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Closed-Loop Subspace System Identification

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The closed-loop subspace system identification (CLsysID) programme uses a data-driven system identification approach to identifying chemical processes using closed-loop operating data from univariate and multivariate processes. Subspace identification methods provide an alternative approach to the classical system identification methods such as the prediction error method (Ljung, 1999) and the instrument variable method (Söderström & Stoica, 1989). Subspace methods use efficient computational algorithms such as QR-factorisation or singular value decomposition (SVD), which makes them more numerically robust than the traditional approaches. Most subspace identification methods have been extended to deal with closed-loop system identification. A closed-loop subspace identification method was proposed in (Danesh Pour, Huang, & Shah, 2008) based on a joint input-output identification approach. An alternative formulation of this method with guaranteed consistency is described in (Huang & Kadali, 2008). The software is based on this algorithm.

The algorithm used by programme can be stated in the following steps:

Manual

The manual for using the toolbox can be found here.

System Requirements

This programme has the following prerequisites:

Download

The files can be downloaded from the Downloads section.

Developers

This software has been developed by the following people:

References