Bilinear State Space Systems for Nonlinear Dynamical Modelling

Verdult, Vincent and Verhaegen, Michel (2000) Bilinear State Space Systems for Nonlinear Dynamical Modelling. Theory in Biosciences, 119 (1). pp. 1-9. ISSN 1431-7613

PDF
Restricted to UT campus only: Request a copy
69Kb

Abstract:	We discuss the identification of multiple input, multiple output, discrete-time bilinear state space systems. We consider two identification problems. In the first case, the input to the system is a measurable white noise sequence. We show that it is possible to identify the system by solving a nonlinear optimization problem. The number of parameters in this optimization problem can be reduced by exploiting the principle of separable least squares. A subspace-based algorithm can be used to generate initial estimates for this nonlinear identification procedure. In the second case, the input to the system is not measurable. This makes it a much more difficult identification problem than the case with known inputs. At present, we can only solve this problem for a certain class of single input, single output bilinear state space systems, namely bilinear systems in phase variable form.
Item Type:	Article
Copyright:	© 2000 Elsevier
Research Group:	Robotics and Mechatronics (CE)
Link to this item:	http://purl.utwente.nl/publications/74262
Official URL:	http://dx.doi.org/10.1078/1431-7613-00001
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page

Metis ID: 129125