Volume 15, Issue 7 · IJARST · ISSN 2319-1783 / 2320-1126

An Experimental Digital Twin Framework for Online State Estimation and Feedback Control of an Induction Motor Drive

An Experimental Digital Twin Framework for Online State Estimation and Feedback Control of an Induction Motor Drive is an open-access, peer-reviewed research paper by Darjon Dhamo, Aida Spahiu, Denis Panxhi, Genci Sharko and Nuri Rusta, published in Volume 15, Issue 7 of the International Journal of Advanced Research in Science and Technology (IJARST), a UGC-approved journal (Print ISSN 2319-1783, Online ISSN 2320-1126).

Author

Darjon Dhamo, Aida Spahiu, Denis Panxhi, Genci Sharko and Nuri Rusta

Abstract

The implementation of a Digital Twin for electric drives requires the combination of measurement synchronization, a realistic virtual model, state estimation, and feedback to the physical system. This paper describes an experimental realization of a Digital Twin for an induction motor fed by a variable frequency drive. The measured quantities, the three-line voltages, three-line currents, and encoder counts, are acquired on a PC using MATLAB. The measured signals are converted into physical units, despiked using causal robust filtering, transformed into the stationary reference frame, and synchronized across different sampling rates. Electrical and mechanical measurements are processed and synchronized at rates suitable for online Extended Kalman Filter (EKF) operation. The model consists of six states and works in the stationary reference frame, calculating the stator current, rotor flux components, rotor speed, and the load torque. A supervisory algorithm evaluates the estimated operating conditions and updates the inverter compensation parameter. The command is transmitted through Modbus TCP to adjust the inverter V/f characteristic within predefined limits. Experiments at 40 Hz and 45 Hz show that the estimator remains synchronized with the physical drive. The Digital Twin feedback improves rotor flux retention and maintains stable motor operation under changing operating conditions. These results show that the proposed system can perform the complete Digital Twin process, from online measurement and state estimation to the application of feedback commands to the induction motor drive.

DOI: https://doi.org/10.62226/ijarst20262748

References:

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DOI

https://doi.org/10.62226/ijarst20262748

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How do you cite this paper?

Darjon Dhamo, Aida Spahiu, Denis Panxhi, Genci Sharko and Nuri Rusta — “An Experimental Digital Twin Framework for Online State Estimation and Feedback Control of an Induction Motor Drive.” International Journal of Advanced Research in Science and Technology (IJARST), Volume 15, Issue 7. DOI: https://doi.org/10.62226/ijarst20262748.

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