In this paper, an identification algorithm for continuous-time systems is proposed. It provides the minimum state space realization of a plant directly from input-output data sampled at regular intervals. It needs the highorder derivatives of input-output signals, but to obtain them is known to be difficult in general. Therefore, a filter and its derivatives are introduced, and the output of the filters can be considered as the derivatives of intput-output. As the result, the precise derivatives of the input-output can be obtained as the output of the filters. If a low-pass filter is chosen as the filters, it can be expected that high-frequency noise is attenuated. Furthermore, the order of the needed derivatives is comparatively lower because this method is based on the Gopinath-Budin's realization algorithm for discrete-time systems. The accuracy of identification is also improved by introducing the input-output scaling and the instrumental variable. Comparing the proposed method with the existing works through numerical simulations, its effectiveness is verified.
