A bias-correction method for closed-loop identification of Linear Parameter-Varying systems. (January 2018)

• Record Type: Journal Article
• Authors: Mejari, Manas; Piga, Dario; Bemporad, Alberto
• Is Part Of: Automatica. Volume 87(2018)
• Page Start: 128
• Page End: 141
• Publication Date: 2018-01
• Subjects: Closed-loop identification -- Bias-corrected least squares -- LPV systems; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2017.09.014
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: Due to safety constraints and unstable open-loop dynamics, system identification of many real-world processes often requiresgathering data from closed-loop experiments. In this paper, we present a bias-correction scheme for closed-loop identification of Linear Parameter-Varying Input–Output (LPV-IO) models, which aims at correcting the bias caused by the correlation between the input signal exciting the process and output noise. The proposed identification algorithm provides a consistent estimate of the open-loop model parameters when both the output signal and the scheduling variable are corrupted by measurement noise. The effectiveness of the proposed methodology is tested in two simulation case studies.