14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrA3.2

Onodera, Koichi (Mitsubishi Chemical Engineering Corp.), Emoto, Genichi (Mitsubishi Chemical Engineering Corp.), Qin, S. Joe (Univ. of Texas)

A New Subspace Identification Method for Closed-Loop Systems

Scheduled for presentation during the Invited Session "New Developments in Closed-Loop Subspace Identification" (FrA3), Friday, March 31, 2006, 10:50−11:10, Hunter Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Subspace Methods, Closed Loop Identification, Process Control


In this paper we present a new subspace identification method applicable to closed-loop data. First, Kalman predictor Markov parameters in a framework of ARX modeling with high order are obtained. These parameters are made available for subspace identification to help the estimation of the Hankel matrix which consists of the estimated predictor Markov parameters. To estimate the observer matrices, eigensystem realization algorithm (ERA) with weightings related to canonical correlation analysis (CCA) is applied to the Hankel matrix. System matrices are easily derived from the estimated observer matrices. We then demonstrate the effectiveness of the proposed algorithm via simulated and industrial closed loop data.