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F. Santoso, M. Liu and G. K. Egan, “Linear Quadratic Optimal Control Synthesis for an UAV,” 12th Australian International Aerospace Congress, AIAC12, Melbourne, 16-22 March 2007.

has been cited by the following article:

• TITLE: LQR Controller with Kalman Estimator Applied to UAV Longitudinal Dynamics

  AUTHORS: Chingiz Hajiyev, Sıtkı Yenal Vural

  KEYWORDS: Unmanned Air Vehicle; LQR Controller; Kalman Filter; Stability Analysis

  JOURNAL NAME: Positioning, Vol.4 No.1, February 27, 2013

  ABSTRACT: The aim of this study is designing an optimal controller with linear quadratic regulator (LQR) method for a small unmanned air vehicle (UAV). To better evaluate the effect of disturbances on the obtained measurements a Kalman filter is also used in the system. For this purpose a small UAV that is normally used as a radio controlled plane is chosen. The linearized equations for a wings level flight condition and the state space matrices are obtained. An optimal controller using LQR method to control the altitude level is then designed. The effect of the disturbances on the measurements are taken into account and the effectiveness of the Kalman filter in obtaining the correct measurements and achieving the desired control level are shown using the controller designed for the system. The small UAV is commanded to the desired altitude using the LQR controller through the control inputs elevator deflection and thrust rate. The LQR effectiveness matrices are chosen to find the gains necessary to build an effective altitude controller. Firstly the controller is tested under the situation where disturbances are absent. Then a Kalman filter is designed and the system under disturbances is tested with the designed controller and the filter. The results reveal the effectiveness of the Kalman filter and the LQR controller.