摘要
本文提出了一种神经网络自适应控制系统,它由两个神经网络组成,一个用于建模,一个用于控制器设计,两者共用一个学习信号。该系统算法简洁,仿真结果令人满意。该方法为在难以建立数学模型的场合实现非线性控制提供了可能。
A neunet adaptive control system is proposed. It is made up of two neunets: one is used in model, the other is in controller. The two parts utilize the same learning signal together and the algorithm is facilitated. Thesimulation results are satisfactory. The method can be used to control the free high-order nonlinear dynamic systems that are difficult to construct the mathematical model.
出处
《控制与决策》
EI
CSCD
北大核心
1992年第5期361-366,共6页
Control and Decision
基金
国家教委博士点基金
关键词
自适应控制
神经网络
nonlinear systems
adaptive control
neural networks
