Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering

Mohammad Diab; Paolo Mercorelli; Benedikt Haus

doi:10.1007/978-981-97-6714-4_7

Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering

Mohammad Diab
, Paolo Mercorelli^*
, Benedikt Haus

^*Corresponding author for this work

Leuphana University of Lüneburg

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Abstract

This paper presents the control of a magnetic levitation (Maglev) system using sliding mode control (SMC) and a Backstepping-based variant. The Maglev system considered in this paper has no sensor for measuring the velocity, which is necessary for the application of SMC. For that reason, a Kalman filter is derived to optimally estimate this state variable, effectively rendering this a speed-sensorless approach. Both controllers are evaluated and compared based on extensive simulation studies, with and without additive disturbances, in order to compare their robustness regarding this aspect.

Original language	English
Title of host publication	Power Engineering and Intelligent Systems - Proceedings of PEIS 2024
Editors	Vivek Shrivastava, Jagdish Chand Bansal, B.K. Panigrahi
Number of pages	14
Publisher	Springer Science and Business Media Deutschland
Publication date	2024
Pages	85-98
ISBN (Print)	978-981-97-6713-7
ISBN (Electronic)	978-981-97-6714-4
DOIs	https://doi.org/10.1007/978-981-97-6714-4_7
Publication status	Published - 2024
Event	2nd International Conference on Power Engineering and Intelligent Systems - PEIS 2024 - Srinagar, India Duration: 16.03.2024 → 17.03.2024 Conference number: 2 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=176808&copyownerid=182588

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Research areas and keywords

Kalman filter
Maglev system
Sliding mode control
Engineering

Access to Document

10.1007/978-981-97-6714-4_7

Cite this

Diab, M., Mercorelli, P., & Haus, B. (2024). Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering. In V. Shrivastava, J. C. Bansal, & B. K. Panigrahi (Eds.), Power Engineering and Intelligent Systems - Proceedings of PEIS 2024 (pp. 85-98). (Lecture Notes in Electrical Engineering; Vol. 1247 LNEE). Springer Science and Business Media Deutschland. https://doi.org/10.1007/978-981-97-6714-4_7

Diab, Mohammad ; Mercorelli, Paolo ; Haus, Benedikt. / Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering. Power Engineering and Intelligent Systems - Proceedings of PEIS 2024. editor / Vivek Shrivastava ; Jagdish Chand Bansal ; B.K. Panigrahi. Springer Science and Business Media Deutschland, 2024. pp. 85-98 (Lecture Notes in Electrical Engineering).

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abstract = "This paper presents the control of a magnetic levitation (Maglev) system using sliding mode control (SMC) and a Backstepping-based variant. The Maglev system considered in this paper has no sensor for measuring the velocity, which is necessary for the application of SMC. For that reason, a Kalman filter is derived to optimally estimate this state variable, effectively rendering this a speed-sensorless approach. Both controllers are evaluated and compared based on extensive simulation studies, with and without additive disturbances, in order to compare their robustness regarding this aspect.",

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Diab, M, Mercorelli, P & Haus, B 2024, Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering. in V Shrivastava, JC Bansal & BK Panigrahi (eds), Power Engineering and Intelligent Systems - Proceedings of PEIS 2024. Lecture Notes in Electrical Engineering, vol. 1247 LNEE, Springer Science and Business Media Deutschland, pp. 85-98, 2nd International Conference on Power Engineering and Intelligent Systems - PEIS 2024, Srinagar, India, 16.03.24. https://doi.org/10.1007/978-981-97-6714-4_7

Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering. / Diab, Mohammad; Mercorelli, Paolo ; Haus, Benedikt.
Power Engineering and Intelligent Systems - Proceedings of PEIS 2024. ed. / Vivek Shrivastava; Jagdish Chand Bansal; B.K. Panigrahi. Springer Science and Business Media Deutschland, 2024. p. 85-98 (Lecture Notes in Electrical Engineering; Vol. 1247 LNEE).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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