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A subspace approach to linear dynamical systems

机译:线性动力系统的子空间方法

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In this paper we present an approach to linear dynamical systems which combines the positive features of two well known formulations, namely, standard state space theory (see for e.g., Wonham, 1978 [9]) and behavioural systems theory (see Polderman and Willems, 1997 [4]). Our development is also 'geometric' in the tradition of Wonham and others. But, instead of using explicit linear maps, we work with linear relations implicitly which amounts to working with subspaces. One of our primary motivations is computational efficiency - all our computations can be performed on the system as it is without elimination of variables and further (unlike the 'behaviourists' who manipulate matrices with polynomial entries) we work only with real matrices. Using our formulation we derive the standard vector space results on controlled and conditioned invariant subspaces of linear dynamical systems. Duality, which is a distinctive feature of state space theory but not of the behavioural view point, comes out naturally in our approach too through the use of the adjoint. We illustrate our ideas for an important class of dynamical systems viz., electrical networks. The theory proposed in this paper gives a unified description of both the standard linear dynamical systems and the linear singular systems (or the linear descriptor systems) (see for e.g., F. Gantmacher 1959 [1] and Lewis, 1986 [2]). Therefore, the algorithms described for the invariant spaces in this paper are also applicable to linear singular systems.
机译:在本文中,我们提出了一种线性动力学系统的方法,该方法结合了两种众所周知的公式的积极特征,即标准状态空间理论(请参见Wonham,1978 [9])和行为系统理论(请参见Polderman和Willems, 1997 [4])。在Wonham和其他人的传统中,我们的发展也是“几何的”。但是,不是使用显式线性映射,而是隐式地使用线性关系,这相当于使用子空间。我们的主要动机之一是计算效率-我们所有的计算都可以在系统上执行,而无需消除变量,而且(不像使用多项式项处理矩阵的“行为主义者”一样),我们只能处理实数矩阵。使用我们的公式,我们得出线性动力系统的受控和条件不变子空间上的标准向量空间结果。对偶性是状态空间理论的一个独特特征,而不是行为观点的特征,通过使用伴随关系,对偶性在我们的方法中也很自然地出现。我们阐述了关于一类重要的动力系统(即电气网络)的想法。本文提出的理论对标准线性动力系统和线性奇异系统(或线性描述符系统)进行了统一描述(例如,参见F. Gantmacher 1959 [1]和Lewis,1986 [2])。因此,本文描述的不变空间算法也适用于线性奇异系统。

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