摘要
根据一类典型工业过程的特点，提出了一种神经网络控制方案．该方法基于ＲＢＦ（ＲａｄｉａｌＢａｓｉｓＦｕｎｃｔｉｏｎ）神经网络辨识过程模型，然后在此模型基础上设计内模控制．利用连续搅拌反应釜（ＣＳＴＲ）系统进行仿真设计，结果表明方案有效．
According to the characteristic of a typical kind of industrial process, a new neural network control strategy is put forward. This strategy is based on the process model which is identified by the radial basis function neural network. With such a model, a nonlinear internal model control (IMC) strategy which has no offset is designed. The simulation with the CSTR shows that the CSTR is successfully identified and the IMC strategy is rather good.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
1998年第1期122-126,共5页
Journal of Shanghai Jiaotong University
关键词
RBF神经网络
连续搅拌反应釜
辨识
内模控制
radial basis function (RBF) neural network
continuous stirred tank reactor (CSTR)
identification
internal model control
