摘要
为解决典型工业过程中大时滞系统难于控制的问题,提出一种增益自适应内模PID(ProportionalIntegralDifferential)控制方法。对时滞系统纯滞后环节一阶Pade逼近后,由内模整定得到PID控制器的参数整定值,再应用Adaline人工神经网络动态获取被控对象的增益,从而自动调节控制器的比例系数。由仿真结果可见,当增益自适应控制方法投入跟踪后,超调从投入前的23%减为投入后的9%,该控制方法能克服增益变化对系统控制性能的影响,显著改善控制品质。
In order to solve the control problem of typical industrial process with great dead time,a design method of the gain self-adaptable IMC(Internal Model Control) tuning PID(Proportional Integral Differential) control is proposed. The IMC tuning parameters of PID controller are obtained by approximating the time-delay of system with first-order Pade formula and the gain of the controlled object is identified via Adaline artificial neutral network to adjust the proportion coefficient of PID controller. Simulation result show that as gain self-adaptation method is put into operation, superscale decreases from 23% to 9%, so the proposed control method can overcome the effect of gain variation and improve the control performance.
出处
《吉林大学学报（信息科学版）》
CAS
2004年第4期355-358,共4页
Journal of Jilin University（Information Science Edition）
基金
山西省中青年基金资助项目(20021018)
