Continuous-time model identification by using adaptive observer - Estimation of the initial state

Importance of the continuous-time model identification is increasing as the computer becomes faster. The main difference between the continuous-time model identification and the discrete-time model identification lies not only in the information loss incurred by sampling but also in the fact that the transient term must be taken into account in the continuous-time identification. This paper proposes a continuous-time model estimation method from sampled I/O data with the ZOH input assumption. The initial state of the plant is estimated by using a backward system of the plant. An upper bound of the plant degree is assumed to be known. Numerical example shows that the proposed method performs well as the conventional method with an initial state estimation.