基于改进粒子群算法的分数阶系统辨识方法

An Identification Method Based on an Improved PSO for Fractional-order System

为获取精确的分数阶系统模型,本文利用惯性权值自适应律来改进基本粒子群算法,基于所改进的粒子群算法提出了一种分数阶系统辨识方法,并选取实际系统与辨识系统的输出误差平方和为目标函数,实现了分数阶模型参数和阶次的同时辨识,适用于成比例和不成比例分数阶系统辨识。仿真结果表明了算法的有效性,辨识结果精度较高。

In order to obtain the accurate model of fractional order system,the basic particle swarm optimization algorithm was improved by using the inertia weight adaptive law. A scheme of fractional order system identification based on the improved particle swarm optimization was proposed in this paper. The fitness function was the sum of devia tions of output of the actual system and the identification system. This method can identify both the model parameter and the fractional order,and can be applicable to the commensurate rate and non-commensurate rate fractional-order systems. A number of numerical simulations were illustrated to validate the concept and had high accuracy of identification.