Bilinear State Space Systems for Nonlinear Dynamical Modelling

V. Verdult, M.H.G. Verhaegen

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    11 Citations (Scopus)


    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.
    Original languageUndefined
    Pages (from-to)1-9
    Number of pages9
    JournalTheory in biosciences
    Issue number1
    Publication statusPublished - 2000


    • System Identification
    • IR-74262
    • METIS-129125
    • Modelling
    • Nonlinear dynamics
    • Billinear systems

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