标题: 基于增益余量与相位余量之非稳定系统PID控制器的调整方法:利用模糊类神经网路
Tuning of PID Controllers for Unstable Processes Based on Gain and Phase Margin Specifications: A Fuzzy Neural
作者: 许振榕
Chen-Gjung Hsu
邓清政
Ching-Cheng Teng
电控工程研究所
关键字: 模糊类神经网路;增益余量;相位余量;倒传递学习法则;PID控制器;FNN;FNGP;Fuzzy;Neural;Gain margin;Phase margin;PID controller
公开日期: 1998
摘要: 在本论文中,我们提出一个根据增益边际与相位边际的规格,用模糊类神网路经来决定PID控制器的参数。过去PID控制器已经很广泛地应用在稳定系统中,但对于开回路的非稳定系统的PID控制器却较少提到。在本文中,我们针对开回路非稳定系统,先用模糊类神经网路去训练增益边际与相位边际的规格与PID控制器参数间的关系之后,再利用已训练过的网路去得到一组符合使用者所需求的增益边际与相位边际的规格之PID控制器参数,而不需靠任何的数值分析或作图法来决定。此网路即使给的规格可能不合理,它依旧会给我们一组合理却又离规格比较近的PID控制器参数。从模拟中可知模糊类神经网路可以有效率地达到所要求的规格。
In the thesis, we present a PID tuning method for unstable processes using Fuzzy Neural Network based on gain and phase margin (FNGP) specifications. PID tuning methods were widely used to control stable processes. However, PID control for unstable processes is less common. A fuzzy neural network approach is proposed to identify the relationship between the gain-phase margin specifications and the PID controller parameters. Then, the FNN is used to automatically tune the PID controller parameters for different gain and phase margin specifications so that neither numerical methods nor graphical methods need be used. Even though for some of the unreasonable specifications, the FNN still can find a suitable PID controllers' parameters close to the specifications. Simulation results show that the FNN can achieve the specified values efficiently.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT870591005
http://hdl.handle.net/11536/64932
显示于类别:Thesis