Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs
- Submitting institution
-
University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1318901
- Type
- D - Journal article
- DOI
-
10.1109/TMECH.2018.2810947
- Title of journal
- IEEE/ASME Transactions on Mechatronics
- Article number
- -
- First page
- 725
- Volume
- 23
- Issue
- 2
- ISSN
- 1083-4435
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 20
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, for the first time, develops and analyses a centroid-based non-singleton fuzzy logic controller for autonomous robots, specifically unmanned aerial vehicles, showing better performance and robustness. The approach directly handles non-stationary levels of uncertainty affecting (e.g. drone) sensors - without increasing the complexity of the controller itself. Because the approach does not require the change of controller parameters, such as its rules, it also facilitates controller design and interpretability. The results are backed up by a systematic evaluation combining (both simulation and real-world) drone experiments, comparing both fuzzy and traditional model based controllers.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
