Control Systems and Optimization Letters
Vol 2, No 3 (2024)

Hybrid Adaptive Backstepping Sliding Mode Controller of Permanent Magnet Linear Synchronous Motors

Maamar, Yahiaoui (Unknown)
Alnami, Hashim (Unknown)
Elzein, I. M. (Unknown)
Benameur, Afif (Unknown)
Brahim, Brahimi (Unknown)
Mohamed, Horch (Unknown)
Mahmoud, Mohamed Metwally (Unknown)



Article Info

Publish Date
24 Dec 2024

Abstract

This paper tackles the tracking position control dilemma of permanent magnet linear synchronous motors with parameter uncertainties and load force disturbance. Adaptive nonlinear backstepping control augmented with sliding mode control (SMC) is proposed to solve the problem of load force distribution. The backstepping is a recursive control technique where its stability is ensured at each step. However, its sensitivity to uncertainties, disturbances, and electromagnetic noise leads to unwanted performances. SMC is a well-known nonlinear robust approach for uncertain dynamical systems and reduces its parametric adaptive laws.  However, implementing this technique in real-time applications is stopped by its main shortcoming, the undesirable chattering phenomenon.  The saturation function is used to reduce the chattering phenomenon.  The incorporation of these approaches is a promising solution to provide a suitable position tracking of PMLSM in the presence of parameter uncertainties and load force disturbance. The simulation tests have been performed on the PMLSM system to prove the effectiveness and robustness of the proposed controller law.  The results highlighted satisfactory position tracking performance in transient conditions and steady-state and under different load force disturbances.

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Journal Info

Abbrev

csol

Publisher

Subject

Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Description

Control Systems and Optimization Letters is an open-access journal offering authors the opportunity to publish in all fundamental and interdisciplinary areas of control and optimization, rapidly enabling a safe and sustainable interconnected human society. Control Systems and Optimization Letters ...