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Applied Sciences
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New Technology for Autonomous UAV Monitoring
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New Technology for Autonomous UAV Monitoring

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 9243

Special Issue Editors

Dr. Qiang Chen

E-Mail Website
Guest Editor
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China
Interests: adaptive and learning control; logistics robot programming and planning; aircraft attitude control
Dr. Shubo Wang

E-Mail Website
Guest Editor
School of Automation, Qingdao University, Qingdao 266071, China
Interests: autonomous navigation; unmanned aerial vehicles; autonomous navigation spray system
Dr. Liang Tao

E-Mail Website
Guest Editor
School of Electrical Engineering, Anhui Polytechnic University, Wuhu 241000, China
Interests: convolutional neural network; deep neural networks; algorithm

Special Issue Information

Dear Colleagues,

As an important security tool in modern social life, video surveillance seriously affects public security and order. The existing video surveillance technology are mainly based on fixed point cameras, which have the defects of high cost and single monitoring perspective. UAV monitoring and control system has great advantages in sparsely populated and vast areas, and has good effects in military security, forest protection and other fields. However, UAV monitoring and control system also faces challenges of complexity and diversity of application scenarios, including detection and tracking of suspicious targets from the perspective of UAVs, endurance, adaptability to severe weather, and autonomy retraction & landing of UAV failures, etc. Therefore, the research and design of new autonomous monitoring and control technology based on UAV are of great attractions to researchers. This special issue of the Applied Sciences will provide a forum for researchers and practitioners to share insights on innovation and new technology for autonomous UAV monitoring and control.

Authors are invited to submit full papers describing original work in all aspects of engineering techniques related to the autonomy, reliability, and safety of autonomous UAV covering the following topics but are not limited to:

  • Target detection and tracking for UAV monitoring;
  • Multi-sensor video image fusion for UAV monitoring;
  • Design& realization of monitor and navigation system for UAV;
  • Autonomous detection and search of UAV;
  • Autonomous obstacle avoidance of UAV;
  • UAV task resource management and planning;
  • Autonomous control system and mode of UAV;
  • Swarm intelligence based multi-UAV coordinated control;
  • lAttitude control and reliability analysis of UAV;
  • New technologies for autonomous control and decision-making of UAV.

Dr. Qiang Chen
Dr. Shubo Wang
Dr. Liang Tao
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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • autonomous navigation
  • unmanned aerial vehicles
  • autonomous navigation spray system

Published Papers (7 papers)

