Robust system identification of continuous-time model from frequency response function data

This paper addresses the numerical conditioning problem that arises in the continuous-time system identification case. To solve this problem, a new frequency domain weighted least squares estimator using matrix orthogonal polynomial basis (MOPB) is proposed, which allow us to model transfer function matrix without vector operation, and yield perfect condition number. The key idea is to expand the matrix fraction description model on MOPB. The construction of MOPB is described in this paper and the efficacy of this method is illustrated with a numerical example.