CCE Faculty Articles
Identification of LPV Systems Using Successive Approximations
Document Type
Article
Publication Title
IEEE Conference on Decision and Control
Event Date/Location
Cancun, Mexico
ISSN
0191-2216
Publication Date
12-2008
Abstract
In this paper a successive approximation approach for MIMO linear parameter varying (LPV) systems with affine parameter dependence is proposed. This new approach is based on an algorithm previously introduced by the authors, which elaborates on a convergent sequence of linear deterministic-stochastic state-space approximations. In the previous algorithm the bilinear term between the time varying parameter vector and the state vector is allowed to behave as a white noise process when the scheduling parameter is a white noise sequence. However, this is a strong limitation in practice since, most often than not, the scheduling parameter is imposed by the process itself and it is typically a non white noise signal. In this paper, the bilinear term is analysed for non white noise scheduling sequences. It is concluded that its behaviour depends on the input sequence itself and it ranges from acting as an independent colored noise source, mostly removed by the identification algorithm, down to a highly input correlated signal that may be incorrectly assumed as being part of the system subspace. Based on the premise that the algorithm performance can be improved by the noise energy reduction, the bilinear term is expressed as a function of past inputs, scheduling parameters, outputs, and states, and the linear terms are included in a new extended input.
DOI
10.1109/CDC.2008.4738786
First Page
4509
Last Page
4515
NSUWorks Citation
Ramos, Jose A.; Lopes dos Santos, Paulo; and Martins de Carvalho, Jorge L., "Identification of LPV Systems Using Successive Approximations" (2008). CCE Faculty Articles. 399.
https://nsuworks.nova.edu/gscis_facarticles/399
