基于人工智能算法的单级全差分折叠式共源共栅运算放大器的多目标设计方法

李照希; 苏震宇; 田宇浩; 侯琛雪; 杨银堂

doi:10.12263/DZXB.20250055

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基于人工智能算法的单级全差分折叠式共源共栅运算放大器的多目标设计方法

大模型与互联网 | 更新时间：2025-10-16

- 基于人工智能算法的单级全差分折叠式共源共栅运算放大器的多目标设计方法
- Multi-Objective Design Method for Single-Stage Fully Differential Folded Cascode Operational Amplifiers Based on the Artificial Intelligence Algorithm
- 电子学报 2025年53卷第6期页码：1784-1791
- 作者机构：
  
  西安电子科技大学集成电路学部，陕西西安 710126
- 作者简介：
  
  [ "李照希男，1996 年1 月出生于陕西省西安市.现为西安电子科技大学副教授.主要研究方向为压电传感器集成电路设计、超声波高频声场控制和超声换能器优化设计.E-mail: lizhaoxi@xidian.edu.cn" ]
  [ "苏震宇男，2001年2月出生于山西省吕梁市.现为西安电子科技大学集成电路科学与工程专业2025级直博生.主要研究方向为超声模拟前端电路及模拟电路优化设计.E-mail: suzhenyu@stu.xidian.edu.cn" ]
  [ "田宇浩男，2004年10月出生于山西省孝义市.现为西安电子科技大学集成电路设计与集成系统专业本科生.主要研究方向为模拟集成电路设计、遗传算法.E-mail: 22009100726@stu.xidian.edu.cn" ]
  [ "侯琛雪女，1997年1月出生于陕西省西安市.现为西安电子科技大学助理研究员、博士后.主要研究方向为复合压电超声换能器仿真与制备、声学阻抗匹配技术.中国电子学会会员编号：E190161716M.E-mail: houchenxue@xidian.edu.cn" ]
  [ "杨银堂男，1962年10月出生于河北省邯郸市.现为西安电子科技大学教授.主持完成多项国家级科研工作，获得国家科学技术进步奖等多项奖项.主要研究方向为SOC与混合信号集成电路设计.中国电子学会会员编号：E190011537F.E-mail: ytyang@xidian.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(62304165);中国博士后科学基金专项资金(2024T170691);中国博士后科学基金(2023M732745);国家博士后资助计划(GZC20232024);陕西省博士后科研项目(30102230001)
- DOI：10.12263/DZXB.20250055
  中图分类号： TN40;TN43
- 收稿：2025-05-22，
  
  修回：2025-06-05，
  
  纸质出版：2025-06-25
- 稿件说明：
移动端阅览
李照希, 苏震宇, 田宇浩, 等. 基于人工智能算法的单级全差分折叠式共源共栅运算放大器的多目标设计方法[J]. 电子学报, 2025, 53(06): 1784-1791.

LI Zhao-xi, SU Zhen-yu, TIAN Yu-hao, et al. Multi-Objective Design Method for Single-Stage Fully Differential Folded Cascode Operational Amplifiers Based on the Artificial Intelligence Algorithm[J]. Acta Electronica Sinica, 2025, 53(06): 1784-1791.
李照希, 苏震宇, 田宇浩, 等. 基于人工智能算法的单级全差分折叠式共源共栅运算放大器的多目标设计方法[J]. 电子学报, 2025, 53(06): 1784-1791. DOI：10.12263/DZXB.20250055

LI Zhao-xi, SU Zhen-yu, TIAN Yu-hao, et al. Multi-Objective Design Method for Single-Stage Fully Differential Folded Cascode Operational Amplifiers Based on the Artificial Intelligence Algorithm[J]. Acta Electronica Sinica, 2025, 53(06): 1784-1791. DOI：10.12263/DZXB.20250055

摘要

随着集成电路制造技术的发展，模拟集成电路设计面临着功耗、增益等性能指标折中的挑战.传统的设计方法依赖于近似方程和反复迭代，导致效率低下.本文提出了一种基于人工智能算法的多目标设计策略，用于单级全差分折叠式共源共栅运算放大器的设计.该方法采用神经网络模型来表征设计参数与8个性能指标之间的映射关系，并通过适应度函数和约束条件设定运放所需达成的目标性能，再使用粒子群优化（Particle Swarm Optimization，PSO）算法搜寻最佳适应度.实验结果表明，多项指标均优于设计目标，其中最大电压增益达到了65 dB，相位裕度为74°.利用该方法，能够快速且准确地获得满足设计要求的运放参数.与手工计算相比，该方法的运行时间仅为906 s，显著提高了设计效率，未来可应用于更多大规模电路设计中.

Abstract

With the advancement of integrated circuit manufacturing technology

analog integrated circuit design faces the challenge of trade-offs between performance metrics such as power consumption and gain. Traditional design methods

reliant on approximate equations and iterative refinement

are inefficient. This paper presents an artificial intelligence algorithm-based multi-objective design strategy for the design of a single-stage fully differential folded cascode operational amplifier. This method employs a neural network model to characterize the mapping relationship between design parameters and eight performance metrics

and sets the target performance for the operational amplifier to achieve through fitness functions and constraint conditions

then utilizes particle swarm optimization (PSO) algorithm to search for the optimal fitness. Experimental results show that multiple metrics exceed design targets

with a maximum voltage gain of 65 dB and a phase margin of 74°. Using this method

we can quickly and accurately obtain operational amplifier parameters that meet design specifications. Compared to manual calculations

this method reduces the running time to merely 906 seconds

significantly improving the design efficiency. It can be applied to more large-scale circuit designs in the future.

关键词

Keywords

references

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