Intelligent Control and Automation

Volume 14, Issue 1 (February 2023)

ISSN Print: 2153-0653   ISSN Online: 2153-0661

Google-based Impact Factor: 0.70  Citations  

Data-Driven Model Identification and Control of the Inertial Systems

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DOI: 10.4236/ica.2023.141001    175 Downloads   849 Views  Citations
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ABSTRACT

In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.

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Cojuhari, I. (2023) Data-Driven Model Identification and Control of the Inertial Systems. Intelligent Control and Automation, 14, 1-18. doi: 10.4236/ica.2023.141001.

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