Two stage CMOS operational transconductance amplifier for front-end electronics design using multiobjective genetic algorithms

In this paper, we elaborate a program based on multi-objective genetic algorithms (MOGAs) to allow automated optimization of analog circuits. The proposed methodology is used to find the optimal transistors sizes (length and width) in order to obtain operational amplifier performances for analog and mixed CMOS-based circuit applications. Eight performances are considered in this study, direct current (DC) gain, unity-gain bandwidth (GBW), phase margin (PM), power consumption (P), area (A), slew rate (SR), thermal noise and signal to noise ratio (SNR). The program is solved using MATLAB Optimization Toolbox™ solvers. Also by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA) is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC (Taiwan Semiconductor Manufacturing Company) RF 0.18μm CMOS technology. A good agreement is observed between the program optimization and electric simulation.