Advanced Navigation, Control and Application of Unmanned Aerial Vehicles

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 565

Special Issue Editor


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Guest Editor
College of Mechanical and Electronic Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: artificial intelligence; computational linguistics; information retrieval; bionic unmanned system design related technologies

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs), also known as drones, have emerged as a versatile and transformative technology with a wide range of applications spanning various fields, including the military, civilian, environmental, agricultural, and industrial sectors. Over the past few decades, significant progress has been made in the development of UAVs, leading to increasingly sophisticated systems capable of autonomous flight, navigation, and versatile applications. The amalgamation of advanced navigation algorithms, cutting-edge control techniques, and innovative applications has paved the way for UAVs to revolutionize traditional industries and open up new frontiers in scientific research.

The rapid advancement in UAV technology has been primarily driven by breakthroughs in key areas such as sensing, communication, and artificial intelligence. As a result, UAVs are now equipped with an array of sophisticated sensors, including GPS, LiDAR, cameras, and other environmental sensors, enabling them to perceive their surroundings with remarkable precision. Moreover, advancements in communication systems allow for real-time data exchange between the UAV and ground stations, facilitating seamless control and navigation even in challenging environments.

Navigation lies at the core of UAV operations, enabling them to traverse dynamic and complex terrains, avoid obstacles, and reach designated destinations autonomously. Traditional control methods have evolved into intelligent and adaptive control strategies, incorporating machine learning and data-driven approaches to enhance flight stability, energy efficiency, and safety. These advancements have significantly reduced the reliance on human pilots, making UAVs increasingly autonomous, reliable, and cost-effective.

This Special Issue aims to explore the latest developments in advanced navigation and control techniques for UAVs and their diverse applications. The research presented here will delve into novel algorithms and methodologies that contribute to precise localization, obstacle avoidance, path planning, and cooperative navigation of UAV swarms. Moreover, this Special Issue will shed light on the integration emerging technologies, such as 5G networks, edge computing, and Internet of Things (IoT) platforms, into UAVs, further expanding their capabilities and potential applications.

Dr. Cai Luo
Guest Editor

Manuscript Submission Information

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Published Papers (2 papers)

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Research

24 pages, 8802 KiB  
Article
Spring-Damped Underactuated Swashplateless Rotor on a Bicopter Unmanned Aerial Vehicle
by Haofei Guan and K. C. Wong
Machines 2024, 12(5), 296; https://doi.org/10.3390/machines12050296 (registering DOI) - 28 Apr 2024
Viewed by 118
Abstract
The stabilisation capabilities of unmanned aerial vehicles (UAVs) with bicopter underactuated swashplateless rotors are highly sensitive to motor-induced vibration. Due to the requirement of the active control of underactuated swashplateless rotors, conventional designs are limited in reducing vibration through control optimisation. A solution [...] Read more.
The stabilisation capabilities of unmanned aerial vehicles (UAVs) with bicopter underactuated swashplateless rotors are highly sensitive to motor-induced vibration. Due to the requirement of the active control of underactuated swashplateless rotors, conventional designs are limited in reducing vibration through control optimisation. A solution with customized passive spring-damping structures on a unique underactuated swashplateless rotor of a tiltrotor bicopter platform is presented. The implementation of this structure effectively reduces the self-coherent vibration in flights. As a result, a higher level of control authority has been achieved without setting excessive low-pass filtering for vibration. Experimentally obtained inertial measurement unit (IMU) data, rotor speed, rotor tilt angle, and the cyclic stator response are presented for comparison with Simulink model predictions. Full article
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21 pages, 1603 KiB  
Article
Enhanced Whale Optimization Algorithm for Fuzzy Proportional–Integral–Derivative Control Optimization in Unmanned Aerial Vehicles
by Yixuan Zhang, Fuzhong Li, Yihe Zhang, Svitlana Pavlova and Zhou Zhang
Machines 2024, 12(5), 295; https://doi.org/10.3390/machines12050295 (registering DOI) - 27 Apr 2024
Viewed by 134
Abstract
The traditional PID controller in quadrotor UAVs has poor performance, a large overshoot, and a long adjustment time, which limit its stability and accuracy in practical applications. In order to solve this problem, an improved whale optimization fuzzy PID control strategy based on [...] Read more.
The traditional PID controller in quadrotor UAVs has poor performance, a large overshoot, and a long adjustment time, which limit its stability and accuracy in practical applications. In order to solve this problem, an improved whale optimization fuzzy PID control strategy based on CRICLE chaos map initialization is proposed, and a detailed simulation analysis was carried out using MATLAB software (MATLAB R2022B). Firstly, to more realistically reflect quadrotor UAVs’ flight behavior, a dynamic simulation model was established, and the dynamics and kinematic characteristics of the aircraft were considered. Then, CRICLE chaotic mapping initialization was introduced to improve the global search ability of the whale optimization algorithm and to effectively initialize the parameters of the fuzzy PID controller. This improved initialization method helped to speed up the convergence process and improve the stability of the control system. In the simulation experiments, we compared the performance indicators of the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID controller to the traditional PID and fuzzy PID controllers, including overshoot, adjustment time, etc. The results show that the proposed control strategy has better performance than the traditional PID and fuzzy PID controllers, significantly reduces overshoot, and achieves a significant improvement in adjustment time. Therefore, the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID control strategy proposed in this study provides an effective solution for improving the performance of the quadrotor control system and has practical application potential. Full article
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