A Time-Frequency Local Polynomial Approach to FRM Estimation from Incomplete Data

Abstract

Frequency Response Matrix (FRM) estimation from measured data is an important step towards the control of complex systems, including motion and thermal systems. Missing samples in the measured data records, e.g., due to sensor failure or faulty data transmission, often occur. In this paper, a method is presented for the nonparametric FRM identification of multiple-inputs multiple-outputs (MIMO) systems from incomplete and noisy data records. The method exploits time- and frequency-domain localizing wavelets to accurately estimate the FRM and its covariance from the time-frequency plane. Good performance is demonstrated in a simulation study.