Voltage sags was a common power system disturbance, usually associated with power system faults. Nowadays, there were more and more methods to detect voltage sag, involving with RMS, peak voltage detect, FFT. Owing to their defections, they were too slow when they came to being applied to detect voltages sags. This paper presents a method based on wavelet energy entropy detection voltage sags, this method can detect the drop time quickly and sensitively. In order to verify the feasibility of the proposed method, a numerical example simulation has been done based on matlab / simulink , results show that there is a significant effect.
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..
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