An Adaptive Identification Method Based on the Modulating Functions Technique and Exact State Observers for Modeling and Simulation of a Nonlinear Miso Glass Melting Process
| Autor: | Jȩdrzej Byrski, Michał Drapała, Witold Byrski |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science Applied Mathematics Process (computing) modulating functions 02 engineering and technology QA75.5-76.95 Adaptive identification Modeling and simulation Nonlinear system 020901 industrial engineering & automation Control theory glass forehearths Electronic computers. Computer science continuous systems 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) QA1-939 Glass melting 020201 artificial intelligence & image processing State (computer science) Engineering (miscellaneous) Mathematics system identification exact state observer |
| Zdroj: | International Journal of Applied Mathematics and Computer Science International Journal of Applied Mathematics and Computer Science, Vol 29, Iss 4, Pp 739-757 (2019) |
| ISSN: | 2083-8492 |
| DOI: | 10.2478/amcs-2019-0055 |
| Popis: | The paper presents new concepts of the identification method based on modulating functions and exact state observers with its application for identification of a real continuous-time industrial process. The method enables transformation of a system of differential equations into an algebraic one with the same parameters. Then, these parameters can be estimated using the least-squares approach. The main problem is the nonlinearity of the MISO process and its noticeable transport delays. It requires specific modifications to be introduced into the basic identification algorithm. The main goal of the method is to obtain on-line a temporary linear model of the process around the selected operating point, because fast methods for tuning PID controller parameters for such a model are well known. Hence, a special adaptive identification approach with a moving window is proposed, which involves using on-line registered input and output process data. An optimal identification method for a MISO model assuming decomposition to many inner SISO systems is presented. Additionally, a special version of the modulating functions method, in which both model parameters and unknown delays are identified, is tested on real data sets collected from a glass melting installation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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