Mystkowski, Arkadiusz; Pawluszewicz, Ewa; Dragašius, Egidijus Robust nonlinear position-flux zero-bias control for uncertain AMB system. (English) Zbl 1337.93028 Int. J. Control 88, No. 8, 1619-1629 (2015). Summary: This paper presents a robust nonlinear control law that combines a parametric uncertainty of the single one-degree-of-freedom Active Magnetic Bearing (AMB) system with disturbance. A robust nonlinear feedback tool such as Control Lyapunov Function (CLF) and robust stability techniques are developed. The control objective is to globally stabilize the mass position of an AMB with flux feedback. The flux-based control model for an AMB system is derived due to voltage switching strategy with voltage saturation. This strategy enables the flux control under a zero-bias or low-bias flux operation. In the zero-bias control, only one electromagnet in each axis of the AMB is active at any given time, depending on the rotor displacement. The proposed robust nonlinear CLF with a zero-bias for an uncertain AMB system can achieve a dynamic performance superior to that of a linear controller with the zero-bias or with the classical bias operations. Cited in 3 Documents MSC: 93B35 Sensitivity (robustness) 93C10 Nonlinear systems in control theory 93B52 Feedback control 78A55 Technical applications of optics and electromagnetic theory Keywords:active magnetic bearings; zero-bias; flux control; parametric uncertainty; control Lyapunov function; robust nonlinear control PDFBibTeX XMLCite \textit{A. Mystkowski} et al., Int. J. Control 88, No. 8, 1619--1629 (2015; Zbl 1337.93028) Full Text: DOI References: [1] DOI: 10.1016/0362-546X(83)90049-4 · Zbl 0525.93053 · doi:10.1016/0362-546X(83)90049-4 [2] Bahr F., ISMB 13 pp 1– (2012) [3] DOI: 10.1016/0005-1098(94)90175-9 · doi:10.1016/0005-1098(94)90175-9 [4] DOI: 10.1109/CDC.1993.325440 · doi:10.1109/CDC.1993.325440 [5] DOI: 10.1007/978-0-8176-4759-9 · doi:10.1007/978-0-8176-4759-9 [6] DOI: 10.4028/www.scientific.net/SSP.113.125 · doi:10.4028/www.scientific.net/SSP.113.125 [7] Gosiewski Z., Archives of Control Sciences 16 (3) pp 327– (2006) [8] DOI: 10.1016/j.ymssp.2007.08.005 · doi:10.1016/j.ymssp.2007.08.005 [9] DOI: 10.1109/9.376058 · Zbl 0822.93029 · doi:10.1109/9.376058 [10] DOI: 10.1109/ACC.2000.877065 · doi:10.1109/ACC.2000.877065 [11] DOI: 10.2307/1969955 · Zbl 0070.31003 · doi:10.2307/1969955 [12] DOI: 10.1002/pamm.200910285 · doi:10.1002/pamm.200910285 [13] Mystkowski A., Archives of Control Sciences 20 pp 123– (2010) · Zbl 1216.93040 · doi:10.2478/v10170-010-0010-y [14] Mystkowski A., Acta Mechanica et Automatica 4 (4) pp 83– (2010) [15] DOI: 10.4028/www.scientific.net/SSP.147-149.302 · doi:10.4028/www.scientific.net/SSP.147-149.302 [16] DOI: 10.1109/TMAG.2006.888731 · doi:10.1109/TMAG.2006.888731 [17] Schweitzer G., Magnetic bearings: Theory, design, and application to rotating machinery (2009) [18] DOI: 10.1137/0321028 · Zbl 0513.93047 · doi:10.1137/0321028 [19] DOI: 10.1016/0362-546X(88)90060-0 · Zbl 0662.93055 · doi:10.1016/0362-546X(88)90060-0 [20] DOI: 10.1109/CDC.2002.1184207 · doi:10.1109/CDC.2002.1184207 [21] Tsiotras P., Proceedings of 39th IEEE CDC’2000 pp 4048– (2000) [22] DOI: 10.1109/TCST.2003.819593 · doi:10.1109/TCST.2003.819593 [23] DOI: 10.1007/BF00276493 · Zbl 0252.93002 · doi:10.1007/BF00276493 [24] Zhou K., Essentials of robust control (1998) [25] Zhou K., Robust and optimal control (1996) · Zbl 0999.49500 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.