Abstract
It is shown that linear multistep methods, commonly used to integrate ordinary differential equations numerically, can be used for the identification of linear continuous-time multivariable systems from samples of input/output data. An example problem is given to illustrate the use of multistep methods in system identification, and the results are compared with those obtained by the use of a discrete-time model.
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