Simulation Study on State Estimation for a Quadrotor Generalized Attitude Model

Abstract

This paper studies the state estimation of a quadrotor yaw-channel generalized attitude model (GAM) using the subspace identification based state estimation method under the conditions that the measurements for the control quantity and the output attitude angle are corrupted with disturbing noises and that there are no available models. The quadrotor attitude control loop for the yaw-channel is first designed by MATLAB using an observer based state feedback law. A high-order coprime factor (CF) model for the GAM is then identified from simulation data by the subspace identification method. Next, the estimation states for the GAM can be given by the similarity transform and the relations between the GAM and its CF model. Finally, the efficacy of the presented state estimation procedure and the accuracy of the state estimation are verified.