Identification of linear continuous-time systems based on the signal projection

This paper presents a novel deterministic approach for the identification of linear continuous-time systems. The approach is based on the projection of measured signals onto the finite dimensional signal subspace whose basis is determined by the parameter structure of the target system model. In this paper, we describe the basic concept and implementation of the proposed identification framework, and develop the methodology to deal with multi-variable input and/or output case. In addition, the initial state estimation technique, which enables us to use the truncated I/O data for identification, is introduced. The important features of the proposed approach are (i) the ability to handle both open and closed loop systems in a unified way and (ii) the robustness against the measurement noise. These features are demonstrated through a numerical example.