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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Butcher, M. Masi, A. Martino, M. Tacchetti, A. |
| Copyright Year | 2012 |
| Description | Author affiliation: Engineering Department, CERN, Geneva 1211, Switzerland (Butcher, M.; Masi, A.) || Technology Department, CERN, Geneva 1211, Switzerland (Martino, M.) || CBCL, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 (Tacchetti, A.) |
| Abstract | In this paper the important practical issues of tuning and implementation of an Extended Kalman Filter for a sensorless hybrid stepper motor drive working with long cables is considered. A method to tune the filter using one set of data acquired from the real system is proposed. From this dataset, the system parameters and the Extended Kalman Filter's covariance matrices are estimated. The hardware and software implementation of the Extended Kalman Filter in the drive is also described, with specific emphasis on the code optimisation steps that are necessary to execute the filter at the desired sampling rate. Moreover, the developed drive's data acquisition capabilities and the experimental testbench used in the tuning and validation of the filter are discussed. Experimental results prove the effectiveness of the tuning method and implementation. |
| Starting Page | 2216 |
| Ending Page | 2222 |
| File Size | 518768 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781467301435 |
| e-ISBN | 9781467301428 |
| e-ISBN | 9781467301411 |
| DOI | 10.1109/ICElMach.2012.6350190 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-09-02 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Real time systems Motor drives Torque Parameter estimation Current measurement Noise Motors Covariance matrix Noise measurement Kalman filters Tuning |
| Content Type | Text |
| Resource Type | Article |
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