A Transformation Algorithm for Estimating System Laplace Transform from Sampled Data

The identification of continuous plants from sampled data is a technique commonly used. This method is normally divided into two parts: the determination of the discrete transfer function from the sampled data and the calculation of the continuous transfer function from the discrete one. An original method to perform the second part of this problem is described. The method, which establishes the minimum condition under which the continuous model can be obtained from the discrete one, has shown to have important advantages in the treatment of multiple poles. The method allows one to assume any temporal behavior of the input signal between sampling instants.