TY  - JOUR
KW  - System identi?cation; Piecewise a ne systems; Mixed-integer programming; Global optimization; Change detection; Wiener models
JF  - Automatica
EP  - 50
SP  - 37
VL  - 40
SN  - 0005-1098
AV  - none
ID  - eprints469
Y1  - 2004/01//
UR  - http://www.sciencedirect.com/science/article/pii/S000510980300270X
PB  - Elsevier
IS  - 1
TI  - Identification of piecewise affine systems via mixed-integer programming
A1  - Roll, Jacob
A1  - Bemporad, Alberto
A1  - Ljung, Lennart
N2  - This paper addresses the problem of identification of hybrid dynamical systems, by focusing the attention on hinging hyperplanes and Wiener piecewise affine autoregressive exogenous models, in which the regressor space is partitioned into polyhedra with affine submodels for each polyhedron. In particular, we provide algorithms based on mixed-integer linear or quadratic programming which are guaranteed to converge to a global optimum. For the special case where the estimation data only seldom switches between the different submodels, we also suggest a way of trading off between optimality and complexity by using a change detection approach.
ER  -