A rapid and reliable approach for optimal design of an electromagnetic nanopositioning actuator

Abstract

This paper presents a rapid approach for optimizing the segmented design of an electromagnetic driving module (EDM) of a nanopositioning actuator. The integral equation model, which has used to compute the magnetic flux density in the air-gap of the EDM, is replaced by a training set of samples of pre-computed database during optimization that significantly reduced the computational complexity. The training set has been constructed by using sequential design sampling, which proved to be more efficient compared to traditional approach. The response in output space is the function of input variables, which are the crucial geometrical parameters, such as air-gap and Permanent Magnet (PM) dimension. Making use of lumped circuit-based thermal model in the design analysis also results in faster optimization process. Up to 80% reduction in computation time is achieved by the application of such database technique. The optimal DM configuration yields significant performance improvement over an initial design offering higher output force, whilst maintaining desired thermal behavior.