Analog Circuit Optimization Based on Hybrid Particle Swarm Optimization

• Published in: 2015 International Conference on Computational Science and Computational Intelligence (CSCI) pp. 164 - 169
• Main Authors: Joshi, Deepak, Dash, Satyabrata, Agarwal, Ujjawal, Bhattacharjee, Ratnajit, Trivedi, Gaurav
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2015
• Subjects: Computational intelligence; Electronic Design Automation; Particle Swarm Optimization (PSO); Scientific computing; Simulated Annealing (SA)
• DOI: 10.1109/CSCI.2015.112

With growing Electronic Design Automation (EDA) industry, automated analog circuit design is now a feasible solution for the demand to exploit a span of nonlinear circuit behaviours from devices to circuits with the flexibility to optimize numerous competing continuous-valued performance specifications. In order to meet desired specifications, state-of-art EDA tools are employed which depend upon more efficient and effective optimization techniques to suffice the cost of designing complex analog systems. In this paper, a hybrid metaheuristic based on PSO and SA is presented to design one of the most prominent design specifications, i.e. gains of a two-stage CMOS operational amplifier circuit and a simple operational transconductance amplifier circuit subject to a variety of design conditions and constraints. Here convergence of PSO is improved by advancing through local solutions using SA to achieve quality global optimum solution. Experimental results are compared with other standard optimization techniques to show performance of proposed hybrid metaheuristic in terms of optimization quality and robustness.