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17 pages, 691 KiB  
Article
Adaptive Optimal Control of UAV Brake Based on Parameter Estimation
by Hao Lv, Qinrui Liu, Yu Wan, Xuehui Gao, Feng Li and Zhen Liu
Appl. Sci. 2023, 13(21), 11888; https://doi.org/10.3390/app132111888 - 30 Oct 2023
Viewed by 623
Abstract
A new parameter estimation method for a UAV braking system with unknown friction parameters is suggested. The unknown part containing friction is separated from the coupling system. The law of parameter updating is driven by the estimation error extracted by the auxiliary filter. [...] Read more.
A new parameter estimation method for a UAV braking system with unknown friction parameters is suggested. The unknown part containing friction is separated from the coupling system. The law of parameter updating is driven by the estimation error extracted by the auxiliary filter. A controller is developed to guarantee the convergence of the parameter estimation and tracking errors simultaneously. Furthermore, a designed performance index function enables the system to track the desired slip rate optimally. The optimal value of the performance function is updated by a single critic neural network (NN) to obtain comprehensive optimization of the control energy consumption, dynamic tracking error, and filtering error during braking. In addition, the unknown bounded interference and neural network approximation errors are compensated by robust integral terms. Simulation results are presented to confirm the effectiveness of the proposed control scheme. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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20 pages, 6159 KiB  
Article
High-Performance Flux Tracking Controller for Reluctance Actuator
by Yang Liu, Qian Miao and Yue Dong
Appl. Sci. 2023, 13(19), 10811; https://doi.org/10.3390/app131910811 - 28 Sep 2023
Viewed by 553
Abstract
To meet the ever-increasing demand for next-generation lithography machines, the actuator plays an important role in the achievement of high acceleration of the wafer stage. However, the voice coil motor, which is widely used in high-precision positioning systems, is reaching its physical limits. [...] Read more.
To meet the ever-increasing demand for next-generation lithography machines, the actuator plays an important role in the achievement of high acceleration of the wafer stage. However, the voice coil motor, which is widely used in high-precision positioning systems, is reaching its physical limits. To tackle this problem, a novel way to design the actuator using the magnetoresistance effect is argued due to the high force densities. However, the strong nonlinearity limits its application in the nan-positioning system. In particular, the hysteresis is coupled with eddy effects and displacement, which lead to a rate-dependent and displacement-dependent hysteresis effect in the reluctance actuator. In this paper, a Hammerstein structure is used to model the rate-dependent reluctance actuator. At the same time, the displacement-dependent of the model is regarded as the interference with the system. Additionally, a control strategy combining inverse model compensation and the disturbance observer-based discrete sliding mode control was proposed, which can effectively suppress the hysteresis effect. It is worthy pointing out that the nonlinear system is transformed into a linear system with inversion bias and disturbance by the inverse model compensation. What is more, the sliding mode controller based on the disturbance observer is designed to deal with the unmodeled dynamics, displacement disturbances, and model identification errors in linear systems. Thus, the tracking performance and robustness to external disturbances of the system are improved. The simulation results show that it is superior to the PI controller combined with an inverse compensator and even to the discrete sliding mode controller connected with inverse compensator, confirming the effectiveness of the novel control method in alleviating hysteresis. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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14 pages, 3569 KiB  
Article
Finite-Time Height Control of Quadrotor UAVs
by Shuaihe Zhao, Yuanqing Xia, Liqun Ma and Hongjiu Yang
Appl. Sci. 2023, 13(13), 7914; https://doi.org/10.3390/app13137914 - 06 Jul 2023
Viewed by 662
Abstract
The quadrotor Unmanned Aerial Vehicle (UAV) belongs to an open-loop unstable nonlinear system, which also has the characteristics of underdrive, strong coupling and external disturbance. In the height control of quadrotor UAVs, the traditional sliding mode control (SMC) and PID methods cannot quickly [...] Read more.
The quadrotor Unmanned Aerial Vehicle (UAV) belongs to an open-loop unstable nonlinear system, which also has the characteristics of underdrive, strong coupling and external disturbance. In the height control of quadrotor UAVs, the traditional sliding mode control (SMC) and PID methods cannot quickly and effectively eliminate disturbance effects caused by gust, aerodynamic drag and other factors, which indicates that the quadrotor UAV cannot return to its predetermined trajectory. To this end, this paper proposes a dual closed-loop finite-time height control method for the quadrotor UAV. The proposed method is able to estimate and compensate for the disturbance in the height control and make up for the lack of anti-disturbance ability in the control process. More specifically, a finite-time Extended State Observer (ESO) and a finite-time super-twisting controller are designed for the velocity control system to compensate for the total disturbance and track the rapidly changing expected signal. An integral sliding mode controller is designed for the height control system. Simulation results show that the proposed method can reduce the chattering phenomenon of traditional SMC and improve both control accuracy and convergence speed. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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19 pages, 1837 KiB  
Article
Reinforcement Learning for Autonomous Underwater Vehicles via Data-Informed Domain Randomization
by Wenjie Lu, Kai Cheng and Manman Hu
Appl. Sci. 2023, 13(3), 1723; https://doi.org/10.3390/app13031723 - 29 Jan 2023
Cited by 3 | Viewed by 1690
Abstract
Autonomous Underwater Vehicles (AUVs) or underwater vehicle-manipulator systems often have large model uncertainties from degenerated or damaged thrusters, varying payloads, disturbances from currents, etc. Other constraints, such as input dead zones and saturations, make the feedback controllers difficult to tune online. Model-free Reinforcement [...] Read more.
