Takagi-Sugeno Fuzzy Model Identification for Small Scale Unmanned Helicopter
This paper presents system identification method for small unmanned helicopter based on Takagi Sugeno fuzzy models under hover. Firstly,the nonlinear discrete model of small unmanned helicopter with unknown parametersis determined by Takagi Sugeno system. Secondly, derivative based gradientmethod is...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2014-01-01.
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| LEADER | 02110 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs3027_1036 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Nighat Khizer, Arbab |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Yaping, Dai |e author |
| 700 | 1 | 0 | |a Ali, Syed Amjad |e author |
| 700 | 1 | 0 | |a Yang, Xu Xiang |e author |
| 245 | 0 | 0 | |a Takagi-Sugeno Fuzzy Model Identification for Small Scale Unmanned Helicopter |
| 260 | |b Institute of Advanced Engineering and Science, |c 2014-01-01. | ||
| 520 | |a This paper presents system identification method for small unmanned helicopter based on Takagi Sugeno fuzzy models under hover. Firstly,the nonlinear discrete model of small unmanned helicopter with unknown parametersis determined by Takagi Sugeno system. Secondly, derivative based gradientmethod is used to identify unknown parameters of TS fuzzy model because in gradientadaptation, fuzzy system is not supposed to be linear in the parameters, so allfuzzy sets for input and output could be adjusted. The proposed method showedits effectiveness in terms of data matching obtained by the X-Plane©flight simulator. Obtained simulation results show high accuracy of themodeling method and better justification for real time applicability of theapproach DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3577 | ||
| 540 | |a Copyright (c) 2013 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc-nd/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Control Engineering | ||
| 690 | |a Small unmanned helicopter (SUH), Modeling, Identification, Takagi-Sugeno fuzzy system, Gradient method. | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 12, No 1: January 2014; 487-495 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v12.i1 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3027/1036 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3027/1036 |z Get fulltext |