Using steady-state prior knowledge to constrain parameter estimates in nonlinear system identification
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications - Tập 49 Số 9 - Trang 1376-1381 - 2002
Tóm tắt
This work investigates the use of prior knowledge in the parameter estimation of NARMAX polynomial models. The problem of parameter estimation is then formulated in such a way that the estimated models have specified features. This formulation results in a constrained optimization problem, which is solved using the ellipsoid algorithm. This technique is applied to a real DC-DC buck converter. In this system, the static relation is known from the theory but identification data are located over a rather narrow range around an operating point. Although obtained from dynamical data, the models provide good approximation to the nonlinear static function.
Từ khóa
#Steady-state #Parameter estimation #Nonlinear systems #Polynomials #Stability #Constraint optimization #Ellipsoids #Buck converters #Least squares approximation #Yield estimationTài liệu tham khảo
korenberg, 1985, orthogonal identification of nonlinear difference equation models, Mid West Symp Circuits and Systems
10.1080/00207178808906169
10.1080/0020718508961129
ogata, 1995, Discrete-Time Control Systems
10.1002/aic.690440114
10.1109/20.767367
sjöberg, 1995, nonlinear back-box modeling in system identification: a unified overview, Automatica, 31, 1691, 10.1016/0005-1098(95)00120-8
suykens, 1997, <formula><tex>${\rm nl}_{q}$</tex></formula> theory: checking and imposing stability of recurrent neural networks for nonlinear modeling, IEEE Transactions on Signal Processings, 45, 2682, 10.1109/78.650094
10.1016/0005-1098(93)90124-C
10.1016/0009-2509(74)80089-8
10.1049/ip-cta:20020398
10.1049/ip-cta:19982112
10.1287/opre.29.6.1039
10.1080/00207728808964057
10.1007/BFb0121078
10.1080/00207178908953472
10.1109/81.855463
10.1080/00207179508921557
10.1016/0005-1098(95)00146-8