A closed loop system identification method is developed in which estimation bias from sensor noise and external disturbances is minimized. The method, based on the instrumental variables four step algorithm (IV4), uses three steps. The first step estimates a model using cross covariance calculations between the reference input signal and the control and measured output signals. The second step employs the prefilter identification process from the IV4 process. The third and final step uses the prefilter, the instrumental variables and the reference, control and output signals to estimate the final model. The method is demonstrated on a diesel engine where an open loop model relating fueling to engine speed is sought. The identification example is complicated by the presence of nonmeasurable external torque disturbances due to vehicle accessories.
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ASME 2008 Dynamic Systems and Control Conference
October 20–22, 2008
Ann Arbor, Michigan, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4335-2
PROCEEDINGS PAPER
Algorithm for Closed Loop System Identification Based on Data Correlation
H. Jammoussi,
H. Jammoussi
University of Houston, Houston, TX
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M. A. Franchek,
M. A. Franchek
University of Houston, Houston, TX
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K. Grigoriadis,
K. Grigoriadis
University of Houston, Houston, TX
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M. Books
M. Books
Cummins Inc., Columbus, IN
Search for other works by this author on:
H. Jammoussi
University of Houston, Houston, TX
M. A. Franchek
University of Houston, Houston, TX
K. Grigoriadis
University of Houston, Houston, TX
M. Books
Cummins Inc., Columbus, IN
Paper No:
DSCC2008-2162, pp. 433-438; 6 pages
Published Online:
June 29, 2009
Citation
Jammoussi, H, Franchek, MA, Grigoriadis, K, & Books, M. "Algorithm for Closed Loop System Identification Based on Data Correlation." Proceedings of the ASME 2008 Dynamic Systems and Control Conference. ASME 2008 Dynamic Systems and Control Conference, Parts A and B. Ann Arbor, Michigan, USA. October 20–22, 2008. pp. 433-438. ASME. https://doi.org/10.1115/DSCC2008-2162
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