Optimal Sizing of Recycling Folded Cascode Amplifier for Low Frequency Applications Using New Hybrid Swarm Intelligence-Based Technique

• Published in: Applied artificial intelligence 2020-11, Vol.34 (13), p.994-1010
• Main Authors: Laskar, Naushad Manzoor, Guha, Koushik, Nath, Sourav, Baishnab, K.L., Paul, P.K.
• Format: Article
• Language: English
• Subjects: Algorithms; Amplification; Amplifiers; Analog circuits; Cascode devices; Circuit design; Computer simulation; Design optimization; Design specifications; Hybrid systems; Low frequencies; Low noise; Optimization techniques; Particle swarm optimization; Recycling; Sizing; Slew rate; Specifications; Statistical analysis; Swarm intelligence
• ISSN: 0883-9514; 1087-6545
• DOI: 10.1080/08839514.2020.1795786

A new efficient design approach for sizing a high performance analog amplifier circuit namely the Recycling Folded Cascode (RFC) amplifier is presented. A RFC amplifier is an enhanced version of the conventional folded cascode amplifier and achieves better slew rate, gain, bandwidth, offset etc. for same area and power budget. Low frequency amplifiers such as biomedical or neural have a demanding requirement of low area, low power and low noise apart from meeting other optimal design specifications which have inherent trade-off amongst themselves. As a result, manual sizing becomes a computationally inefficient approach. Thus, swarm based optimization techniques have been employed to efficiently determine the optimal sizing for the RFC amplifier such that the area is minimized while meeting all the optimal design specifications considering the constraints. A new hybrid whale particle swarm optimization (HWPSO) algorithm is employed which takes advantage of the good qualities of both the whale algorithm and the PSO algorithm to optimize the area with less computational complexity. Simulations and statistical analysis have been performed and comparisons with other state of art algorithms reveals that HWPSO-based approach achieves a minimum circuit area of 21 µm 2 with a mean Friedman's statistical rank of 2.05 while meeting optimal design specifications for low frequency systems. Finally, validation with circuit design tool Cadence Virtuoso is done and pre as well as post layout analysis have been performed which further illustrated a close agreement with algorithmic results.