POWERFUL ALGORITHM FOR ADAPTIVE RECOGNITION OF DYNAMIC SYSTEM PARAMETERS

Objectives. The aim of this work is to propose an algorithm to solve the problem of adaptive identification of dynamic system parameters under uncertainty conditions with respect to drift parameters. Methods: Dynamic (temporal) characteristics are analyzed to form an image of adaptive systems in a turbulent atmosphere. The sterol parameter is calculated analytically based on the generalized Huygens-Kirchhoff principle. Results: The simulation result showed a fast approximation of the localized identification algorithms. Novelty: The proposed algorithm provides higher definition quality than the usual least squares weighted exponential method or competitive recognition algorithm.