Home > Research > Publications & Outputs > An Adaptive Scheme to Estimate Unknown Paramete...

Research

Associated organisational units

Electronic data

  • NIR_Conf_Russia

    Rights statement: ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Accepted author manuscript, 1.1 MB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Links

Text available via DOI:

View graph of relations

An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published

Standard

An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle. / Imran, Imil; Montazeri, Allahyar.
2020 International Conference Nonlinearity, Information and Robotics (NIR). IEEE, 2020. p. 1-6.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Imran, I & Montazeri, A 2020, An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle. in 2020 International Conference Nonlinearity, Information and Robotics (NIR). IEEE, pp. 1-6, Nonlinearity, Information, and Robotics, Innopolis, Russian Federation, 3/09/20. https://doi.org/10.1109/NIR50484.2020.9290205

APA

Imran, I., & Montazeri, A. (2020). An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle. In 2020 International Conference Nonlinearity, Information and Robotics (NIR) (pp. 1-6). IEEE. https://doi.org/10.1109/NIR50484.2020.9290205

Vancouver

Imran I, Montazeri A. An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle. In 2020 International Conference Nonlinearity, Information and Robotics (NIR). IEEE. 2020. p. 1-6 doi: 10.1109/NIR50484.2020.9290205

Author

Imran, Imil ; Montazeri, Allahyar. / An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle. 2020 International Conference Nonlinearity, Information and Robotics (NIR). IEEE, 2020. pp. 1-6

Bibtex

@inproceedings{74c5f6bfbea34d5e9ccdd12e614133e0,
title = "An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle",
abstract = "This paper deals with tracking control problem for six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV). A virtual control design using PD controller is proposed for tracking control position. The rotational dynamics of UAV is considered to have several unknown parameters suchas propeller inertia, rotational drag coefficient and an external disturbance parameter. To handle this issue, an adaptive scheme using the certainty equivalence principle is developed. The basic idea behind this scheme is to cancel the nonlinear term by applying a similar nonlinear structure in the feedback control design. The unknown parameters are replaced by estimated parameters generated by adaptation law. The rigorous theoretical design and simulation results are presented to demonstrate the effectiveness of the controller.",
author = "Imil Imran and Allahyar Montazeri",
note = "{\textcopyright}2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ; Nonlinearity, Information, and Robotics ; Conference date: 03-09-2020 Through 06-09-2020",
year = "2020",
month = dec,
day = "28",
doi = "10.1109/NIR50484.2020.9290205",
language = "English",
pages = "1--6",
booktitle = "2020 International Conference Nonlinearity, Information and Robotics (NIR)",
publisher = "IEEE",
url = "http://nir.innopolis.university/",

}

RIS

TY - GEN

T1 - An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle

AU - Imran, Imil

AU - Montazeri, Allahyar

N1 - ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2020/12/28

Y1 - 2020/12/28

N2 - This paper deals with tracking control problem for six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV). A virtual control design using PD controller is proposed for tracking control position. The rotational dynamics of UAV is considered to have several unknown parameters suchas propeller inertia, rotational drag coefficient and an external disturbance parameter. To handle this issue, an adaptive scheme using the certainty equivalence principle is developed. The basic idea behind this scheme is to cancel the nonlinear term by applying a similar nonlinear structure in the feedback control design. The unknown parameters are replaced by estimated parameters generated by adaptation law. The rigorous theoretical design and simulation results are presented to demonstrate the effectiveness of the controller.

AB - This paper deals with tracking control problem for six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV). A virtual control design using PD controller is proposed for tracking control position. The rotational dynamics of UAV is considered to have several unknown parameters suchas propeller inertia, rotational drag coefficient and an external disturbance parameter. To handle this issue, an adaptive scheme using the certainty equivalence principle is developed. The basic idea behind this scheme is to cancel the nonlinear term by applying a similar nonlinear structure in the feedback control design. The unknown parameters are replaced by estimated parameters generated by adaptation law. The rigorous theoretical design and simulation results are presented to demonstrate the effectiveness of the controller.

U2 - 10.1109/NIR50484.2020.9290205

DO - 10.1109/NIR50484.2020.9290205

M3 - Conference contribution/Paper

SP - 1

EP - 6

BT - 2020 International Conference Nonlinearity, Information and Robotics (NIR)

PB - IEEE

T2 - Nonlinearity, Information, and Robotics

Y2 - 3 September 2020 through 6 September 2020

ER -