摘要
人工神经元网络基于其特有的功能而被应用于控制系统中,为智能控制提供了一个有潜力的发展方向,本文讨论了神经元网络控制的三种方法:基于模式识别功能的BP网络控制器,基于联想记忆模型的模糊控制,以及基于神经元网络优化功能的控制优化调节,并分别指出其优、缺点及有待解决的一些问题。
There have been many attempts to use neural networks in control systems. Based on special characteristics, they provide an approach with significant potential toward intelligent control. This paper reviews the emerging field of neural networks for control systems. The methods used in this field can be broadly classified as: 1) BP network controllers 2)fuzzy control based on associative memory models, and 3) neural networks for optimization. Comments on these methods and expectations are also given in.this paper.
出处
《信息与控制》
CSCD
北大核心
1992年第3期156-161,166,共7页
Information and Control
基金
国家自然科学基金
关键词
控制系统
神经网络
neural networks lesrning identification control BP network Hopfield network
