控制系统性能评估中干扰通道模型的选择  

The Selection of Disturbance Process Model in Performance Assessment of Control Loops

作　　者：金晓明[1] 周超[1] 

机构地区：[1]浙江大学智能系统与控制研究所,浙江杭州310027

出　　处：《控制工程》2011年第5期681-684,共4页Control Engineering of China

基　　金：国家高技术研究发展计划863计划资助项目(2007AA04Z172)

摘　　要：控制系统性能评估是过程控制领域的研究热点,理论研究得到了极大重视,在工业上也得到了一定的应用。性能评估的理论依据最小方差控制律属于随机系统最优控制范畴,与传统的控制理论中控制系统通常作为确定性系统来研究存在差异。Eriksson等人曾注意到在某些条件下,基于最小方差控制的性能评估结果可能存在问题。简略介绍了单回路反馈控制中的最小方差控制实现,以及ARMA和FCOR两种性能指标估计算法,并在Eriksson等人工作的基础上,针对典型的一阶/二阶加纯滞后过程以及积分加纯滞后过程进行仿真实验,对比控制系统的设定值跟踪性能,研究了干扰通道模型的不同对性能评估结果的影响,最后指出在应用性能评估方法时需根据干扰信号注意样本序列的选取。Performance assessment of control loops which is a hot spot in process control has been paid much attention in theoretic research, and has been applied in process industry. The benchmark of performance assessment--mininmm variance control belongs to optimal control law of stochastic systems, that is different from traditional control theory in which control system is treated as deterministic system. Eriksson et al found that the performance assessment result based on MVC may have problems on certain occasions. The implementation of minimum variance control in univariate feedback control is introduced as well as the ARMA and FCOR algorithm. Based on Erikssong work, for classic first order/second order plus dead-time process and integral plus dead-time process, we study the influence of disturbance process model on performance assessment result of control loops, and compare it with the setpoint tracking performance. Finally, the selection of sample series based on disturbance is emphasized in practical applications.

关 键 词：性能评估 最小方差控制 干扰通道模型 ARMA FCOR 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]