Subspace identification for nonlinear systems that are linear in unmeasured states
作者： S.L. Lacy , D.S. Bernstein
关键词:
摘要: In this paper, we apply subspace methods to the identification of a class multi-input multi-output (MIMO) discrete-time nonlinear time-varying systems. Specifically, study systems that are in measured data and linear unmeasured states. We present numerical simulations demonstrate efficacy method.
sci-hub.se 参考文章(17)
Jer-Nan Juang, Applied system identification ,(1994)
Peter van Overschee, Bart L. R. de Moor, Subspace Identification for Linear Systems: Theory - Implementation - Applications ,(2011)
W.E. Larimore, Generalized canonical variate analysis of nonlinear systems conference on decision and control. pp. 1720- 1725 ,(1988) , 10.1109/CDC.1988.194622
Lennart Ljung, System Identification: Theory for the User ,(1987)
T.H. Van Pelt, D.S. Bernstein, Nonlinear system identification using Hammerstein and nonlinear feedback models with piecewise linear static maps. 1. Theory american control conference. ,vol. 1, pp. 225- 229 ,(2000) , 10.1109/ACC.2000.878840
Marc Moonen, Bart De Moor, Lieven Vandenberghe, Joos Vandewalle, On- and off-line identification of linear state-space models International Journal of Control. ,vol. 49, pp. 219- 232 ,(1989) , 10.1080/00207178908559631
Torben Knudsen, Brief Consistency analysis of subspace identification methods based on a linear regression approach Automatica. ,vol. 37, pp. 81- 89 ,(2001) , 10.1016/S0005-1098(00)00125-4
Lennart Ljung, Tomas McKelvey, Subspace identification from closed loop data Signal Processing. ,vol. 52, pp. 209- 215 ,(1996) , 10.1016/0165-1684(96)00054-0
David Westwick, Michel Verhaegen, Identifying MIMO Wiener systems using subspace model identification methods Signal Processing. ,vol. 52, pp. 235- 258 ,(1996) , 10.1016/0165-1684(96)00056-4
Peter Van Overschee, Bart De Moor, A unifying theorem for three subspace system identification algorithms Automatica. ,vol. 31, pp. 1853- 1864 ,(1995) , 10.1016/0005-1098(95)00072-0