Review
Version 1
Preserved in Portico This version is not peer-reviewed
Structural Identification of Control Objects. Review
Version 1
: Received: 1 September 2023 / Approved: 4 September 2023 / Online: 5 September 2023 (05:05:17 CEST)
Version 2 : Received: 5 September 2023 / Approved: 6 September 2023 / Online: 6 September 2023 (09:45:35 CEST)
Version 2 : Received: 5 September 2023 / Approved: 6 September 2023 / Online: 6 September 2023 (09:45:35 CEST)
How to cite: Karabutov, N. Structural Identification of Control Objects. Review. Preprints 2023, 2023090171. https://doi.org/10.20944/preprints202309.0171.v1 Karabutov, N. Structural Identification of Control Objects. Review. Preprints 2023, 2023090171. https://doi.org/10.20944/preprints202309.0171.v1
Abstract
The structural identification (SI) problem of control objects has not been solved. The formalization and interpretation complexity of the structure concept is the main problem. In identification systems, the form of the model (its structure) choice is intuitive and bases on the experience and knowledge of the researcher in most cases. The task of parametric identification is often interpreted as SI. It introduces certain confusion in understanding of the task and decision-making. This is two different areas of research. The structural identification problem is multifaceted and includes many subtasks, and their solution gives the final result. Some tasks have been solved. The purpose of this work is to review existing approaches and methods to the structural identification problem of control objects from a system perspective. It is necessary to give the SI problem statement at the multiple-informational level to reflect the difficulties of formalizing SI. New directions to analyse that were not SI areas until now.
Keywords
excitation constancy; geometric structure; Lyapunov exponent; structural identification; structural identifiability; S-synchronization
Subject
Physical Sciences, Mathematical Physics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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