Online identification of a rotary wing Unmanned Aerial Vehicle from data streams

• Main Authors: Ferdaus, Md Meftahul, Pratama, Mahardhika, Anavatti, Sreenatha G., Garratt, Matthew A.
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering; Evolving; Fuzzy
• Online Access: https://hdl.handle.net/10356/150569
• Institution: Nanyang Technological University

Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unmanned Aerial Vehicles (UAVs), such as the quadrotor, have been based on batch learning techniques, therefore static in structure, and cannot adapt to rapidly changing environments. Implication of Evolvin...