Optimization Method Incorporating Equivalent Circuit Theory and Space Mapping for Metamaterial Absorbers

Abstract

Due to the pivotal role of metamaterial absorbers in enhancing electromagnetic (EM) wave control and management, the optimization for metamaterial absorbers has garnered increasing attention. It is time-consuming to optimize the design of metamaterial absorbers by using the existing methods, so it is necessary to develop a more efficient optimization method. In this article, an optimization method incorporating equivalent circuit theory and space mapping (SM) for the metamaterial absorbers is proposed to enhance the optimization efficiency. This method takes the EM response of the metamaterial absorber to be optimized as a fine model, while the reflection coefficient formula derived from the equivalent circuit model is used as a coarse model, the mapping between the coarse model and the fine model is established through an artificial neural network (ANN). The coarse model and the ANN mapping together constitute the ANN-SM model, which can replace the EM simulation to predict the EM responses quickly. The orthogonal sampling method and the star sampling method are employed to reduce the number of training sample points for the ANN-SM surrogate model. Additionally, we also introduce the trust region algorithm, which can speed up the convergence of the optimization method and improve the optimization efficiency of the metamaterial absorber. Compared with the genetic algorithm (GA)-based design method, particle swarm optimization (PSO)-based design method, the deep-learning (DL)-based inverse design method, and the ANN surrogate-based optimization method for the optimization of metamaterial absorbers, the proposed method has higher design efficiency, especially when the number of design parameters for the metamaterial absorbers is relatively large. By using this method, we can accurately find the optimal design parameters that meet the design goals. Moreover, this method can be applied to the optimization of multi-layer metamaterial absorbers as well as metamaterial absorbers with lumped elements. In this article, we use three examples to verify the effectiveness of the method.

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