Improvement of Attitude Estimation Using Modified Rodrigues Parameters and Intelligent Controller

Abstract

The attitude estimation method of attitude heading reference system (AHRS) using an Extended Kalman Filter (EKF) with a filter tuning algorithm based on fuzzy controller is introduced.The AHRS uses inertial sensors and magnetometers to calculate its attitude. It is known that the attitude update using gyros are prone to diverge and hence the attitude error needs to compensate using accelerometers and magnetometers. In this paper, a Kalman filter model with a state variables represented by Modified Rodrigues Parameters (MRP) is presented to improve the computational efficiency and a model changing algorithm is used to make the filter more robust to acceleration and magnetic disturbances.If the AHRS measures any disturbances which are caused by movement of the vehicle, using fuzzy controller changes the filter gain .Simulation results show, EKF tuned by fuzzy controller is correct method that makes robust to disturbances more properly ,Rodrigues parameters can improve the computational efficiency..