Angular velocity dynamics identification of small unmanned helicopter using fuzzy model

Arbab Nighat Khizer; Ya Ping Dai; Amjad Ali Syed; Xiang Yang Xu

Angular velocity dynamics identification of small unmanned helicopter using fuzzy model

Arbab Nighat Khizer^*, Ya Ping Dai, Amjad Ali Syed, Xiang Yang Xu

^*Corresponding author for this work

School of Automation

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane^©. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.

Original language	English
Pages (from-to)	527-533
Number of pages	7
Journal	Journal of Beijing Institute of Technology (English Edition)
Volume	23
Issue number	4
Publication status	Published - 1 Dec 2014

Keywords

Attitude model
Gradient method
Identification
Small unmanned helicopter (SUH)
Takagi-Sugeno (TS) fuzzy model

Cite this

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title = "Angular velocity dynamics identification of small unmanned helicopter using fuzzy model",

abstract = "Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane{\textcopyright}. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.",

keywords = "Attitude model, Gradient method, Identification, Small unmanned helicopter (SUH), Takagi-Sugeno (TS) fuzzy model",

author = "Khizer, {Arbab Nighat} and Dai, {Ya Ping} and Syed, {Amjad Ali} and Xu, {Xiang Yang}",

note = "Publisher Copyright: Beijing Institute of Technology.",

year = "2014",

month = dec,

day = "1",

language = "English",

volume = "23",

pages = "527--533",

journal = "Journal of Beijing Institute of Technology (English Edition)",

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publisher = "Beijing Institute of Technology",

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TY - JOUR

T1 - Angular velocity dynamics identification of small unmanned helicopter using fuzzy model

AU - Khizer, Arbab Nighat

AU - Dai, Ya Ping

AU - Syed, Amjad Ali

AU - Xu, Xiang Yang

N1 - Publisher Copyright: Beijing Institute of Technology.

PY - 2014/12/1

Y1 - 2014/12/1

N2 - Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane©. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.

AB - Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane©. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.

KW - Attitude model

KW - Gradient method

KW - Identification

KW - Small unmanned helicopter (SUH)

KW - Takagi-Sugeno (TS) fuzzy model

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JO - Journal of Beijing Institute of Technology (English Edition)

JF - Journal of Beijing Institute of Technology (English Edition)

IS - 4

ER -

Angular velocity dynamics identification of small unmanned helicopter using fuzzy model

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