The ADAPT x Software for Automated Multivariable System Identification

Abstract The ADAPTX software is a recently developed technology for the automatic identification or modeling of multivariable systems from observational input/output data. It has been applied to a number of difficult industrial applications resulting in major improvements. This paper describes the software, the extensive theory upon which it is based, and a number of major applications. This technology involves the identification of linear, time invariant dynamical processes with noise disturbances and possible feedback and includes determination of the system state order. The ADAPTX software package is available running under Matlab versions 4.2, 5.2 and 5.3 on Unix workstations and Windows or Macintosh computers. A C++ package is also available for UNIX workstations and Windows computers. The basic method involves a canonical variate analysis (CVA) that, for each potential state order, gives an optimal statistical selection of the system states. The computation involves primarily a singular value decomposition that is always computationally stable and accurate. For model state order selection, an optimal statistical procedure is used, namely a small sample version of the Akaike information criterion (AIC). The resulting procedure is completely automatic and suitable for online identification of high-order systems.

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