Control Algorithms, Kalman Estimation and Near Actual Simulation for UAVs: State of Art Perspective

  1. Tahir, Muhammad Amir 1
  2. Mir, Imran 1
  3. Islam, Tauqeer Ul 1
  4. González Aguilera, Diego 2
  1. 1 College of Aeronautical Engineering, National University of Science & Technology, Risalpur 23200, Pakistan
  2. 2 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
Drones

ISSN: 2504-446X

Año de publicación: 2023

Volumen: 7

Número: 6

Páginas: 339

Tipo: Artículo

DOI: 10.3390/DRONES7060339 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Drones

Resumen

The pervasive use of unmanned aerial vehicles for both commercial and military operations has undergone rapid development in the recent past. When designing unmanned aerial vehicles, it is highly desirable for them to be able to complete their missions with minimal human intervention. Reaching full autonomy requires a reliable and efficient control algorithm that can handle all flight conditions. Due to the confidential nature of UAV design and development, there is a lack of comprehensive literature on the subject. When it comes to the practical application of the ideas presented in the literature, the situation is even bleaker. This research not only examines the flight phases in which controllers and estimators are used for UAVs but also provides an in-depth analysis of the most recent and state-of-the-art control and estimate techniques for UAVs. Research opportunities and challenges specific to UAVs were also examined in this study in an effort to raise the bar for UAV design as a whole and smooth the way for researchers to go from simulation-based research to practical applications. This review paper establishes a foundation that not only investigates the inherent flight dynamics, control architecture, and Kalman estimators utilized in the development of UAVs but also points out the shortcomings that currently exist in research. A number of design considerations for realistic applications and potential studies are presented in the conclusion.

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