Abstract
Several methods for the identification of linear multivariable continuous-time systems from the samples of input-output data are discussed. These include three new methods proposed by the authors. The suitability of these methods for estimating the parameters of the system using recursive least-squares algorithm is compared using a simulated example. The results indicate that the best results are obtained using the block pulse function method as proposed by the authors.
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