The purpose of this work is to investigate the performance of the kinematic Kalman filter (KKF). In order to measure angular acceleration with a reliable and cost-effective method, Micro-Electro-Mechanical System MEMS accelerom- eters have been used. The estimated velocity has been implemented based on the model-based state estimation theory in order to compare the results with the KKF. In the model-based approaches, model parameters and external dis- turbance must be accurately known for the estimate of velocity to be accurate, which is very difficult in reality. The most attractive feature of KKF is that it is insensitive to modeling uncertainties and parameter variations

Velocity estimation and motion control using mems accelerometer

Fardin, Luca
2011/2012

Abstract

The purpose of this work is to investigate the performance of the kinematic Kalman filter (KKF). In order to measure angular acceleration with a reliable and cost-effective method, Micro-Electro-Mechanical System MEMS accelerom- eters have been used. The estimated velocity has been implemented based on the model-based state estimation theory in order to compare the results with the KKF. In the model-based approaches, model parameters and external dis- turbance must be accurately known for the estimate of velocity to be accurate, which is very difficult in reality. The most attractive feature of KKF is that it is insensitive to modeling uncertainties and parameter variations
2011-04-05
143
velocity estimation, motion control, MEMS, accelerometer, stima della velocità, controllo del moto, accelerometro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/14526