A novel threshold sensing strategy for improving accuracy of a tracking controller used in calibration of an Inertial Measurement Unit (IMU) with a piezoelectric micro-actuator is presented in this paper. An asynchronous threshold sensor is hypothesized as a way to improve state estimates obtained from analog sensor measurements of micro-actuator motion. In order to produce accurate periodic signals using the proposed piezoelectric actuator and sensing arrangement, an Iterative Learning Control (ILC) is employed for control system design. 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. Results show that incorporating threshold sensors into the piezoelectric micro-actuation system should allow at least certain angular positions or rates to be known with much higher accuracy than from analog sensing alone, which can be useful for identifying calibration curves from the linear region of IMU operation.
- Dynamic Systems and Control Division
An Iterative Learning Controller for High Precision Calibration of an Inertial Measurement Unit Using a Piezoelectric Platform
- Views Icon Views
- Share Icon Share
- Search Site
Edamana, B, & Oldham, K. "An Iterative Learning Controller for High Precision Calibration of an Inertial Measurement Unit Using a Piezoelectric Platform." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control. Palo Alto, California, USA. October 21–23, 2013. V003T37A004. ASME. https://doi.org/10.1115/DSCC2013-3974
Download citation file: