Abstract
Mixed-mode integrated circuits become increasingly popular in modern VLSI Chip design. However, designing these circuits in CMOS technology is no small feat given the need to balance a range of conflicting performance criteria and design constraints. In this work, optimized two-stage operational amplifier designed using meta heuristics ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) algorithms. By leveraging ABC and PSO algorithms, the design process can efficiently achieve the desired performance goals by optimally sizing of the circuit components. In the proposed automated optimization environment, implementation of the ABC and PSO algorithms are implemented in Python language and integrated with the Ngspice simulation tool using BSIM4 MOSFET models in TSMC’s 130nm technology node. The entire optimization environment is set up on the Ubuntu operating system, and the results achieved with the ABC and PSO are compared with earlier reported work in which proposed optimized operational amplifier achieved higher unity gain bandwidth and higher CMRR. Proposed automated design environment interface between Ngspice circuit simulator and evolutionary algorithm to obtain the optimum results for the mentioned multidimensional design problem.
Keywords: ABC Algorithm, Automated Environment, Operational Amplifier Design, Optimization, PSO Algorithm.