Grammatical Evolution-based Analog Circuit Synthesis

Abstract

Computer aided circuit design is becoming one of the mainstream methods for helping circuit designers. Multiple new methods have been developed in this field including Evolutionary Electronics. A lot of work has been done in this field but there is still a room for improvement since some of the solutions lack the flexibility (diversity of components, limited topology etc.) in circuit design or lack complex fitness functions that would enable the synthesis of more complex circuits. The research presented in this article aims to improve this by introducing Grammatical Evolution-based approach for circuit synthesis. Grammatical Evolution offers great flexibility since it is rule based – adding a new element is as simple as writing one additional line of initialization code. In addition, the use of a complex multi-criteria function allows us to create circuits that can be as complex as required thus further increasing the flexibility of the approach. To achieve this, we use a combination of Python and SPICE to create a series of netlists, evaluate them in the PyOpus environment, and select the best possible circuit for the task. We demonstrate the efficiency of our approach in three different case studies where we automatically generate oscillators and high/low-pass filters of second and third order.