Title :
Using semidefinite programming for L1 identification of the ARX model
Author :
Kolumbán, S. ; Vajk, I.
Author_Institution :
Dept. of Autom. & Appl. Inf., Budapest Univ. of Technol. & Econ., Budapest, Hungary
Abstract :
Since system identification is closely related to control theory it is quite convenient that common tools of control may prove to be useful for identification as well. Semidefinite programming is now considered as a standard tool in control theory, however its applications for identification purposes are rare. This paper shows how L1 identification of the ARX model structure can be formulated as a semidefinite program. The way of incorporating a priori information into the identification process is demonstrated which necessitates the usage of semidefinite programming.
Keywords :
autoregressive processes; mathematical programming; ARX model; L1 identification; autoregressive model; semidefinite programming; Noise; Noise measurement; Optimization; Polynomials; Programming; Support vector machines; Symmetric matrices;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2010 11th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-9279-4
Electronic_ISBN :
978-1-4244-9280-0
DOI :
10.1109/CINTI.2010.5672269