Details

Autor(en) / Beteiligte

• Tlelo-Cuautle, E.
• Sanabria-Borbon, A.C.

Titel

Optimising operational amplifiers by evolutionary algorithms and gm/Id method

Ist Teil von

• International journal of electronics, 2016-10, Vol.103 (10), p.1665-1684

Ort / Verlag

Abingdon: Taylor & Francis

Erscheinungsjahr

2016

Quelle

Taylor & Francis

Beschreibungen/Notizen

• The evolutionary algorithm called non-dominated sorting genetic algorithm (NSGA-II) is applied herein in the optimisation of operational transconductance amplifiers. NSGA-II is accelerated by applying the g m /I d method to estimate reduced search spaces associated to widths (W) and lengths (L) of the metal-oxide-semiconductor field-effect-transistor (MOSFETs), and to guarantee their appropriate bias levels conditions. In addition, we introduce an integer encoding for the W/L sizes of the MOSFETs to avoid a post-processing step for rounding-off their values to be multiples of the integrated circuit fabrication technology. Finally, from the feasible solutions generated by NSGA-II, we introduce a second optimisation stage to guarantee that the final feasible W/L sizes solutions support process, voltage and temperature (PVT) variations. The optimisation results lead us to conclude that the g m /I d method and integer encoding are quite useful to accelerate the convergence of the evolutionary algorithm NSGA-II, while the second optimisation stage guarantees robustness of the feasible solutions to PVT variations.