Progress of Low-Speed Uavs Integrated with Computational Control Systems

DOI

10.2991/978-94-6463-864-6_14How to use a DOI?

Keywords

Unmanned Aerial Vehicles; Aerodynamic Optimization; Brushless Motors; Pid Control; Lqr Control

Abstract

This paper examines the design and application of low-speed unmanned aerial vehicles (UAVs) by integrating aerodynamic optimization and advanced computational control systems. Despite their widespread use in surveillance, logistics, environmental monitoring, and disaster response, UAVs face challenges in achieving optimal aerodynamic performance and precise control, particularly in low-speed subsonic regimes. To address these issues, this study proposes a novel framework combining computational fluid dynamics (CFD) simulations, wind tunnel testing, and adaptive control strategies such as proportion integration differentiation (PID), linear quadratic regulator (LQR), and reinforcement learning algorithms. Key results include a 15–20% improvement in lift-to-drag ratio through aerodynamic optimization, a 20–30% reduction in power consumption using high-efficiency brushless motors, and enhanced stability and responsiveness via hybrid control strategies. The integration of artificial intelligence in flight control systems demonstrated significant adaptability to dynamic flight conditions, enabling effective operation in complex environments. The study emphasizes the importance of holistic design approaches that optimize both aerodynamics and control systems. While substantial progress has been made, future research should focus on extreme environmental conditions, novel propulsion technologies, and AI-driven predictive maintenance and fault-tolerant control systems. These advancements aim to enhance safety, efficiency, and reliability in autonomous UAV operations.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhongsi Jiao
AU  - Weitao Lin
AU  - Yite Zheng
PY  - 2025
DA  - 2025/10/23
TI  - Progress of Low-Speed Uavs Integrated with Computational Control Systems
BT  - Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
PB  - Atlantis Press
SP  - 132
EP  - 141
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-864-6_14
DO  - 10.2991/978-94-6463-864-6_14
ID  - Jiao2025
ER  -