• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (07): 1404-1408.

• 论文 • 上一篇    下一篇

基于PSO的负反馈电路参数自适应优化及仿真分析

杨一军,陈得宝,王江涛,丁国华,王孟杰   

  1. (淮北师范大学物理与电子信息学院,安徽 淮北 235000)
  • 收稿日期:2012-12-03 修回日期:2013-04-03 出版日期:2014-07-25 发布日期:2014-07-25
  • 基金资助:

    国家自然科学基金资助项目(51101067,61203272);安徽省自然科学基金资助项目(1308085MF82);安徽省教育厅重点资助项目(2013jyxm097);淮北市科技人才培育基金计划资助项目(20110304)

Adaptive optimization and simulation analysis of
parameters of negative feedback circuit based on PSO                        

 YANG Yijun,CHEN Debao,WANG Jiangtao,DING Guohua,WANG Mengjie   

  1. (School of Physics and Electronic Information,Huaibei Normal University,Huaibei 235000,China)
  • Received:2012-12-03 Revised:2013-04-03 Online:2014-07-25 Published:2014-07-25

摘要:

采用粒子群优化算法,以电压增益、共模抑制比、输入电阻平方根的三者乘积对输出电阻的比作为适应度函数,对差分共射两级直接耦合电压串联负反馈放大电路中的电阻做自适应优化。结果显示,只要对电路交流指标加以约束,适应度函数值总会减小。当分别对增大电压增益和减小输出电阻进行限制后,电压增益总是尽量小,输出电阻总是尽量大,以使适应度函数在给定约束下取得最大。经EWB软件对优化参数仿真,结果满足线性放大要求。同时说明了可以调整适应度函数形式,找到最佳电路参数,以满足工程上对放大器指标的不同需求。

关键词: PSO, 电压增益, 输出电阻, 仿真

Abstract:

The resistance values of two layers directly coupled differentialcommon emitter voltage series negative feedback amplifying circuit are adaptively optimized by particle swarm optimization. In the method, the voltage gain, commonmode rejection ratio and the square root of the input resistance are multiplied, and the ratio between the product and the output resistance is used as the fitness function. The results indicate that the fitness function value will decrease under the constraint condition that alternating current index is limited. After increasing voltage gain and decreasing the output resistance are restricted, to derive the maximal fitness function value under the given condition, the voltage gain is as small as possible and the output resistance is as large as possible. Simulation results of the parameters with EWB software can meet the requirements of linear amplification. The results also indicate that the optimal parameters of circuit can be found by adjusting the fitness function.

Key words: particle swarm optimization;voltage gain;output resistance;simulation