Year: 2024
Type: conference-paper
Abstract: Optimising circuit performance is a key task in analogue circuit design. This study proposes an evolutionary algorithm-based circuit design optimisation method that combines Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO) for efficient tuning of circuit parameters. By adjusting the transistor size and compensation capacitance, this study aims to maximise the DC gain, gain bandwidth product (GB), conversion rate (SR), and minimise the power consumption. The circuit simulation is done by HSPICE and the optimisation algorithm is implemented in MATLAB. The experimental results show that the combination of GA and PSO can significantly improve the circuit performance metrics, especially in terms of gain bandwidth product and conversion rate. Meanwhile, the PSO algorithm performs relatively poorly in terms of power consumption optimisation. The study also compares the performance of different optimisation methods and verifies the effectiveness of the combination of GA and PSO methods in improving the circuit performance during the optimisation process. This paper provides theoretical support and practical basis for the design of complex circuits and demonstrates the effective application of evolutionary algorithms in circuit optimisation.
Authors: Zhengyang Wang, Zhongqi Wang, Yang Lv
Institution: Shenyang Aerospace University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410347728