maintain the stability of the aircraft while tracking aggressive trajectories for large-scale VTOLs with noises at the same time. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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22 pages, 10049 KiB  
Article
Design, Modeling, and Control of a Composite Tilt-Rotor Unmanned Aerial Vehicle
by Zhuang Liang, Li Fan, Guangwei Wen and Zhixiong Xu
Drones 2024, 8(3), 102; https://doi.org/10.3390/drones8030102 - 16 Mar 2024
Cited by 1 | Viewed by 3801
Abstract
Tilt-rotor unmanned aerial vehicles combine the advantages of multirotor and fixed-wing aircraft, offering features like rapid takeoff and landing, extended endurance, and wide flight conditions. This article provides a summary of the design, modeling, and control of a composite tilt-rotor. During modeling process, [...] Read more.
Tilt-rotor unmanned aerial vehicles combine the advantages of multirotor and fixed-wing aircraft, offering features like rapid takeoff and landing, extended endurance, and wide flight conditions. This article provides a summary of the design, modeling, and control of a composite tilt-rotor. During modeling process, aerodynamic modeling was performed on the tilting and non-tilting parts based on the subcomponent modeling method, and CFD simulation analysis was conducted on the entire unmanned aerial vehicle to obtain its accurate aerodynamic characteristics. In the process of modeling the motor propeller, the reduction of motor thrust and torque due to forward flow and tilt angle velocity is thoroughly examined, which is usually ignored in most tilt UAV propeller models. In the controller design, this paper proposes a fusion ADRC control strategy suitable for vertical takeoff and landing of this type of tiltrotor. The control system framework is built using Simulink, and the control algorithm’s efficiency has been verified through simulation testing. Through the proposed control scheme, it is possible for the composite tiltrotor unmanned aerial vehicle to smoothly transition between multirotor and fixed-wing flight modes. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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30 pages, 3867 KiB  
Article
Distributed Dynamic Surface Control for a Class of Quadrotor UAVs with Input Saturation and External Disturbance
by Guoqiang Zhu, Laiping Lv, Lingfang Sun and Xiuyu Zhang
Drones 2024, 8(3), 77; https://doi.org/10.3390/drones8030077 - 23 Feb 2024
Cited by 2 | Viewed by 1531
Abstract
An adaptive dynamic surface trajectory tracking control method based on the Nussbaum function is proposed for a class of quadrotor UAVs encountering unknown external disturbances and unidentified nonlinearities. By transforming controller expressions into numerical solutions, the challenge of overly complex controller design expressions [...] Read more.
An adaptive dynamic surface trajectory tracking control method based on the Nussbaum function is proposed for a class of quadrotor UAVs encountering unknown external disturbances and unidentified nonlinearities. By transforming controller expressions into numerical solutions, the challenge of overly complex controller design expressions is addressed, simplifying the overall controller design process and enhancing the efficiency of simulation programs. Additionally, an adaptive controller based on Nussbaum gain is introduced to effectively resolve actuator saturation issues. This approach mitigates complexities associated with traditional control design and ensures smooth operation of the quadrotor UAVs. The proposed methodology offers promising prospects for enhancing the robustness and performance of quadrotor UAVs under uncertain operating conditions. Finally, to validate the effectiveness of the proposed control scheme, a hardware-in-the-loop experimental setup is constructed. The dynamic model of the quadrotor UAVs and the proposed controller scheme are implemented on the Rapid Control Prototype (RCP) and Real-Time Simulator (RTS), respectively. This facilitates a semi-physical simulation experiment, providing a basis for the subsequent application of the control scheme to actual aerial vehicles. The concluding experimental results affirm the effectiveness of the proposed control scheme and highlight its potential for practical applications. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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22 pages, 37144 KiB  
Article
Modular Reinforcement Learning for Autonomous UAV Flight Control
by Jongkwan Choi, Hyeon Min Kim, Ha Jun Hwang, Yong-Duk Kim and Chang Ouk Kim
Drones 2023, 7(7), 418; https://doi.org/10.3390/drones7070418 - 23 Jun 2023
Cited by 5 | Viewed by 3351
Abstract
Recently, research on unmanned aerial vehicles (UAVs) has increased significantly. UAVs do not require pilots for operation, and UAVs must possess autonomous flight capabilities to ensure that they can be controlled without a human pilot on the ground. Previous studies have mainly focused [...] Read more.
