The multi-disciplinary optimization of actuators which is the key component of a Nested Flying Vehicle (NFV) is done through ModelCenter. The NFV is operated inside the space station for space science experiments. The conceptual design of the NFV has been done with expensive simulation models. However, the optimization result of the NFV using the genetic algorithm led to an unaccepted time consumption. In order to solve those problems, a self-programmed optimizer which is embedded the Radial Basis Function (RBF)-based optimization strategy is developed and integrated to ModelCenter and applied to the electromagnetic actuators of NFV. The optimizer helps to integrate more metamodel-based optimization algorithms and enhance the optimization ability of ModelCenter. By comparing with the optimization algorithms supplied by ModelCenter, the RBF-based optimization strategy proposed in this paper costs less time and results in an acceptable design. The conceptual design of the NFV, the methodology of RBF-based optimization strategy and the key components of optimizer are introduced in this paper.

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