Abbas Nadir, Abbas Zeshan, Zafar Samra, Ahmad Naseem, Liu Xiaodong, Khan Saad Saleem, Foster Eric Deale, Larkin Stephen
School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China.
Institute of Ultrasonic Technology, Shenzhen Polytechnic University, Shenzhen 518055, China.
Sensors (Basel). 2024 May 21;24(11):3286. doi: 10.3390/s24113286.
This survey paper explores advanced nonlinear control strategies for Unmanned Aerial Vehicles (UAVs), including systems such as the Twin Rotor MIMO system (TRMS) and quadrotors. UAVs, with their high nonlinearity and significant coupling effects, serve as crucial benchmarks for testing control algorithms. Integration of sophisticated sensors enhances UAV versatility, making traditional linear control techniques less effective. Advanced nonlinear strategies, including sensor-based adaptive controls and AI, are increasingly essential. Recent years have seen the development of diverse sliding surface-based, sensor-driven, and hybrid control strategies for UAVs, offering superior performance over linear methods. This paper reviews the significance of these strategies, emphasizing their role in addressing UAV complexities and outlining future research directions.
本文探讨了无人机（UAV）的先进非线性控制策略，包括双旋翼多输入多输出系统（TRMS）和四旋翼飞行器等系统。无人机具有高度非线性和显著的耦合效应，是测试控制算法的关键基准。复杂传感器的集成增强了无人机的通用性，使传统线性控制技术的效果降低。包括基于传感器的自适应控制和人工智能在内的先进非线性策略变得越来越重要。近年来，针对无人机开发了各种基于滑模面、传感器驱动和混合控制策略，与线性方法相比具有卓越的性能。本文回顾了这些策略的重要性，强调了它们在应对无人机复杂性方面的作用，并概述了未来的研究方向。
