摘要
分析了利用具有多层反馈的动态回归神经网络作为控制器的可行性 ,构造了基于RNN的控制系统 ,并对典型的非线性化工对象连续搅拌釜反应器 (CSTR)和化工过程Benchmark问题进行了实时的控制应用。结果表明 ,多层反馈的回归神经网络控制器具有结构简单、控制效果好的优点 ,特别是在对Benchmark控制中采用了多入多出的RNN控制器构造的串级控制系统 ,体现了RNN控制系统的强适应能力 ,可用于复杂动态过程的控制。
The direct neural network control is introduced and the dynamic feedback recurrent neural network (RNN) with multi layers as a controller is analyzed. A new type of RNN control system is proposed with applications to a continuous stirred tank reactor (CSTR) control and a plant wide industrial process control (Benchmark) problems. The control results show that the RNN controller with multi layers leads to simplification of control structure and good effect, especially for multi input/multi output cascade control systems, exhibiting that the RNN controller is adaptable and applicable to complex industrial problems.
出处
《北京化工大学学报（自然科学版）》
EI
CAS
CSCD
2000年第3期88-90,共3页
Journal of Beijing University of Chemical Technology(Natural Science Edition)
基金
国家自然科学基金!资助项目 (2 96760 0 2
2 99760 0 3)
