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System Identification for an Autonomous Quadrotor using Extended and Unscented Kalman Filters
Norafizah Abas,Ari Legowo,Rini Akmeliawati 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper presents aerodynamic parameters estimation techniques for an autonomous quadrotor through the implementation of Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). EKF and UKF have known to be typical estimation techniques used to estimate the state vectors and parameters of nonlinear dynamical systems. In this paper, three main processes are highlighted; dynamic modeling of the quadrotor, the implementation of EKF and the implementation of UKF algorithms. The aim is to identify and estimate the needed parameters for an autonomous quadrotor. The obtained results demonstrate the performances of EKF and UKF based on the flight test applied to the quadrotor system.