Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge

• Main Authors: Sarabakha, Andriy, Kayacan, Erdal
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Training; Fuzzy Logic
• Online Access: https://hdl.handle.net/10356/141407
• Institution: Nanyang Technological University

This work presents an online learning-based control method for improved trajectory tracking of unmanned aerial vehicles using both deep learning and expert knowledge. The proposed method does not require the exact model of the system to be controlled, and it is robust against variations in system dy...