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Survey of Advanced Nonlinear Control Strategies for UAVs: Integration of Sensors and Hybrid Techniques.
Abbas, Nadir; Abbas, Zeshan; Zafar, Samra; Ahmad, Naseem; Liu, Xiaodong; Khan, Saad Saleem; Foster, Eric Deale; Larkin, Stephen.
Afiliação
  • Abbas N; School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China.
  • Abbas Z; Institute of Ultrasonic Technology, Shenzhen Polytechnic University, Shenzhen 518055, China.
  • Zafar S; Department of Computer Science, School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China.
  • Ahmad N; School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China.
  • Liu X; School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China.
  • Khan SS; Department of Electrical Engineering, College of Engineering, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.
  • Foster ED; Omega Aviation Ltd., Leicester LE9 4LG, UK.
  • Larkin S; Omega Aviation Ltd., Leicester LE9 4LG, UK.
Sensors (Basel) ; 24(11)2024 May 21.
Article em En | MEDLINE | ID: mdl-38894079
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article