Multiple objective genetic algorithms (MOGAs) simultaneously optimize a control law and geometrical features of a set of homopolar magnetic bearings (HOMB) supporting a generic flexible, spinning shaft. The minimization objectives include shaft dynamic response (vibration), actuator mass and total actuator power losses. Levitation of the spinning rotor and dynamic stability are constraint conditions for the control law search. Nonlinearities include magnetic flux saturation, and current and voltage limits. Pareto frontiers were applied to identify the best-compromised solution. Mass and vibration reductions improve with a two control law approach.
Magnetic Bearing Rotordynamic System Optimization Using Multi-Objective Genetic Algorithms
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 28, 2014; final manuscript received August 13, 2014; published online September 24, 2014. Assoc. Editor: M. Porfiri.
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Zhong, W., and Palazzolo, A. (September 24, 2014). "Magnetic Bearing Rotordynamic System Optimization Using Multi-Objective Genetic Algorithms." ASME. J. Dyn. Sys., Meas., Control. February 2015; 137(2): 021012. https://doi.org/10.1115/1.4028401
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