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 ,仿真表明了该控制的有效性、快速性和鲁棒性 .
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.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2003年第8期48-52,共5页
Systems Engineering-Theory & Practice