Recently, research on unmanned aerial vehicles (UAVs) has increased significantly. UAVs do not require pilots for operation, and UAVs must possess autonomous flight capabilities to ensure that they can be controlled without a human pilot on the ground. Previous studies have mainly focused on rule-based methods, which require specialized personnel to create rules. Reinforcement learning has been applied to research on UAV autonomous flight; however, it does not include six-degree-of-freedom (6-DOF) environments and lacks realistic application, resulting in difficulties in performing complex tasks. This study proposes a method of efficient learning by connecting two different maneuvering methods using modular learning for autonomous UAV flights. The proposed method divides complex tasks into simpler tasks, learns them individually, and then connects them in order to achieve faster learning by transferring information from one module to another. Additionally, the curriculum learning concept was applied, and the difficulty level of individual tasks was gradually increased, which strengthened the learning stability. In conclusion, modular learning and curriculum learning methods were used to demonstrate that UAVs can effectively perform complex tasks in a realistic, 6-DOF environment. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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41 pages, 3623 KiB  
Article
Sliding Mode Controller with Disturbance Observer for Quadcopters; Experiments with Dynamic Disturbances and in Turbulent Indoor Space
by Yutao Jing, Adam Mirza, Rifat Sipahi and Jose Martinez-Lorenzo
Drones 2023, 7(5), 328; https://doi.org/10.3390/drones7050328 - 20 May 2023
Cited by 2 | Viewed by 2666
Abstract
In this study, a sliding mode surface controller (SMC) designed for a quadcopter is experimentally tested. The SMC was combined with disturbance observers in six degrees of freedom of the quadcopter to effectively reject external disturbances. While respecting stability conditions all control parameters [...] Read more.
In this study, a sliding mode surface controller (SMC) designed for a quadcopter is experimentally tested. The SMC was combined with disturbance observers in six degrees of freedom of the quadcopter to effectively reject external disturbances. While respecting stability conditions all control parameters were automatically initialized and tuned using a simulation-based offline particle swarm optimization (PSO) algorithm, followed by onboard manual fine-tuning. To demonstrate its superiority, the SMC was compared with a PSO-optimized PID controller in terms of agility, stability, and the accurate tracking of hover, rectangular, and figure-eight pattern trajectories. To evaluate its robustness, the SMC controller was extensively tested in a small, enclosed, turbulent space while being subjected to a series of external disturbances, such as hanging payloads and lateral wind. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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25 pages, 13838 KiB  
Article
A UAV Formation Control Method Based on Sliding-Mode Control under Communication Constraints
by Qijie Chen, Taoyu Wang, Yuqiang Jin, Yao Wang and Bei Qian
Drones 2023, 7(4), 231; https://doi.org/10.3390/drones7040231 - 27 Mar 2023
Cited by 5 | Viewed by 1932
Abstract
The problem of vision-based fixed-wing UAV formation control under communication limitations and the presence of measurement errors was investigated. In the first part of this paper, the single UAV motion model and the process of estimating the neighboring UAV states using the Extended [...] Read more.
The problem of vision-based fixed-wing UAV formation control under communication limitations and the presence of measurement errors was investigated. In the first part of this paper, the single UAV motion model and the process of estimating the neighboring UAV states using the Extended Kalman Filter are introduced. The second part describes how we designed a sliding mode controller considering the sensor measurement errors and discusses the sufficient conditions for the stability and formation system in the presence of state transfer time delays in the formation. The main motivation of this paper was to develop a hierarchical, globally stable sliding mode controller that could enable the considered vision-based multiple fixed-wing UAVs to achieve and maintain formation in the presence of measurement errors. To this end, the selected problem was first transformed into a state-tracking problem for UAVs in the neighborhood, and then the stability criterion was established using the Lyapunov stability theory. Finally, the effectiveness of the proposed control method was illustrated using three numerical arithmetic examples. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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26 pages, 22508 KiB  
Article
Multi-UAV Cooperative Trajectory Planning Based on FDS-ADEA in Complex Environments
by Gang Huang, Min Hu, Xueying Yang and Peng Lin
Drones 2023, 7(1), 55; https://doi.org/10.3390/drones7010055 - 12 Jan 2023
Cited by 9 | Viewed by 2263
Abstract
Multi-UAV cooperative trajectory planning (MUCTP) refers to the planning of multiple flyable trajectories based on the location of each UAV and mission point in a complex environment. In the planning process, the complex 3D space structure increases the difficulty of solving the trajectory [...] Read more.
