Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review
In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned Aerial Vehicle (UAV) in both civil and military sectors. Among various UAVs, the ability of rotary wing UAVs (RUAVs) in vertical take-off and landing, to hover and perform quick maneuvering attract rese...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/10356/142506 |
| _version_ | 1826114724500078592 |
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| author | Md Meftahul Ferdaus Anavatti, Sreenatha G. Pratama, Mahardhika Garratt, Matthew A. |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Md Meftahul Ferdaus Anavatti, Sreenatha G. Pratama, Mahardhika Garratt, Matthew A. |
| author_sort | Md Meftahul Ferdaus |
| collection | NTU |
| description | In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned Aerial Vehicle (UAV) in both civil and military sectors. Among various UAVs, the ability of rotary wing UAVs (RUAVs) in vertical take-off and landing, to hover and perform quick maneuvering attract researchers to develop models fully autonomous control framework. The majority of first principle techniques in modeling and controlling RUAV face challenges in incorporating and handling various uncertainties. Recently various fuzzy and neuro-fuzzy based intelligent systems are utilized to enhance the RUAV’s modeling and control performance. However, the majority of these fuzzy systems are based on batch learning methods, have static structure, and cannot adapt to rapidly changing environments. The implication of Evolving Intelligent System based model-free data-driven techniques can be a smart option since they can adapt their structure and parameters to cope with sudden changes in the behavior of RUAVs real-time flight. They work in a single pass learning fashion which is suitable for online real-time deployment. In this paper, state of the art of various fuzzy systems from the basic fuzzy system to evolving fuzzy system, their application in a RUAV namely quadcopter with existing limitations, and possible opportunities are analyzed. Besides, a variety of first principle techniques to control the quadcopter, their impediments, and conceivable solution with recently employed evolving fuzzy controllers are reviewed. |
| first_indexed | 2024-10-01T03:43:49Z |
| format | Journal Article |
| id | ntu-10356/142506 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:43:49Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1425062020-06-23T03:48:42Z Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review Md Meftahul Ferdaus Anavatti, Sreenatha G. Pratama, Mahardhika Garratt, Matthew A. School of Computer Science and Engineering Engineering::Computer science and engineering Evolving Fuzzy Learning Machine In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned Aerial Vehicle (UAV) in both civil and military sectors. Among various UAVs, the ability of rotary wing UAVs (RUAVs) in vertical take-off and landing, to hover and perform quick maneuvering attract researchers to develop models fully autonomous control framework. The majority of first principle techniques in modeling and controlling RUAV face challenges in incorporating and handling various uncertainties. Recently various fuzzy and neuro-fuzzy based intelligent systems are utilized to enhance the RUAV’s modeling and control performance. However, the majority of these fuzzy systems are based on batch learning methods, have static structure, and cannot adapt to rapidly changing environments. The implication of Evolving Intelligent System based model-free data-driven techniques can be a smart option since they can adapt their structure and parameters to cope with sudden changes in the behavior of RUAVs real-time flight. They work in a single pass learning fashion which is suitable for online real-time deployment. In this paper, state of the art of various fuzzy systems from the basic fuzzy system to evolving fuzzy system, their application in a RUAV namely quadcopter with existing limitations, and possible opportunities are analyzed. Besides, a variety of first principle techniques to control the quadcopter, their impediments, and conceivable solution with recently employed evolving fuzzy controllers are reviewed. 2020-06-23T03:48:42Z 2020-06-23T03:48:42Z 2020 Journal Article Md Meftahul Ferdaus., Anavatti, S. G., Pratama, M., & Garratt, M. A. (2020). Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review. Artificial Intelligence Review, 53, 257–290. doi:10.1007/s10462-018-9653-z 0269-2821 https://hdl.handle.net/10356/142506 10.1007/s10462-018-9653-z 2-s2.0-85052106496 53 257 290 en Artificial Intelligence Review © 2018 Springer Nature B. V. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Evolving Fuzzy Learning Machine Md Meftahul Ferdaus Anavatti, Sreenatha G. Pratama, Mahardhika Garratt, Matthew A. Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title | Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title_full | Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title_fullStr | Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title_full_unstemmed | Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title_short | Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle : a review |
| title_sort | towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle a review |
| topic | Engineering::Computer science and engineering Evolving Fuzzy Learning Machine |
| url | https://hdl.handle.net/10356/142506 |
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