首页> 外文会议>International Conference on Emerging Trends in Engineering, Science and Technology >Neural Network Based PI Controller Parameter Calculation on a Boiler Drum Level System
【24h】

Neural Network Based PI Controller Parameter Calculation on a Boiler Drum Level System

机译:基于神经网络的锅炉鼓级系统PI控制器参数计算

获取原文

摘要

The controller parameters influence the performance of the closed loop system. So we have to develop a tuning method for obtaining the optimum values of the controller parameters with respect to a particular process. Controller tuning is very much process dependent and any improper selection of the controller settings may lead to instability and affect performance of the closed loop system. Closed loop tuning methods like Ziegler-Nichols method depends on estimation of ultimate gain and ultimate time period. When trying different gains on an unknown process the amplitude of undampened oscillations can become unsafe or on the conversely for low initial gain settings the test can take a long time to reach sustained oscillation condition. This paper proposes a neural network based scheme to estimate ultimate gain and optimum proportional and integral value of PI controller within affordable time limit and safe input range when the parameters change.
机译:控制器参数影响闭环系统的性能。因此,我们必须开发一个调整方法,用于获得关于特定过程的控制器参数的最佳值。 Controller tuning is very much process dependent and any improper selection of the controller settings may lead to instability and affect performance of the closed loop system. Ziegler-Nichols方法等闭环调谐方法取决于估计最终增益和最终时间段。当在未知过程上尝试不同的收益时,阻尼振荡的幅度可以变得不安全或相反,对于低初始增益设置,测试可能需要很长时间才能达到持续的振荡条件。本文提出了一种基于神经网络的基于神经网络,以在参数改变时在实惠的时间限制和安全输入范围内估计PI控制器的最终增益和最佳比例和积分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号