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Title: Nonlinear Model Identification of a Ball and Beam Mechanism using Experimental Data
Authors: Abedinifar, M.
Ertuǧrul, S.
Argüz, S.H.
Keywords: Nonlinear systems
Statistical tests
Ball and beam
Beam mechanism
Dead time
Dead zones
In-laboratory experiments
Mechanism mathematical model
Nonlinear friction
Nonlinear model identification
Particle swarm optimization algorithm
Particle swarm optimization (PSO)
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: A ball and beam mechanism is widely utilized in laboratory experiments to demonstrate the behavior of more complex systems. In this research, the phenomena such as nonlinear frictions, dead-zone and time-delay in the ball and beam mechanism's mathematical model is investigated. The following procedures are taken to construct a credible mathematical model of the system for this purpose. Firstly, the ball and beam mechanism's mathematical model, which includes different probable physically meaningful nonlinearities, is simulated using MATLAB\Simulink. Then, the Particle Swarm Optimization (PSO) algorithm is coded to determine the exact nonlinear model of a ball and beam system using the experimental data. Third, the accuracy of the results obtained from the PSO algorithm is tested using the hypothesis test and the confidence interval test. According to the statistical tests, the PSO algorithm is highly accurate in determining the parameters of the actual model of the system. © 2023 IEEE.
Description: IEEE;LISIER;Sapienza Universita di Roma
9th International Conference on Control, Decision and Information Technologies, CoDIT 2023 -- 3 July 2023 through 6 July 2023 -- 193871
ISBN: 9798350311402
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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