Identification methods based on associative search procedure

• Autorzy: Bakhtadze N. N. , Kulba V. V. , Yadikin I. B. , Lototsky V. A. , Maximov E. M.
• Języki publikacji: EN

Abstrakty

EN

In modern control systems, identification is an integral part of adaptive control where process models are adjusted using real-time operation data and control actions optimal with respect to some performance criterion are developed. A variety of identification methods based on mathematical statistics techniques have been developed. Algorithms optimal for certain classes of objects and external disturbances were categorized dependent on the available a priori information about the control object. The limits of approximating models development and application were outlined. Against this background, the paper presents novel associative search techniques enabling the development of a new dynamic object's model on each time step rather than plant approximation pertaining to time. The model is build using the data samples from process history (associations) developed at the learning phase. The new techniques employs the models of human individual's (process operator's, stock analyst's or trader's) behavior based on professional knowledge formalization. Application examples from oil refining and chemical industries, power engineering, and banking are adduced.

Słowa kluczowe

EN

process identification; knowledge base; associative search models; soft sensors

PL

proces identyfikacji; baza wiedzy; model wyszukiwania asocjacyjny

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2011
• Tom: Vol. 2, No. 3
• Strony: 6--18
• Opis fizyczny: Bibliogr. 22 poz., rys.

Twórcy

autor

Bakhtadze N. N.

autor

Kulba V. V.

autor

Yadikin I. B.

autor

Lototsky V. A.

autor

Maximov E. M.

• V.A. Trapeznikov Institute of Control Sciences, 65 Profsoyuznaya St., 17997 Moscow, Russia, phone: [phone],

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