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Machines
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Dynamics and Control of UAVs
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Dynamics and Control of UAVs

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 6242

Special Issue Editors

Dr. Maria Eusebia Guerrero-Sanchez

E-Mail Website
Guest Editor
CONACYT/Tecnológico Nacional de México, IT, Hermosillo, Mexico
Interests: passivity-based control; under-actuated systems; nonlinear control; UAV control; control applications; nonlinear observers
Dr. Omar Hernández-González

E-Mail Website
Guest Editor
Conacyt-Tecnológico Nacional de México, Hermosillo, Mexico
Interests: control system synthesis; nonlinear control systems; delays; observers; time-varying systems; uncertain systems; Lyapunov methods; autonomous aerial vehicles

Special Issue Information

Dear Colleagues,

The use of unmanned aerial vehicles (UAVs) is significantly increasing to a wide range of useful tasks, such as recognition in open fields, communication, environmental monitoring, precision agriculture, transportation of packages, rescue operations, policing, professional photography, remote inspection, etc. These applications thus rely on modelling, control systems and design of control strategies for UAVs. Therefore, more studies of advanced control techniques and modeling are necessary in order to ensure that UAVs can navigate as required to carry out specific applications in a robust and reliable manner. In this context, we invite the submission of papers to this Special Issue, with a focus on new developments in modeling and advanced control techniques for UAVs and their applications.

We are soliciting high-quality original research papers on topics including but not limited to modeling and control algorithms, collision-free navigation and control, trajectory optimization, cooperative control, fault detection, nonlinear observers and applications in real fields.

Dr. Maria Eusebia Guerrero-Sanchez
Dr. Omar Hernández-González
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. Machines 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 2400 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 control systems
  • advanced flight-control algorithms
  • hybrid UAVs
  • cooperative control of multi-UAV systems
  • modeling, parameter estimation and optimization of UAVs
  • trajectory optimization for UAVs
  • path-planning problem for UAVs in complex environments
  • nonlinear observers of UAVs
  • fault detection for UAVs
  • applications of UAVs in real fields

Published Papers (4 papers)

