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Control and estimation with threshold sensing for Inertial Measurement Unit calibration using a piezoelectric microstage

A threshold sensing strategy for improving measurement accuracy of a piezoelectric microactuator in calibration of miniature Inertial Measurement Units (IMUs) is presented. An asynchronous threshold sensor is hypothesized as a way to improve state estimates obtained from analog sensor measurements of microactuator motion. To produce accurate periodic signals using the proposed piezoelectric actuator and sensing arrangement, an Iterative Learning Control (ILC) is employed. Three sensing strategies: (i) an analog sensor alone with a Kalman filter; (ii) an analog sensor and threshold sensor with a Kalman filter; and (iii) an analog sensor and threshold sensor with a Kalman smoother are compared in simulation and single-axis experiments. Results show that incorporating threshold sensors in a projected low-noise environment based on capacitive sensing will produce high-accuracy velocity measurements at certain fixed angles, while experimental testing with less reliable piezoelectric sensing shows improved estimation accuracy at all velocities and positions.