• DocumentCode
    622042
  • Title

    LQG-based control of unmanned helicopter using OKID-based identification approach

  • Author

    El Ferik, Sami ; Omar, Hanafy M. ; Koesdwiady, Arief Barkah ; Al-Yazidi, Nezar M.

  • Author_Institution
    King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • fYear
    2013
  • fDate
    18-21 March 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents the system identification and control of an unmanned helicopter(UH) with ducted fan. The plant is an unstable multi-input-multi-output (MIMO) system. First, four identification methods have been considered in this work. Two of these methods studied the identification of the system as a set of transfer functions relating different inputs and outputs, namely the least square method with QR-factorization (LS-QR) and the recursive least square method (RLS). The other two methods are state-space identification method. Indeed, the classical subspace identification method and the observer-Kalman filter identification (OKID) method have been used to identify the system in state space representation. Analytical formulations of these methods as well as comparison of their performances based on their degree of fitness are presented for the special case of UH system. The results show that OKID out-performs the other methods. Based on this result, an OKID-LQGI-based controller for velocities tracking controller is proposed. The simulation results show excellent tracking performance.
  • Keywords
    Kalman filters; MIMO systems; aircraft control; autonomous aerial vehicles; identification; least squares approximations; linear quadratic Gaussian control; matrix decomposition; mobile robots; observers; recursive estimation; state-space methods; telerobotics; transfer functions; LQG-based control; LS-QR; MIMO system; OKID-LQGI-based controller; OKID-based identification approach; RLS; UH system; classical subspace identification method; ducted fan; fitness degree; least square method with QR-factorization; observer-Kalman filter identification method; recursive least square method; state space representation; state-space identification method; system identification; transfer functions; unmanned helicopter; unstable multiinput-multioutput system; velocities tracking controller; Equations; Kalman filters; Mathematical model; Noise; Observers; Rotors; Transfer functions; LQGI; Least-Square; OKID; QR-Factorization; Subspace; System Identification; Unmanned Helicopter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signals & Devices (SSD), 2013 10th International Multi-Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4673-6459-1
  • Electronic_ISBN
    978-1-4673-6458-4
  • Type

    conf

  • DOI
    10.1109/SSD.2013.6564105
  • Filename
    6564105