An efficient optimisation-based design of current conveyor performances
Abdelaziz Lberni, Malika Alami Marktani, Abdelaziz Ahaitouf, Ali Ahaitouf · International Journal of Computer Aided Engineering and Technology · 2022
Optimisation algorithms are increasingly used by electronic circuit designers to optimally design and size the performance of their circuits. Multi-objective optimisation algorithms have a great interest, since in most cases the problems of sizing analogue, RF and mixed-signal ICs include at least two conflicting and contradictory objectives. In the present paper, we present two evolutionary algorithms (EA) well known in the literature for their better performance in solving more difficult multi-objective problems (MOP). The performances of these proposed algorithms are first applied to some well-known mathematical benchmark functions and then to deal with the optimal sizing of current conveyor transistors in the framework of 0.18 μm technology. The most important objectives are to maximise the cut-off frequency and minimise the parasitic resistance of X-port. Pareto fronts are generated, and optimised solutions are chosen. Performance metrics of the optimisation results obtained are carried out by the CADENCE Virtuoso software. This paper discusses and shows that AEs are a priori the most adapted class of metaheuristics to be used in the field of optimal electronic circuit sizing.