Design, Modeling, and Control Allocation of a Heavy-Lift Aerial Vehicle Consisting of Large Fixed Rotors and Small Tiltrotors


IEEE-ASME TRANSACTIONS ON MECHATRONICS, vol.27, no.5, pp.4011-4021, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1109/tmech.2022.3150713
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.4011-4021
  • Keywords: Rotors, Propellers, Servomotors, Controllability, Loading, Autonomous aerial vehicles, Robots, Aerial robotics, control allocation, design optimization, dynamic modeling, flight control, tiltrotor
  • Middle East Technical University Affiliated: Yes


In this article, we propose an unconventional heavy-lift aerial vehicle (HLAV), present the design and its control allocation analysis, and prove the concept by the demonstration of the experimental test prototype in the outdoor environment. We aim for a mechanically robust and simple vehicle design that efficiently performs heavy lifting compared to other common aerial vehicles under certain width constraints, without using a complex swashplate mechanism. The HLAV performs the task of carrying the main load with two large propellers that are efficient, thanks to the greater disk area, and includes two small tilting propellers for controllability. This system has a "PPNN" (P: clockwise and N: counterclockwise) propeller arrangement to compensate for the reaction torques of equally sized propeller pairs placed on opposite sides. However, conventional quadcopters with the "PPNN" propeller arrangement lose their controllability upon hovering. Therefore, servo motors are integrated into the small propellers to ensure controllability. The nonlinear dynamic model of the HLAV is built by the Newton-Euler approach, and the system is linearized around the hover equilibrium point for controllability analysis. Model parameters are estimated using closed-loop system identification tools. High-level controllers are designed with the "loop shaping" method. To show feasibility, the proposed system is experimentally verified with a newly designed prototype, and sufficient trajectory tracking performance is achieved in a stable manner.