摘要
提出利用压缩机运行数据样本建立压缩机性能的模糊控制模型的方法,并将神经网络引入到压缩机性能模型当中,修正模糊控制模型的输出,提高模型精度。仿真结果表明,该方法有效且建模精度优于Elman网络和单纯的模糊控制,模型的输出精度较高,实现了压缩机高精度模型的建立。
A method to build fuzzy control model of refrigeration compressor performance by using compressor running data sample was proposed.Fuzzy-neural network was introduced into the compressor performance model to modify the output and improve the accuracy of the model.Simulation results show that the method is effective and the modeling accurate is better than the Elman network and simple fuzzy control.The accuracy of the model output is high and realizing high precision modeling for compressor.
出处
《化工自动化及仪表》
CAS
北大核心
2010年第6期32-34,38,共4页
Control and Instruments in Chemical Industry
关键词
离心压缩机
性能模型
模糊控制
模糊神经网络
refrigeration compressor
performance model
fuzzy control
fuzzy-neural network
