Modeling and System Identification using Extended Kalman Filter for a Quadrotor System
Quadrotor has emerged as a popular testbed for Unmanned Aerial Vehicle (UAV) research due to its simplicity in construction and maintenance,and its vertical take-off,landing and hovering capabilities.It is a flying rotorcraft that has four lift-generating propellers; two of the propellers rotate clockwise and the other two rotate counter-clockwise.This paper presents modeling and system identification for auto-stabilization of a quadrotor system through the implementation of Extended Kalman Filter (EKF).EKF has known to be typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems.In this paper,two main processes are highlighted; dynamic modeling of the quadrotor and the implementation of EKF algorithms.The aim is to obtain a more accurate dynamic modelby identify and estimate the needed parameters for thequadrotor.The obtained results demonstrate the performances of EKF based on the flight test applied to the quadrotor system.
Extended Kalman Filter (EKF) system identification quadrotor system
Norafizah Abas Ari Legowo Zulkiflie Ibrahim Norhidayah Rahim Anuar M.Kassim
Faculty of Electrical Engineering,UniversitiTeknikal Malaysia Melaka Kulliyyah of Engineering,International Islamic University Malaysia
国际会议
济南
英文
976-981
2012-12-29（万方平台首次上网日期，不代表论文的发表时间）