基于模糊神经网络PID的水轮机组频率控制  

Hydraulic turbine set frequency control based on fuzzy neural network PID

作　　者：陈德海 朱正坤 王超 CHEN Dehai;ZHU Zhengkun;WANG Chao(College of Electrical Engineering and Automation,Jiangxi University of Science and Technology,Ganzhou 341000,China)

机构地区：[1]江西理工大学电气工程与自动化学院,江西赣州341000

出　　处：《现代电子技术》2020年第23期99-102,共4页Modern Electronics Technique

基　　金：国家自然科学基金(61463020);江西省自然科学基金(20151BAB206034)。

摘　　要：在水电站发电过程中,频率控制至关重要,但是对于这种非线性、时变性的复杂控制系统来说,传统PID控制方法存在参数整定困难,控制效果不佳的缺陷。因此在传统的PID算法、模糊控制以及神经网络控制算法的基础之上,提出一种模糊神经网络PID联合控制算法来优化水轮机调节系统的PID参数,并应用到水轮机调节系统当中,与传统PID控制器进行对比,结果表明模糊神经网络PID控制算法对水轮机调节系统的控制上在调整时间以及超调量方面都比传统PID算法更好,控制效果好,克服了传统PID算法的不足。Frequency control is very important in the process of hydroelectric power generation,but the traditional PID control method for the complex control system with non-linearity and time-varying characteristics has the defects of difficult parameter tuning and poor control effect.Therefore,on the basis of the traditional PID algorithm,fuzzy control and neural network control algorithm,a combined control algorithm of fuzzy neural network and PID is proposed to optimize the PID parameters of hydraulic turbine governing system.It is applied to the hydraulic turbine governing system and compared with the traditional PID controller.The results show that the fuzzy neural network PID control algorithm is better than the traditional PID algorithm in adjusting time and overshoot,and has good control effect.It has overcome the shortcomings of the traditional PID control algorithm.

关 键 词：频率控制 水轮机调速 系统参数优化 PID控制器设计 模糊神经网络PID 水电站 

分 类 号：TN876-34[电子电信—信息与通信工程] TP13[自动化与计算机技术—控制理论与控制工程]