PSO在非线性电路及器件参数优化设计中的应用

为了解决非线性电路的一个多参数组合优化问题,使用了一种全局优化搜索方法-粒子群优化方法(PSO)来获取非线性电路及其中非线性器件参数的最优组合.首先对非线性电路建立线性化的数学模型,分析关键参数的基本特性,然后利用粒子群优化方法良好的全局搜索特性以及快速的收敛速度,在整个参数空间进行高效并行搜索来获得参数组合的最优化,以有效降低电路功耗.对典型的非线性分压式偏置电路以及其中BJT参数提取的设计实例证明了该方法的有效性以及其在搜索速度上的优越性.

A PSO Algorithm for Optimized Combinational Design of Parameters in Nonlinear Circuits

In order to resolve a multi-parameter combinational optimization problem, particle swarm optimization (PSO) algorithm is used to get the optimized combination of parameters in nonlinear circuits and the nonlinear devices. Firstly, the mathematical models of nonlinear circuits are constructed, and the basic characters of primary parameters are analyzed. Then the PSO algorithm is used to optimize the parameters in the parameter spaces to reduce the power consumption of the circuits. The design examples of typical nonlinear biasing circuit of divided voltage circuits and the extraction of BJT parameters show that the PSO algorithm can be used effectively.