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模糊自学习控制在水电机组控制中应用研究
引用本文:王淑青,李朝晖,袁晓辉.模糊自学习控制在水电机组控制中应用研究[J].水电能源科学,2006,24(2):11-13.
作者姓名:王淑青  李朝晖  袁晓辉
作者单位:1. 华中科技大学,水电与数字化工程学院,湖北,武汉,430074;湖北工业大学,电气与电子学院,湖北,武汉,430068
2. 华中科技大学,水电与数字化工程学院,湖北,武汉,430074
基金项目:中国科学院资助项目;湖北省自然科学基金
摘    要:采用具有自学习能力的自适应模糊控制器来控制水电机组运行。自适应模糊控制器将模糊控制和神经网络结合,根据运行情况在线调整模糊推理规则和隶属函数,使控制系统具有自适应学习的特性。学习中学习速率和平滑因子可根据误差情况在线修改,克服了网络学习速度慢和局部最优的缺点。仿真实验表明,设计的自适应模糊控制器具有良好的鲁棒性,可有效地改善水轮发电机组系统的动、静态性能。

关 键 词:水轮发电机组  模糊控制  神经网络  在线学习
文章编号:1000-7709(2006)02-0011-03
收稿时间:2006-03-28
修稿时间:2006年3月28日

Research on Fuzzy Self-learning Controller Used in Hydroelectric Generating Unit
WANG Shuqing,LI Zhaohui,YUAN Xiao.Research on Fuzzy Self-learning Controller Used in Hydroelectric Generating Unit[J].International Journal Hydroelectric Energy,2006,24(2):11-13.
Authors:WANG Shuqing  LI Zhaohui  YUAN Xiao
Abstract:Conventional controller cannot get good controlling performance in the control of hydroelectric generating unit system because the system is non-linear and complicated.In the paper new fuzzy self-learning controller is designed to control hydroelectric generating unit.The designed new fuzzy controller combines neural network into fuzzy reasoning system.Fuzzy reasoning rules and member function may be trained on-line via neural network,which makes control system having the character of self-adapting.In order to accelerate learning and converging quickly,parameters may be adjusted according to error and error change.Simulation experiment shows that the designed controller has stronger robust performance and excellent static and dynamic performance.
Keywords:hydroelectric generating unit  fuzzy control  neural network  on-line learning
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