TY - GEN
T1 - Basis-function optimization for subspace-based nonlinear identification of systems with measured-input nonlinearities
AU - Palanthandalam-Madapusi, Harish J.
AU - Hoagg, Jesse B.
AU - Bernstein, Dennis S.
PY - 2004
Y1 - 2004
N2 - For nonlinear systems with measured-input non-linearities, a subspace identification algorithm is used to identify the linear dynamics with the nonlinear mappings represented as a linear combination of basis functions. A selective-refinement technique and a quasi-Newton optimization algorithm are used to iteratively improve the representation of the system nonlinearity. For both methods, polynomials, splines, sigmoids, wavelets, sines and cosines, or radial basis functions can be used as basis functions. Both approaches can be used to identify nonlinear maps with multiple arguments and with multiple outputs.
AB - For nonlinear systems with measured-input non-linearities, a subspace identification algorithm is used to identify the linear dynamics with the nonlinear mappings represented as a linear combination of basis functions. A selective-refinement technique and a quasi-Newton optimization algorithm are used to iteratively improve the representation of the system nonlinearity. For both methods, polynomials, splines, sigmoids, wavelets, sines and cosines, or radial basis functions can be used as basis functions. Both approaches can be used to identify nonlinear maps with multiple arguments and with multiple outputs.
UR - https://www.scopus.com/pages/publications/8744280016
UR - https://www.scopus.com/pages/publications/8744280016#tab=citedBy
U2 - 10.1109/ACC.2004.182709
DO - 10.1109/ACC.2004.182709
M3 - Conference contribution
AN - SCOPUS:8744280016
SN - 0780383354
T3 - Proceedings of the American Control Conference
SP - 4788
EP - 4793
BT - Proceedings of the 2004 American Control Conference (AAC)
T2 - Proceedings of the 2004 American Control Conference (AAC)
Y2 - 30 June 2004 through 2 July 2004
ER -