Evolutionary algorithms in the optimal sizing of analog circuits

Abstract

Analog signal processing applications such as filter design and oscillators, require the use of different kinds of amplifiers, namely: voltage follower, current conveyors, operational amplifiers and current feedback operational amplifiers. To improve the performances on these applications, it is very much needed to optimize the behavior of the amplifiers. That way, this work shows their optimization by applying two evolutionary algorithms: the Non-Sorting Genetic Algorithm (NSGA-II), and the Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D). The analog circuits are sized taking into account design constraints, and linking HSPICE like circuit simulator to evaluate their electrical characteristics. Additionally, we show that differential evolution (DE) enhances the convergence to the Pareto front and controls the evolution of the objectives among different runs. DE also preserves the same time efficiency and increases the dominance on NSGA-II and MOEA/D compared with the one point crossover genetic operator. © 2011 Springer-Verlag Berlin Heidelberg.