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Engineering costs especially for controller design are substantial and obstruct active magnetic bearings (AMBs) for broader industrial applications. An optimization based AMB controller design method is developed to solve this problem. The optimization criteria are selected to describe AMB practical performance. Controller components are chosen considering that parameters can be manually interpreted and modified onsite for commissioning. A multi-objective genetic algorithm (MOGA) toolbox is used to tune these controller component parameters to minimize the design criteria automatically. The method has been verified in a controller design process for an AMB levitated machine. With this method, the engineering cost for controller design can be reduced significantly.

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Booktitle: Proceedings of ISMB14