Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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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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TY - CHAP
T1 - Sliding Mode Control Strategies for Maglev Systems Based on Kalman Filtering
AU - Diab, Mohammad
AU - Mercorelli, Paolo
AU - Haus, Benedikt
N1 - Conference code: 2
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Kalman filter
KW - Maglev system
KW - Sliding mode control
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85212970725&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-6714-4_7
DO - 10.1007/978-981-97-6714-4_7
M3 - Article in conference proceedings
AN - SCOPUS:85212970725
SN - 978-981-97-6713-7
T3 - Lecture Notes in Electrical Engineering
SP - 85
EP - 98
BT - Power Engineering and Intelligent Systems - Proceedings of PEIS 2024
A2 - Shrivastava, Vivek
A2 - Bansal, Jagdish Chand
A2 - Panigrahi, B.K.
PB - Springer Science and Business Media Deutschland
T2 - 2nd International Conference on Power Engineering and Intelligent Systems - PEIS 2024
Y2 - 16 March 2024 through 17 March 2024
ER -