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Research

31 pages, 24369 KiB  
Article
An Integrated YOLOv5 and Hierarchical Human-Weight-First Path Planning Approach for Efficient UAV Searching Systems
by Ing-Chau Chang, Chin-En Yen, Hao-Fu Chang, Yi-Wei Chen, Ming-Tsung Hsu, Wen-Fu Wang, Da-Yi Yang and Yu-Hsuan Hsieh
Machines 2024, 12(1), 65; https://doi.org/10.3390/machines12010065 - 16 Jan 2024
Viewed by 962
Abstract
Because the average number of missing people in our country is more than 20,000 per year, determining how to efficiently locate missing people is important. The traditional method of finding missing people involves deploying fixed cameras in some hotspots to capture images and [...] Read more.
Because the average number of missing people in our country is more than 20,000 per year, determining how to efficiently locate missing people is important. The traditional method of finding missing people involves deploying fixed cameras in some hotspots to capture images and using humans to identify targets from these images. However, in this approach, high costs are incurred in deploying sufficient cameras in order to avoid blind spots, and a great deal of time and human effort is wasted in identifying possible targets. Further, most AI-based search systems focus on how to improve the human body recognition model, without considering how to speed up the search in order to shorten the search time and improve search efficiency, which is the aim of this study. Hence, by exploiting the high-mobility characteristics of unmanned aerial vehicles (UAVs), this study proposes an integrated YOLOv5 and hierarchical human-weight-first (HWF) path planning framework to serve as an efficient UAV searching system, which works by dividing the whole searching process into two levels. At level one, a searching UAV is dispatched to a higher altitude to capture images, covering the whole search area. Then, the well-known artificial intelligence model YOLOv5 is used to identify all persons in the captured images and compute corresponding weighted scores for each block in the search area, according to the values of the identified human bodies, clothing types, and clothing colors. At level two, the UAV lowers its altitude to sequentially capture images for each block, in descending order according to its weighted score at level one, and it uses the YOLOv5 recognition model repeatedly until the search target is found. Two improved search algorithms, HWFR-S and HWFR-D, which incorporate the concept of the convenient visit threshold and weight difference, respectively, are further proposed to resolve the issue of the lengthy and redundant flight paths of HWF. The simulation results suggest that the HWF, HWFR-S, and HWFR-D search algorithms proposed in this study not only effectively reduce the length of a UAV’s search path and the number of search blocks but also decrease the search time required for a UAV to locate the search target, with a much higher search accuracy than the two traditional search algorithms. Moreover, this integrated YOLOv5 and HWF framework is implemented and tested in a real scenario to demonstrate its capability in enhancing the efficiency of a search and rescue operation. Full article
(This article belongs to the Special Issue Dynamics and Control of UAVs)
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14 pages, 8353 KiB  
Article
Trajectory Tracking Control of Quadrotor Based on Fractional-Order S-Plane Model
by Jiacheng Li, Pengyun Chen, Zhe Chang, Guobing Zhang, Luji Guo and Chenbo Zhao
Machines 2023, 11(7), 672; https://doi.org/10.3390/machines11070672 - 21 Jun 2023
Cited by 3 | Viewed by 1214
Abstract
Quadrotors possess traits such as under-actuation, nonlinearity, and strong coupling. Quaternions are primarily used for attitude calculations in drones, with error quaternions seldom being employed directly in the control of specific quadcopter drones. This paper focuses on the low tracking accuracy and weak [...] Read more.
Quadrotors possess traits such as under-actuation, nonlinearity, and strong coupling. Quaternions are primarily used for attitude calculations in drones, with error quaternions seldom being employed directly in the control of specific quadcopter drones. This paper focuses on the low tracking accuracy and weak anti-interference ability of quadcopter drones in trajectory-tracking control. By establishing the quadcopter quaternion model, a controller based on quaternion error is designed through a combination of fractional-order PID control with S-plane control. Trajectory-tracking experiments demonstrate that, in comparison with fractional-order PID, this method exhibits strong wind disturbance resistance and high tracking accuracy. Full article
(This article belongs to the Special Issue Dynamics and Control of UAVs)
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19 pages, 1207 KiB  
Article
Spherical Inverted Pendulum on a Quadrotor UAV: A Flatness and Discontinuous Extended State Observer Approach
by Adrian H. Martinez-Vasquez, Rafael Castro-Linares, Abraham Efraím Rodríguez-Mata and Hebertt Sira-Ramírez
Machines 2023, 11(6), 578; https://doi.org/10.3390/machines11060578 - 23 May 2023
Viewed by 1449
Abstract
This article addresses the problem of balancing an inverted spherical pendulum on a quadrotor. The full dynamic model is obtained via the Euler-Lagrange formalism, where the dynamics of the pendulum is coupled to the dynamics of the quadrotor, taking as control inputs the [...] Read more.
This article addresses the problem of balancing an inverted spherical pendulum on a quadrotor. The full dynamic model is obtained via the Euler-Lagrange formalism, where the dynamics of the pendulum is coupled to the dynamics of the quadrotor, taking as control inputs the torques associated with the yaw, roll, and pitch dynamics, and a control input for the vertical displacement in height. A trajectory tracking control scheme is proposed by means of an active disturbance rejection control based on a discontinuous extended state observer (ADRC-DESO) that allows controlling the system in the translational dynamics of the quadrotor including the rotational dynamics and the inverted pendulum dynamics. To address this problem, the dynamic model is linearized around an equilibrium point, taking into consideration that the system operates in close vicinity of the equilibrium points, thus considerably simplifying the dynamic model. Proving that the linear model is controllable and therefore differentiable flat, flat outputs are proposed around the displacements associated with the three cartesian axes of the Euclidean space, including a dynamic associated with the yaw dynamics of the quadrotor allowing to parameterize the full linear system. Simulation results as well as a convergence analysis validate the performance of the strategy. Full article
(This article belongs to the Special Issue Dynamics and Control of UAVs)
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22 pages, 1614 KiB  
Article
Simple Internal Model-Based Robust Control Design for a Non-Minimum Phase Unmanned Aerial Vehicle
by Argyrios Zolotas
Machines 2023, 11(4), 498; https://doi.org/10.3390/machines11040498 - 21 Apr 2023
Cited by 1 | Viewed by 1759
Abstract
Robust control has been successful in enabling flight stability and performance for UAVs. This paper presents a simple explainable robust control design for UAV platforms with non-minimum phase (NMP) zero characteristics in their model. The paper contributes to economic (simple) robust control design [...] Read more.
Robust control has been successful in enabling flight stability and performance for UAVs. This paper presents a simple explainable robust control design for UAV platforms with non-minimum phase (NMP) zero characteristics in their model. The paper contributes to economic (simple) robust control design by addressing the NMP model’s characteristics via Internal Model Control (IMC) and its impact on the UAV pitch response performance. The proposed design is compared with a Parallel Feedback Control Design (PFCD) scheme for the same vehicle platform, for fair comparison. Simulation results illustrate the achievement of the proposed control designs for the UAV platform; only the pitch control is addressed. A by-product of this work is the interpretation of different ways of manipulating the non-minimum phase plant model, so-called ‘modelling for control’, to enable the simple controller design. The work in this paper underpins the simplicity and robustness of the IMC technique for the NMP UAV platform, which further supports the explainability of the control structure relative to performance. Full article
(This article belongs to the Special Issue Dynamics and Control of UAVs)
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