Multi-UAV cooperative trajectory planning (MUCTP) refers to the planning of multiple flyable trajectories based on the location of each UAV and mission point in a complex environment. In the planning process, the complex 3D space structure increases the difficulty of solving the trajectory points, and the mutual constraints of the UAV cooperative constraints can degrade the performance of the planning system. Therefore, to improve the efficiency of MUCTP, this study proposes MUCTP based on feasible domain space and adaptive differential evolution algorithm (FDS-ADEA). The method first constructs a three-dimensional feasible domain space to reduce the complexity of the search space structure; then, the constraints of heterogeneous UAVs are linearly weighted and transformed into a new objective function, and the information of the fitness value is shared in accordance with the adaptive method and the code correction method to improve the search efficiency of the algorithm; finally, the trajectories are smoothed to ensure the flyability of the UAVs performing the mission by combining the cubic B-spline curves. Experiments 1, 2, 3, and 4 validate the proposed algorithm. Simulation results verify that FDS-ADEA has fast convergence, high cooperative capability, and more reasonable planned trajectory sets when processing MUCTP. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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26 pages, 15184 KiB  
Article
Autonomous Tracking of ShenZhou Reentry Capsules Based on Heterogeneous UAV Swarms
by Boxin Li, Boyang Liu, Dapeng Han and Zhaokui Wang
Drones 2023, 7(1), 20; https://doi.org/10.3390/drones7010020 - 27 Dec 2022
Cited by 3 | Viewed by 2757
Abstract
The safe landing and rapid recovery of the reentry capsules are very important to manned spacecraft missions. A variety of uncertain factors, such as flight control accuracy and wind speed, lead to a low orbit prediction accuracy and a large landing range of [...] Read more.
The safe landing and rapid recovery of the reentry capsules are very important to manned spacecraft missions. A variety of uncertain factors, such as flight control accuracy and wind speed, lead to a low orbit prediction accuracy and a large landing range of reentry capsules. It is necessary to realize the autonomous tracking and continuous video observation of the reentry capsule during the low-altitude phase. Aiming at the Shenzhou return capsule landing mission, the paper proposes a new approach for the autonomous tracking of Shenzhou reentry capsules based on video detection and heterogeneous UAV swarms. A multi-scale video target detection algorithm based on deep learning is developed to recognize the reentry capsules and obtain positioning data. A self-organizing control method based on virtual potential field is proposed to realize the cooperative flight of UAV swarms. A hardware-in-the-loop simulation system is established to verify the method. The results show that the reentry capsule can be detected in four different states, and the detection accuracy rate of the capsule with parachute is 99.5%. The UAV swarm effectively achieved autonomous tracking for the Shenzhou reentry capsule based on the position obtained by video detection. This is of great significance in the real-time searching of reentry capsules and the guaranteeing of astronauts’ safety. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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Review

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35 pages, 6092 KiB  
Review
Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion
by Pengfei Tong, Xuerong Yang, Yajun Yang, Wei Liu and Peiyi Wu
Drones 2023, 7(4), 261; https://doi.org/10.3390/drones7040261 - 11 Apr 2023
Cited by 25 | Viewed by 9570
Abstract
The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, [...] Read more.
The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, disaster monitoring, and sports event broadcasting, among many other disciplines. Some applications have stricter requirements for the autonomous positioning capability of UAV clusters, requiring its positioning precision to be within the cognitive range of a human or machine. Global Navigation Satellite System (GNSS) is currently the only method that can be applied directly and consistently to UAV positioning. Even with dependable GNSS, large-scale clustering of drones might fail, resulting in drone cluster bombardment. As a type of passive sensor, the visual sensor has a compact size, a low cost, a wealth of information, strong positional autonomy and reliability, and high positioning accuracy. This automated navigation technology is ideal for drone swarms. The application of vision sensors in the collaborative task of multiple UAVs can effectively avoid navigation interruption or precision deficiency caused by factors such as field-of-view obstruction or flight height limitation of a single UAV sensor and achieve large-area group positioning and navigation in complex environments. This paper examines collaborative visual positioning among multiple UAVs (UAV autonomous positioning and navigation, distributed collaborative measurement fusion under cluster dynamic topology, and group navigation based on active behavior control and distributed fusion of multi-source dynamic sensing information). Current research constraints are compared and appraised, and the most pressing issues to be addressed in the future are anticipated and researched. Through analysis and discussion, it has been concluded that the integrated employment of the aforementioned methodologies aids in enhancing the cooperative positioning and navigation capabilities of multiple UAVs during GNSS denial. Full article
(This article belongs to the Special Issue A UAV Platform for Flight Dynamics and Control System)
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