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基于混沌神经网络模型的预测控制器的设计及应用
引用本文:窦春霞. 基于混沌神经网络模型的预测控制器的设计及应用[J]. 系统工程理论与实践, 2003, 23(8): 48-52. DOI: 10.12011/1000-6788(2003)8-48
作者姓名:窦春霞
作者单位:燕山大学电气工程学院 河北秦皇岛066004
摘    要:根据具有混沌特性非线性、大时滞系统的时间序列重构相空间,计算相空间饱和嵌入维数、并以此为指导,建立混沌神经网络,即便在网络输入不完整或发生变异的情况下,该模型仍能对系统作高精度的短期预测;在此基础上,又设计了模糊神经网络预测控制器,实现了对非线性、大时滞系统高精度的自适应控制。将该控制器应用到单元机组负荷控制系统中,仿真表明了该控制有效性、快速性和鲁棒性。

关 键 词:混沌神经网络  模糊神经网络  鲁棒性   
文章编号:1000-6788(2003)08-0048-05
修稿时间:2002-06-16

Design of Fuzzy Neural Network Controller Based on Chaos Neural Network Forecast Model and Application
DOU Chun-xia. Design of Fuzzy Neural Network Controller Based on Chaos Neural Network Forecast Model and Application[J]. Systems Engineering —Theory & Practice, 2003, 23(8): 48-52. DOI: 10.12011/1000-6788(2003)8-48
Authors:DOU Chun-xia
Affiliation:Yanshan University, Qinghuangdao 066004, China
Abstract:In order to realize adaptive control of nonlinear big-lagged system, First, a chaotic attractors space is reconstructed, space embed dimension is calculated by the nonlinear big-lagged system chaos time series in this paper. By above all, a chaos neural network model is constructed, which can make high precision short-term forecast for the system even by imperfect and variation inputs. On the basis of this, a fuzzy-neural forecast controller is designed and robust adaptive control to the nonlinear big-lagged chaos system is realized. Last, the controller is applied to units load system, the validity, the high-speed and the robustness are proved by simulate results.
Keywords:chaos neural network  fuzzy neural network  robustness
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