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Structured transfer function matrices and integer matrices: the computation of the generic McMillan degree and infinite zero structure

机译:结构化传递函数矩阵和整数矩阵:通用McMillan度和无限零结构的计算

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The computation of the McMillan degree and structure at infinity of a transfer function model is considered for the family of early design models, referred to as Structured Transfer Function (STF) matrices. Such transfer functions have certain elements fixed to zero, some elements being constant and other elements expressing some identified dominant dynamics of the system. For the family of large dimension STF matrices the computation of the generic McMillan degree and structure at infinity are considered using genericity arguments which lead to optimization problems of integer matrices. A novel approach is introduced here that uses the notion of "irreducibility" of integer matrices, which is developed as the equivalent of irreducibility (properness) of polynomial matrices. This new notion provides the means for exploiting the structure of integer matrices and enables the termination of searching processes in a reduced number of steps, thus leading to an efficient new algorithm for the computation of the generic value of the McMillan degree and the structure at infinity of STFs. Links are made to standard optimization problems and to graph theory. The formulation of the optimization algorithm in terms of bipartite graphs offers better results and reduces the computational effort.
机译:对于早期设计模型家族,考虑了传递函数模型无穷大处McMillan度和结构的计算,称为结构传递函数(STF)矩阵。这样的传递函数具有固定为零的某些元素,一些元素是恒定的,而其他元素表示系统的某些确定的主导动力学。对于大型STF矩阵家族,使用泛型参数考虑了在无穷大处的通用McMillan度和结构的计算,这会导致整数矩阵的优化问题。这里介绍一种新颖的方法,该方法使用整数矩阵的“不可约性”概念,该概念被开发为多项式矩阵的不可约性(性质)的等效项。这个新概念为利用整数矩阵的结构提供了手段,并使得能够以减少的步骤数终止搜索过程,从而导致了一种高效的新算法,可用于计算麦克米伦度的通用值和无穷大的结构STF。链接到标准优化问题和图论。用二部图表示优化算法可以提供更好的结果并减少计算量。

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