自适应模糊辨识及其在大系统中的应用*

Adaptive Fuzzy Identification and Its Applicationto the Hierarchical Control of Large Scale Systems

中文关键词  模糊逻辑  神经网络  动态过程  稳态模型  系统辨识  大系统

英文关键词  fuzzy logic  neural network  dynamic processes  steady model  systems identification  large scale systems

中文摘要

      本文基于T-S模糊模型构造了一种新的自适应模糊神经网络，给出了网络的连接结构和学习算法，它能自动学习和修正前件参数及模糊规则. 将其用于大系统随机稳态递阶优化的控制建模中，仿真结果表明，该方法具有收敛速度快、辨识精度高、泛化能力强等特点，可当作复杂大系统建模的一种有效手段.

英文摘要

      ln this paper， a new adaptive fuzzy neural network based on the T-S model is proposed. Also， the network structure and the learning algorithms are given， and it is used in the hierarchical systems for large scale processes operating in random steady state. The simulation results show that the method has the properties of fast convergence， high accuracy and better capability of generalizing. So it is a powerful tool for modeling large scale systems in steady state.