Autonomous Underwater Vehicles (AUVs) or underwater vehicle-manipulator systems often have large model uncertainties from degenerated or damaged thrusters, varying payloads, disturbances from currents, etc. Other constraints, such as input dead zones and saturations, make the feedback controllers difficult to tune online. Model-free Reinforcement Learning (RL) has been applied to control AUVs, but most results were validated through numerical simulations. The trained controllers often perform unsatisfactorily on real AUVs; this is because the distributions of the AUV dynamics in numerical simulations and those of real AUVs are mismatched. This paper presents a model-free RL via Data-informed Domain Randomization (DDR) for controlling AUVs, where the mismatches between the trajectory data from numerical simulations and the real AUV were minimized by adjusting the parameters in the simulated AUVs. The DDR strategy extends the existing adaptive domain randomization technique by aggregating an input network to learn mappings between control signals across domains, enabling the controller to adapt to sudden changes in dynamics. The proposed RL via DDR was tested on the problems of AUV pose regulation through extensive numerical simulations and experiments in a lab tank with an underwater positioning system. These results have demonstrated the effectiveness of RL-DDR for transferring trained controllers to AUVs with different dynamics. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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21 pages, 24358 KiB  
Article
Design of Robust Sensing Matrix for UAV Images Encryption and Compression
by Qianru Jiang, Huang Bai and Xiongxiong He
Appl. Sci. 2023, 13(3), 1575; https://doi.org/10.3390/app13031575 - 26 Jan 2023
Cited by 2 | Viewed by 904
Abstract
The sparse representation error (SRE) exists when the images are represented sparsely. The SRE is particularly large in unmanned aerial vehicles (UAV) images due to the disturbance of the harsh environment or the instability of its flight, which will bring more noise. In [...] Read more.
The sparse representation error (SRE) exists when the images are represented sparsely. The SRE is particularly large in unmanned aerial vehicles (UAV) images due to the disturbance of the harsh environment or the instability of its flight, which will bring more noise. In the compressed sensing (CS) system, the projected SRE in the compressed measurement will bring a significant challenge to the recovery accuracy of the images. In this work, a new SRE structure is proposed. Following the new structure, a lower sparse representation error (LSRE) is achieved by eliminating groups of sparse representation. With the proposed LSRE modeling, a robust sensing matrix is designed to compress and encrypt the UAV images. Experiments for UAV images are carried out to compare the recovery performance of the proposed algorithm with the existing related algorithms. The results of the proposed algorithm reveal superior recovery accuracy. The new CS framework with the proposed sensing matrix to address the scenario of UAV images with large SRE is dominant. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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14 pages, 1947 KiB  
Article
Integer Ambiguity Parameter Identification for Fast Satellite Positioning and Navigation Based on LAMBDA-GWO with Tikhonov Regularization
by Guanbin Gao, Le Li, Qinghua Shi and Pei Xie
Appl. Sci. 2023, 13(3), 1239; https://doi.org/10.3390/app13031239 - 17 Jan 2023
Viewed by 1299
Abstract
Satellite positioning is one of the main navigation technologies in unmanned aerial vehicles (UAVs), the accuracy of which has an important impact on the safety, stability, and flexibility of UAVs. The parameters of integer ambiguity are important factors affecting the accuracy of satellite [...] Read more.
Satellite positioning is one of the main navigation technologies in unmanned aerial vehicles (UAVs), the accuracy of which has an important impact on the safety, stability, and flexibility of UAVs. The parameters of integer ambiguity are important factors affecting the accuracy of satellite positioning. However, the accuracy of the integer ambiguity cannot be guaranteed when only a few epoch data can be obtained in the fast positioning such that the identification matrix of the integer ambiguity parameters is seriously ill-conditioned and the information of position deviation is enlarged. In this paper, an error checking and correcting strategy is proposed, where a Least-square Ambiguity Decorrelation Adjustment-Grey Wolf Optimization (LAMBDA-GWO) Method combined with the Tikhonov regularization method is developed to improve the accuracy of integer ambiguity for fast satellite positioning. More specifically, the LAMBDA-GWO is first used to search the integer ambiguity parameters. To reduce the ill-condition of the integer ambiguity parameter identification matrix, the Tikhonov regularization method is introduced to regularize the identification matrix such that a reliable integer ambiguity floating-point solution can be obtained. Furthermore, the correctness of the integer ambiguity is checked according to the prior accuracy information of the initial coordinates and the Total Electron Content (TEC), and the part that fails the test is corrected by the Grey Wolf Optimization (GWO) Method. Finally, experimental studies based on a 522 m baseline and a 975 m baseline show that the identification success rates of the proposed method are both above 99%, which is 12% and 23% higher than that of traditional LAMBDA, respectively. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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15 pages, 3229 KiB  
Technical Note
IGBT Overvoltage Protection Based on Dynamic Voltage Feedback and Active Clamping
by Mingfang Chen, Zhichao Xiong, Yongxia Zhang, Enxiao Zhu, Yuying Zhao and Zunbo Ma
Appl. Sci. 2023, 13(2), 795; https://doi.org/10.3390/app13020795 - 06 Jan 2023
Cited by 2 | Viewed by 2655
Abstract
In view of the stability of the unmanned aerial vehicle (UAV) power system, this paper found that the voltage spike generated by IGBT mainly occurs when the IGBT is turned off in the study of the power system interior and IGBT drive and [...] Read more.
In view of the stability of the unmanned aerial vehicle (UAV) power system, this paper found that the voltage spike generated by IGBT mainly occurs when the IGBT is turned off in the study of the power system interior and IGBT drive and overvoltage protection, and an excessive voltage spike will lead to IGBT damage. To eliminate this serious threat to the safe operation of the circuit, an IGBT overvoltage protection circuit combining dynamic voltage feedback and active clamping is proposed. In this method, active clamping and dynamic voltage feedback circuits are operated alternately, and the drive circuit is controlled by the feedback of capacitor’s the dynamic voltage rise rate. The gate current output of the IGBT is directly compensated to control the signal delay of the gate, combined with improving the lifting effect of the active clamp circuit on the gate voltage and suppressing the peak of the turn-off voltage. According to the IGBT turn off process, combined with SABER simulation, this paper finally builds IGBT turn off experimental circuit to prove that the proposed method suppresses the size of the turn off voltage spike, further analyzes the effect of key circuit parameters on the suppression of the turn off voltage spike, thereby ensuring the safe operation of the IGBT, and improving the stability of the UAV power system. Full article
(This article belongs to the Special Issue New Technology for Autonomous UAV Monitoring)
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