TY  - CHAP
ID  - eprints2443
EP  - 13929
SP  - 13924
TI  - Computational burden reduction in set-membership Hammerstein system identification
N2  - Hammerstein system identification from measurements affected by bounded noise is considered in the paper. First, we show that computation of tight parameter bounds requires the solution to nonconvex optimization problems where the number of decision variables increases with the length of the experimental data sequence. Then, in order to reduce the computational burden of the identification problem, we propose a procedure to relax the previously formulated problem to a set of polynomial optimization problems where the number of variables does not depend on the size of the measurements sequence. Advantages of the presented approach with respect to previously published results are discussed.
N1  - 18th IFAC World Congress, held in Milano (Italy), August 28- September 2nd 2011
AV  - public
SN  - 1474-6670
T2  - Proceedings of the 18th IFAC World Congress
KW  - Hammerstein systems
KW  -  Convex relaxation
KW  -  Parameters bounds
KW  -  Set-membership identification.
UR  - http://dx.doi.org/10.3182/20110828-6-IT-1002.02090
A1  - Cerone, Vito
A1  - Piga, Dario
A1  - Regruto, Diego
Y1  - 2011///
PB  - IFAC
ER  -