Velocity Estimation by Using Position and Acceleration Sensors

Knowledge of velocity is crucial to certain industrial applications involving high-bandwidth modeling and control. In conventional approaches, the velocities obtained from encoders or tachometers are quite noisy, and low-pass filters are usually engaged to generate usable velocity signals. The low-pass filter, however, causes significant phase lag that can severely affect both modeling and control accuracy in the mid- and high-frequency ranges. In this paper, two approaches using a combination of an encoder and an imperfect accelerometer are proposed to estimate velocities with high bandwidth. The two approaches, namely the two-channel approach and the observer-based approach, estimate velocities by applying proper frequency weightings to the encoder and accelerometer signals. The encoder mainly contributes to the low-frequency components of velocity estimation, and the accelerometer mainly contributes to the high-frequency components of velocity estimation. An adaptive mechanism for estimating the accelerometer gain is also presented. The effectiveness of the two velocity estimation approaches is verified experimentally with respect to a one-degree-of-freedom robot performing both rigid contact modeling and control. Extension to 3-D applications is discussed.