A robust fault-tolerant control algorithm for GPS-denied mini quadrotors using PID-TinyMPC and visual-inertial odometry


Çintaş E., ÖZYER B.

Control Engineering Practice, cilt.169, 2026 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 169
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.conengprac.2026.106779
  • Dergi Adı: Control Engineering Practice
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Anahtar Kelimeler: Computer vision, Fault-tolerant control, Quadrotor, Robot safety, Unmanned aerial vehicles, Visual-inertial odometry
  • Atatürk Üniversitesi Adresli: Evet

Özet

Fault-tolerant control (FTC) is crucial for ensuring the safety and reliability of autonomous quadrotors, especially in scenarios involving rotor failures. This paper presents a hybrid control architecture that combines a PID-based outer-loop controller with a TinyMPC-based inner-loop controller, integrated with visual-inertial odometry (VIO) for real-time state estimation. The proposed method enables a mini quadrotor to maintain stable flight and trajectory tracking even under rotor failure conditions, using only onboard sensors (IMU, barometer and monocular camera) without relying on external positioning systems such as GPS and VICON. The outer-loop PID controller handles position control at a lower frequency, while the inner-loop TinyMPC operates at a higher frequency to manage the fast-changing attitude dynamics. This design reduces computational overhead while maintaining spatial-temporal stability and precision. Experimental results demonstrate the effectiveness of the proposed method in real-world scenarios, where the quadrotor successfully maintains hovering under varying yaw rates and rotor speed reduction conditions. The proposed low-cost, computationally efficient solution addresses a significant gap in the literature by providing a robust FTC approach that is feasible for microcontrollers and resource-constrained platforms. The source code and some flight videos are publicly available at: https://github.com/emrecintas/fault_tolerant_control.