A Novel Genetic Programming Approach for Frequency-Dependent Modeling

Abstract

Frequency-dependent modeling of devices and systems is a common practice in several fields, such as power systems, microwave systems, and electronics systems. The modeling process usually involves converting the tabulated frequency-response data into a compact equivalent circuit model. The main drawback of the currently existing methods such as vector fitting is that the obtained model is often nonpassive, leading to unstable simulations. In order to overcome this problem, this paper proposes a genetic programming (GP) approach to generate equivalent circuits with guaranteed passivity. The proposed method starts with a nonoptimal initial equivalent circuit. Both the elements and the topology of this circuit are then evolved by the proposed GP-based method, and an accurate equivalent circuit is obtained. Key ideas and detailed algorithms are presented in this paper. Finally, the performance of the proposed method is verified by using different case studies.