A Non-integer high-order sliding mode control of induction motor with machine learning-based speed observer

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A Non-integer high-order sliding mode control of induction motor with machine learning-based speed observer

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Sami, Irfan / Ullah, Shafaat / Ullah, Shafqat / Bukhari, Syed Sabir Hussain / Ahmed, Naseer / Salman, Muhammad / Ro, Jong-Suk

Abstract

The induction motor (IM) drives are prone to various uncertainties, disturbances, and non-linear dynamics. A high-performance control system is essential in the outer loop to guarantee the accurate convergence of speed and torque to the required value. Super-twisting sliding mode control (ST-SMC) and fractional-order calculus have been widely used to enhance the sliding mode control (SMC) performance for IM drives. This paper combines the ST-SMC and fractional-order calculus attributes to propose a novel super-twisting fractional-order sliding mode control (ST-FOSMC) for the outer loop speed control of the model predictive torque control (MPTC)-based IM drive system. The MPTC of the IM drive requires some additional sensors for speed control. This paper also presents a novel machine learning-based Gaussian Process Regression (GPR) framework to estimate the speed of IM. The GPR model is trained using the voltage and current dataset obtained from the simulation of a three-phase MPTC based IM drive system. The performance of the GPR-based ST-FOSMC MPTC drive system is evaluated using various test cases, namely (a) electric fault incorporation, (b) parameter perturbation, and (c) load torque variations in Matlab/Simulink environment. The stability of ST-FOSMC is validated using a fractional-order Lyapunov function. The proposed control and estimation strategy provides effective and improved performance with minimal error compared to the conventional proportional integral (PI) and SMC strategies.

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Dokumentinformationen

Titel :

A Non-integer high-order sliding mode control of induction motor with machine learning-based speed observer

Beteiligte:

Sami, Irfan (Autor:in) / Ullah, Shafaat (Autor:in) / Ullah, Shafqat (Autor:in) / Bukhari, Syed Sabir Hussain (Autor:in) / Ahmed, Naseer (Autor:in) / Salman, Muhammad (Autor:in) / Ro, Jong-Suk (Autor:in) / Sami, Irfan / Ullah, Shafaat / Ullah, Shafqat

Erscheinungsdatum :

2023-01-01

DOI :

https://doi.org/10.3390/machines11060584

Medientyp :

Aufsatz (Zeitschrift)

Format :

Elektronische Ressource

Sprache :

Englisch

Schlagwörter :

sliding mode control , induction motor , observer , artificial intelligence