Please use this identifier to cite or link to this item:
Title: Adaptive estimation of discrete-time systems with nonlinear parameterization
Authors: Skantze, F.P.
Kojić, A.
Loh, A.-P. 
Annaswamy, A.M.
Issue Date: Dec-2000
Citation: Skantze, F.P., Kojić, A., Loh, A.-P., Annaswamy, A.M. (2000-12). Adaptive estimation of discrete-time systems with nonlinear parameterization. Automatica 36 (12) : 1879-1887. ScholarBank@NUS Repository.
Abstract: This paper concerns adaptive estimation of dynamic systems which are nonlinearly parameterized. A majority of adaptive algorithms employ a gradient approach to determine the direction of adjustment, which ensures stable estimation when parameters occur linearly. These algorithms, however, do not suffice for estimation in systems with nonlinear parameterization. We introduce in this paper a new algorithm for such systems and show that it leads to globally stable estimation by employing a different regression vector and selecting a suitable step size. Both concave/convex parameterizations as well as general nonlinear parameterizations are considered. Stable estimation in the presence of both nonlinear parameters and linear parameters which may appear multiplicatively is established. For the case of concave/convex parameterizations, parameter convergence is shown to result under certain conditions of persistent excitation.
Source Title: Automatica
ISSN: 00051098
DOI: 10.1016/S0005-1098(00)00106-0
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Oct 21, 2021


checked on Oct 14, 2021

Page view(s)

checked on Oct 14, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.