引用本文:陈增强 ,赵天航, 袁著祉.基于Tank-Hopfield神经网络的有约束多变量广义预测控制器[J].控制理论与应用,1998,15(6):847~852.[点击复制]
CHEN Zengqiang, ZHAO Tianhang and YUAN Zhuzhi.The Constrained Multivariable Predictive ControllerBased on Tank-Hopfield Nenral Network[J].Control Theory and Technology,1998,15(6):847~852.[点击复制]
基于Tank-Hopfield神经网络的有约束多变量广义预测控制器
The Constrained Multivariable Predictive ControllerBased on Tank-Hopfield Nenral Network
摘要点击 1141  全文点击 463  投稿时间:1996-09-24  修订日期:1997-09-16
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DOI编号  
  1998,15(6):847-852
中文关键词  神经网络  T-H网络  预测控制  多变量控制  二次优化
英文关键词  neural network  T-H network  predictive control  multivariable control  quadratie opti-mization
基金项目  
作者单位
陈增强 ,赵天航, 袁著祉 南开大学计算机与系统科学系 
中文摘要
      通过对系统的信号约束,构成有约束多变量广义预测控制问题,并运用T-H优化神经网络来求解这一复杂的优化问题. 在求解过程中,有约束广义预测控制的求解被转化为一个T-H优化电路弼络的稳态解. 因此可以通过硬件电路或龙格一库塔数值方法进行求取. 在一个工业过程模型上的仿真研究证明了这一方法是非常有效的.
英文摘要
      Through the constrain of the signals of sy8tem,this paper drives the generalized predictive control,and solves the complicate optimizing problem with T-H neural network It is transformed into the solving of a stable state of a T-H optimizing neural networks for the constrainetl general ized predictive controllcr. Hence,the solution can be obtained through hardware electricity circuit or Runge-Kutta numerical algorithm. The simulation research on a process verifies that the method is very effective.