LAPSE:2023.30117
Published Article

LAPSE:2023.30117
Enhanced Model Reference Adaptive Control Scheme for Tracking Control of Magnetic Levitation System
April 14, 2023
Abstract
Magnetic Levitation is a process in which an object is suspended with the support of the magnetic field. Despite being an unstable system, Magnetic Levitation Systems (MAGLEV) have profound applications in various fields of engineering. MAGLEV systems are sensitive, unstable, and nonlinear and uncertainties always pose a challenge in Controller Design. As a solution, adaptive controllers came into existence with adaptation mechanisms to cover the system uncertainties. In this study, a simple, novel, and an effective approach to the Enhanced Adaptive Control scheme is proposed for the ball position control and tracking of an unstable Magnetic Levitation System. The proposed Enhanced Model Reference Adaptive Scheme (EMRAC) follows the same phenomenon of the Model Reference Adaptive Scheme (MRAC) with a slight difference in its control strategy. The proposed scheme consists of Proportional-Integral-Velocity plus Feed Forward as the control structure and a modified version of the standard tuning rule is used as the adaptation mechanism. The control scheme is applied to a standard benchmark Magnetic Levitation System and the tracking performance of the scheme is tested by applying square and multi-sine pattern trajectories to the Magnetic Levitation System. The performance of the developed Enhanced MRAC performance is compared with that of the Proportional Integral Velocity with Feedforward Control (PIV+FF) scheme and the proposed control scheme is proven to be more suitable. The performance of the proposed scheme is also analyzed with Power Spectral Density and Root Mean Square Error to evaluate the ball position tracking control. It is inferred from the experimental results that Enhanced MRAC accommodates the changes and makes the system more reliable with good tracking ability.
Magnetic Levitation is a process in which an object is suspended with the support of the magnetic field. Despite being an unstable system, Magnetic Levitation Systems (MAGLEV) have profound applications in various fields of engineering. MAGLEV systems are sensitive, unstable, and nonlinear and uncertainties always pose a challenge in Controller Design. As a solution, adaptive controllers came into existence with adaptation mechanisms to cover the system uncertainties. In this study, a simple, novel, and an effective approach to the Enhanced Adaptive Control scheme is proposed for the ball position control and tracking of an unstable Magnetic Levitation System. The proposed Enhanced Model Reference Adaptive Scheme (EMRAC) follows the same phenomenon of the Model Reference Adaptive Scheme (MRAC) with a slight difference in its control strategy. The proposed scheme consists of Proportional-Integral-Velocity plus Feed Forward as the control structure and a modified version of the standard tuning rule is used as the adaptation mechanism. The control scheme is applied to a standard benchmark Magnetic Levitation System and the tracking performance of the scheme is tested by applying square and multi-sine pattern trajectories to the Magnetic Levitation System. The performance of the developed Enhanced MRAC performance is compared with that of the Proportional Integral Velocity with Feedforward Control (PIV+FF) scheme and the proposed control scheme is proven to be more suitable. The performance of the proposed scheme is also analyzed with Power Spectral Density and Root Mean Square Error to evaluate the ball position tracking control. It is inferred from the experimental results that Enhanced MRAC accommodates the changes and makes the system more reliable with good tracking ability.
Record ID
Keywords
adaptive, control, levitation, magnetic
Subject
Suggested Citation
Gopi RS, Srinivasan S, Panneerselvam K, Teekaraman Y, Kuppusamy R, Urooj S. Enhanced Model Reference Adaptive Control Scheme for Tracking Control of Magnetic Levitation System. (2023). LAPSE:2023.30117
Author Affiliations
Gopi RS: Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India [ORCID]
Srinivasan S: Vellore Institute of Technology, School of Electrical Engineering, Vellore 632014, India
Panneerselvam K: Vellore Institute of Technology, School of Electrical Engineering, Vellore 632014, India
Teekaraman Y: MOBI-Mobility, Logistics and Automotive Technology Research Centre, EVERGi, Vrije Universiteit Brussels, 1050 Ixelles, Belgium [ORCID]
Kuppusamy R: Department of Electrical and Electronics Engineering, Sri Sairam College of Engineering, Bangalore 562106, India
Urooj S: Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, Riyadh 84428, Saudi Arabia [ORCID]
Srinivasan S: Vellore Institute of Technology, School of Electrical Engineering, Vellore 632014, India
Panneerselvam K: Vellore Institute of Technology, School of Electrical Engineering, Vellore 632014, India
Teekaraman Y: MOBI-Mobility, Logistics and Automotive Technology Research Centre, EVERGi, Vrije Universiteit Brussels, 1050 Ixelles, Belgium [ORCID]
Kuppusamy R: Department of Electrical and Electronics Engineering, Sri Sairam College of Engineering, Bangalore 562106, India
Urooj S: Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, Riyadh 84428, Saudi Arabia [ORCID]
Journal Name
Energies
Volume
14
Issue
5
First Page
1455
Year
2021
Publication Date
2021-03-07
ISSN
1996-1073
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Original Submission
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PII: en14051455, Publication Type: Journal Article
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LAPSE:2023.30117
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https://doi.org/10.3390/en14051455
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