曹清, 章辉, 孙优贤. 改进的用于模型降阶的最小信息损失方法[J]. 信息与控制, 2005, 34(4): 423-428.
引用本文: 曹清, 章辉, 孙优贤. 改进的用于模型降阶的最小信息损失方法[J]. 信息与控制, 2005, 34(4): 423-428.
CAO Qing, ZHANG Hui, SUN You-xian. A Revised Minimum Information Loss Method for Model Reduction[J]. INFORMATION AND CONTROL, 2005, 34(4): 423-428.
Citation: CAO Qing, ZHANG Hui, SUN You-xian. A Revised Minimum Information Loss Method for Model Reduction[J]. INFORMATION AND CONTROL, 2005, 34(4): 423-428.

改进的用于模型降阶的最小信息损失方法

A Revised Minimum Information Loss Method for Model Reduction

  • 摘要: 针对最小信息损失方法进行模型降阶时结果不唯一的问题,提出了改进的最小信息损失方法.本方法通过限制系统采用输出正规模型,将系统的能观性格兰姆矩阵限制为单位矩阵,从而使得系统的总信息损失达到最小.并且保证了降阶结果的唯一性.

     

    Abstract: Aiming at the problem that the reduced-order model generated by the MIL(Minimum Information Loss) method is not unique, we propose the RMIL(Revised Minimum Information Loss) method. By restricting the system to be the output normal model and transforming the observability Grammian to be an identity matrix, the presented RMIL method minimizes the total information loss and preserves the reduced-order model to be unique.

     

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