Model-based real-time control of a magnetic manipulator system

Jan Willem Damsteeg; Subramanya P. Nageshrao; Robert Babuška

doi:10.1109/CDC.2017.8264140

Model-based real-time control of a magnetic manipulator system

Jan Willem Damsteeg, Subramanya P. Nageshrao, Robert Babuška

Learning & Autonomous Control

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

Abstract

Precise magnetic manipulation has numerous applications, ranging from manufacturing to the medical field. Owing to the nonlinear nature of the electromagnetic force, magnetic manipulation requires advanced nonlinear control. In this paper, we design and experimentally evaluate two nonlinear controllers for a magnetic manipulation (Magman) system, which consists of four electromagnetic coils arranged linearly. The current through the coils is controlled in order to accurately position a steel ball, rolling freely in a track above the coils. We benchmark two nonlinear control methods, namely feedback linearization and a constrained state-dependent Riccati equation (SDRE) control. These methods are chosen due to their widespread use in academia as well as industrial applications. On the actual setup, constrained SDRE has performed considerably better in terms of the settling time, overshoot, and the amount of control effort when compared to feedback linearization.

Original language	English
Title of host publication	Proceedings 2017 IEEE 56th Annual Conference on Decision and Control (CDC 2017)
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	3277-3282
ISBN (Electronic)	978-1-5090-2873-3
ISBN (Print)	978-1-5090-2874-0
DOIs	https://doi.org/10.1109/CDC.2017.8264140
Publication status	Published - 2017
Event	CDC 2017: 56th IEEE Annual Conference on Decision and Control - Melbourne, Australia Duration: 12 Dec 2017 → 15 Dec 2017 http://cdc2017.ieeecss.org/

Conference

Conference	CDC 2017: 56th IEEE Annual Conference on Decision and Control
Country/Territory	Australia
City	Melbourne
Period	12/12/17 → 15/12/17
Other	The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.
Internet address	http://cdc2017.ieeecss.org/

Keywords

Coils
Mathematical model
Force
Steel
Position measurement
Manipulators

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10.1109/CDC.2017.8264140

Cite this

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Damsteeg, JW, Nageshrao, SP & Babuška, R 2017, Model-based real-time control of a magnetic manipulator system. in Proceedings 2017 IEEE 56th Annual Conference on Decision and Control (CDC 2017). IEEE, Piscataway, NJ, USA, pp. 3277-3282, CDC 2017: 56th IEEE Annual Conference on Decision and Control, Melbourne, Australia, 12/12/17. https://doi.org/10.1109/CDC.2017.8264140

Model-based real-time control of a magnetic manipulator system. / Damsteeg, Jan Willem; Nageshrao, Subramanya P.; Babuška, Robert.
Proceedings 2017 IEEE 56th Annual Conference on Decision and Control (CDC 2017). Piscataway, NJ, USA: IEEE, 2017. p. 3277-3282.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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N2 - Precise magnetic manipulation has numerous applications, ranging from manufacturing to the medical field. Owing to the nonlinear nature of the electromagnetic force, magnetic manipulation requires advanced nonlinear control. In this paper, we design and experimentally evaluate two nonlinear controllers for a magnetic manipulation (Magman) system, which consists of four electromagnetic coils arranged linearly. The current through the coils is controlled in order to accurately position a steel ball, rolling freely in a track above the coils. We benchmark two nonlinear control methods, namely feedback linearization and a constrained state-dependent Riccati equation (SDRE) control. These methods are chosen due to their widespread use in academia as well as industrial applications. On the actual setup, constrained SDRE has performed considerably better in terms of the settling time, overshoot, and the amount of control effort when compared to feedback linearization.

AB - Precise magnetic manipulation has numerous applications, ranging from manufacturing to the medical field. Owing to the nonlinear nature of the electromagnetic force, magnetic manipulation requires advanced nonlinear control. In this paper, we design and experimentally evaluate two nonlinear controllers for a magnetic manipulation (Magman) system, which consists of four electromagnetic coils arranged linearly. The current through the coils is controlled in order to accurately position a steel ball, rolling freely in a track above the coils. We benchmark two nonlinear control methods, namely feedback linearization and a constrained state-dependent Riccati equation (SDRE) control. These methods are chosen due to their widespread use in academia as well as industrial applications. On the actual setup, constrained SDRE has performed considerably better in terms of the settling time, overshoot, and the amount of control effort when compared to feedback linearization.

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Model-based real-time control of a magnetic manipulator system

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