Automated design of operational transconductance amplifiers using reversed geometric programming

Abstract

We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and non-convex constraints. Adding a limited set of non-convex constraints can improve the accuracy of convex equation-based optimization, without compromising global optimality. These constraints allow increased accuracy for critical modeling equations, such as the relationship between gm and IDS. To demonstrate the design methodology, a folded-cascode amplifier is designed in a [0.18]μm technology for varying speed requirements and is compared with simulations and designs obtained from geometric programming.