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Identification, Knowledge Engineering and Digital Modeling for Adaptive and Intelligent Control

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Free Download Identification, Knowledge Engineering and Digital Modeling for Adaptive and Intelligent Control by Natalia Bakhtadze, Igor Yadykin, Andrei Torgashov et al
English | PDF | 2023 | 262 Pages | ISBN : N/A | 14.2 MB
Starting our work on this Special Issue, we assumed that the research results presented here would reflect the solutions to various problems related to production management; however, the set of identified problems showed that their solutions could be useful for a wider range of applications. Therefore, we have presented 14 articles covering various aspects of the new trends in adaptive and intelligent control and identification.

The results of research on the theories and methodologies of identification are presented. New methods for solving the problems of parametric and non-parametric identification are proposed, and the possibilities of using data mining and knowledge engineering methods for identifying control systems and building digital models of dynamic processes in real time are studied. Various aspects of constructing intelligent control systems with an identifier and reinforcement learning are discussed and the possibilities of intelligent model predictive control and its application to control objects of various natures, as well as stability problems, are investigated. Approaches to building models of strategic decision making under informational control are also proposed.
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