Abstract
Abstract A magnetic bearing system is a coupled, nonlinear, high-dimensional system. The relationship among the design parameters, design constraints and the optimization goals is not obvious. Solving this type of design problem within a reasonable time frame is a challenge for any optimization method. This research investigated the simultaneous optimization of the magnetic bearing configuration and bearing locations. A multistage genetic algorithm was developed to search through a discrete and non-convex solution space. Because the genetic algorithm can search through a much larger solution space than any engineer can do, innovative designs different from those using traditional methods can be found.
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