Naturally based optimisation algorithm for analogue electronic circuits : GA, PSO, ABC, BFO, and firefly a case study

Abstract EN

This work presents various intelligence optimisation techniques.

Namely: genetic algorithm (GA), particle swarm optimisation (PSO), artificial bee colony (ABC), bacterial foraging optimisation (BFO), and Firefly algorithm (FA).

It attempts to optimise analogue electronic circuits using cascode amplifier design by applying all the swarm intelligence algorithms.

Small signal model transformation of the cascode circuit is carried out while mesh analysis is used to convert the circuit to matrix form.

Codes are developed in Matlab using GA, PSO, ABC, BFO, and (FA) to optimise the cascode amplifier circuit.

The objective function is based on power consumption, lower frequency band, upper-frequency band, gain, input resistance and output resistance.

Results are presented and compared to the original circuit simulated in PSPICE and an optimised circuit using Nelder-Mead constrained nonlinear minimisation algorithm.

The PSO result has proven to be the best followed by GA in terms of frequency response and power consumption reduction.

Three circuit elements are targeted (C, R, and transistors number) using the various optimisation methods then compared to the initial circuit.