An Experimental Study of the Empirical Identification Method to Infer an Unknown System Transfer Function

Identification is considered a very important procedure, within the control area, to estimate the best-possible approximate model among different designs. Its significance comes from the fact that more than 75% of the cost associated with an advanced control project is aimed at obtaining a precise m...

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Bibliographic Details
Published in:Robotics (Basel) 2023-10, Vol.12 (5), p.140
Main Authors: Gonzalez-Villagomez, Jacob, Gonzalez-Villagomez, Esau, Rodriguez-Donate, Carlos, Cabal-Yepez, Eduardo, Ledesma-Carrillo, Luis Manuel, Hernández-Gómez, Geovanni
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Approximation
Control theory
Controllers
Empirical analysis
experimental identification method
experimental study
Identification
Identification methods
Mathematical models
Methods
PID control tuning
Proportional integral derivative
Robots
Step response
system transfer function inference
Transfer functions
unknown system transfer function
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Summary:Identification is considered a very important procedure, within the control area, to estimate the best-possible approximate model among different designs. Its significance comes from the fact that more than 75% of the cost associated with an advanced control project is aimed at obtaining a precise mathematical modeling. Therefore, in this work, an exhaustive analysis was carried out to determine the appropriate input stimulus for an unknown real system that must be controlled, with the aim of accurately estimating its transfer function (TF) using the empirical identification method (gray-box). The analysis was performed quantitatively by means of three tests: (i) the PID controller step response was evaluated theoretically; (ii) the controller performance was assessed in a Cartesian robot by tracking a trajectory defined through a Gaussian acceleration profile; (iii) the efficiency of the determined input stimulus with the best performance on inferring the TF for the system to be controlled was verified by assessing its operation in a real system, through repeatability tests, utilizing the integral errors.
ISSN:2218-6581
2218-6581
DOI:10.3390/robotics12050140