文献类型：期刊文献

中文题名：基于改进粒子群优化算法的闭环时滞系统辨识

英文题名：Closed-Loop System Identification with Time-Delay Based on Improved Particle Swarm Optimization Algorithm

作者：王谦[1];孙京诰[1]

机构：[1]华东理工大学信息科学与工程学院化工过程先进控制和优化技术教育部重点实验室,上海200237

年份：2015

卷号：41

期号：2

起止页码：159

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

语种：中文

中文关键词：闭环系统;时滞;混沌粒子群优化算法;误差准则函数

外文关键词：closed-loop system; time-delay; chaotic particle swarm optimization algorithm; error rule function

摘要：闭环时滞模型参数的辨识一直是先进工业控制领域的一个重要课题。然而由于时滞的存在,被控量不能及时地反映系统所承受的扰动,从而产生明显的超调,使得控制系统的稳定性变差。本文充分利用粒子群优化算法收敛速度较快和混沌运动遍历性的优点,提出了一种基于混沌优化思想的混沌粒子群优化算法来直接辨识含有滞后环节的被控对象的闭环传递函数,而不用将其转化为状态方程。将闭环时滞系统的传递函数通过z变换转化为离散的差分方程,对于滞后环节的处理,用一阶Pade近似。利用CPSO的全局优化能力来极小化误差准则函数,从而获得模型参数的估计值。仿真实验结果证明:该方法收敛速度较快、辨识得到的参数精度较高,适用于实际的工业生产。该方法与辅助变量最小二乘方法相比,计算量小、过程简单、不用计算多重积分、辨识速度较快、辨识精度高。
The identification on parameters of closed-loop time-delay systems has been an important topic in advanced industrial control field. However, due to the existence of time delays, the controlled variable cannot timely reflect the external disturbance, which may result in obvious overshoot and poor stability. Using the advantages of particle swarm optimization algorithm and chaotic motion, this paper proposes a direct identification method on the transfer function of closed-loop time-delay systems, rather than transforming the transfer function to the state equation. Using z transform, the transfer function of closed-loop time-delay system is changed into discrete differential equation. Besides, the time delay is approximated by means of first-order Pade approximation. CPSO method is adopted to minimize the error criterion function so as to obtain the estimation of the model parameters. It is shown from the simulation results that the proposed method has fast convergence speed and higher identification accuracy.