Work

Iterative identification algorithm for tumor model using controlled ARMA model

Year: 2025

Type: article

Abstract: Since system identification of a tumor model is a primary need for controlling tumor model system, accessing suitable and applicable identification methods is a necessary object. In this paper, firstly, for estimating controlled auto-regressive moving average (CARMA) systems, two identification methods, namely generalized projection algorithm (GPA) and two-stage GPA (2S-GPA), are introduced and presented in order to estimate unknown parameters of a specific and vital tumor model. Furthermore, effectiveness of such methods, like convergence rate and estimation error, are discussed and considered. The introduced algorithms are simulated to prove these methods effectiveness, and data derived from the simulations are depicted through tables and figures.

Source: Åbo Akademi University Research Portal

DOI: 10.22124/jmm.2024.27240.2404

Authors: Sadeghi, Kiavash Hossein, Razminia, Abolhassan; id_orcid 0000-0001-5139-4255, Marashian, Arash

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7128690532

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