Magnetic sensors have previously been used for position measurement only at very small distances between the magnet and the sensor. While they could potentially also be used at larger distances by exploiting nonlinear magnetic field functions, a serious challenge comes from magnetic disturbances. The presence of foreign ferromagnetic objects, variations in the Earth's magnetic field with location, and electromagnetic disturbances can cause such position estimation systems to have significant errors. This paper enables robust large-distance position estimation using redundant sensors and real-time disturbance estimation. Adaptive estimation algorithms that auto-calibrate magnetic parameters and compensate for disturbances are developed. Experimental results with a pneumatic cylinder demonstrate that sub-millimeter accuracies in position measurement can be obtained with such a system in spite of disturbances from external ferromagnetic objects. The developed sensing principle has a large number of applications, including position estimation in pneumatic cylinders, hydraulic actuators, spool valves, and many other machinery.
|Original language||English (US)|
|Number of pages||10|
|Journal||IEEE Sensors Journal|
|State||Published - Aug 1 2015|
Bibliographical notePublisher Copyright:
© 2001-2012 IEEE.
- Position estimation
- Robust estimation
- disturbance rejection
- extended Kalman filter
- magnetic sensors
- nonlinear least squares