摘要
提出一种新的基于高斯基函数 (GPFN- Gaussian potential function networks)网络的内模控制算法 ,并对高斯基函数网络内部模型和内模控制器的建立进行了深入分析 .仿真及实时控制结果表明该算法是有效的 ,具有很好的自适应性和鲁棒性 ,可以应用于具有时滞和非线性时变系统中 .
A novel algorithm on internal model control based on gaussian potential function networks (GPFN) is presented. The internal model and internal model controller respectively represented by gaussian potential function networks are deeply analyzed and real-time control experiments are also made in detail. The control results show that the proposed algorithm has better properties in term of adaptive method and robustness and can be introduced to time delay systems, nonlinear systems and time varying systems.
出处
《信息与控制》
CSCD
北大核心
2001年第2期143-148,共6页
Information and Control
关键词
神经网络
高斯基函数
自适应控制
非线性系统
时滞系统
neural network, gaussian potential function networks, internal model control, adaptive control, process control
