Nonlinear control system using Learning Petri Network

被引：0

作者：

Ohbayashi, M

Hirasawa, K

Sakai, S

Hu, JL

机构：

[1] Kyushu Univ, Fac Engn, Fukuoka 812, Japan

[2] Kyushu Univ, Grad Sch, Syst & Informat Sci Res Div, Fukuoka 812, Japan

来源：

ELECTRICAL ENGINEERING IN JAPAN | 2000年 / 131卷 / 03期

关键词：

neural network; Learning Petri Network; function distribution; optimization; nonlinear control;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

According to recent understanding of brain science, it is suggested that there is a distribution of functions in the brain, which means that different neurons are activated depending on which sort of sensory information the brain receives. We have already developed a learning network with a function distribution which is called the Learning Petri Network (LPN) and have shown that this network could learn nonlinear and discontinuous mappings which the Neural Network (NN) cannot. In this paper, a more realistic application which has dynamic characteristics is studied. From simulation results of a nonlinear crane control system using LPN controller, it is clarified that the control performance of LPN controller is superior to that of NN controller. (C) 2000 Scripta Technica.

引用

页码：58 / 69

页数：12