Online identification of a rotary wing Unmanned Aerial Vehicle from data streams
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...
Main Authors: | Ferdaus, Md Meftahul, Pratama, Mahardhika, Anavatti, Sreenatha G., Garratt, Matthew A. |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/150569 |
Similar Items
-
Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review
by: Md Meftahul Ferdaus, et al.
Published: (2020) -
Development of C-Means clustering based adaptive fuzzy controller for a flapping wing micro air vehicle
by: Md Meftahul Ferdaus, et al.
Published: (2020) -
PAC : A novel self-adaptive neuro-fuzzy controller for micro aerial vehicles
by: Ferdaus, Md Meftahul, et al.
Published: (2021) -
Scalable teacher forcing network for semi-supervised large scale data streams
by: Pratama, Mahardhika, et al.
Published: (2022) -
Evolving ensemble fuzzy classifier
by: Pratama, Mahardhika, et al.
Published: (2019)