A design of generalized minimum variance controllers using a GMDH-type neural network for nonlinear systems
A design of generalized minimum variance controllers using a GMDH-type neural network for nonlinear systems
复制标题
使用 GMDH 型神经网络的非线性系统广义最小方差控制器的设计
DOI：
10.1109/icsmc.1999.812562
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
M. Kaneda
中科院分区：
文献类型：
--
作者：
A. Sakaguchi;T. Yamamoto;M. Kaneda
介绍了用广义最小方差控制器（GMVC）设计非线性系统的GMVC。采用一种多层神经网络的数据处理分组方法（GMDH），得到GMVC律所要求的输出预测值。由于GMVC律中输出的预测值是由非线性模型计算的，因此可以预期比线性模型计算的控制性能更好。通过数值仿真实例对所提控制方案的性能进行了评价。
Describes the design of a generalized minimun variance controller (GMVC) using a GMDH-type neural network for nonlinear systems. The predictive value of the output required in the GMVC law is obtained by using a group method of data handling (GMDH) which is a kind of multilayered neural network. Since the predictive value of the output in GMVC law is calculated by a nonlinear model, one can expect a better control performance than that calculated by a linear model. The behavior of the proposed control scheme is evaluated on a numerical simulation example.
影响因子：
6.4
作者：
CLARKE, DW;MOHTADI, C;TUFFS, PS
通讯作者：
TUFFS, PS