Abstract
Discrete linear repetitive processes are a distinct class of two-dimensional linear systems with applications in areas ranging from long-wall coal cutting to iterative learning control schemes. In this paper, a one-dimensional linear systems equivalent state-space model description of the dynamics of discrete nonunit memory linear repetitive processes is developed and used (with related approaches) to characterize key systems theoretic properties.
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