25 Papers
94 Citations
M. Dymkov is an academic researcher from National Academy of Sciences of Belarus. The author has contributed to research in topics: Linear system & Optimal control. The author has an hindex of 6, co-authored 23 publications.
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Papers
Control theory for a class of 2D continuous-discrete linear systems
TL;DR: In this paper, a general class of 2D continuous-discrete linear systems of both systems theoretic and applications interest is considered and a comprehensive control systems theory for members of this class is developed in a unified manner based on analysis in an appropriate algebraic and operator setting.
Exponential Stability of Discrete Linear Repetitive Processes
TL;DR: In this article, the concept of exponential stability for the sub-class of discrete linear repetitive processes has been developed and compared to those already in both the general 2D linear systems and repetitive process literature.
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Modeling and control of a sorption process using 2D systems theory
M. Dymkov,Krzysztof Galkowski,Eric Rogers,Vitali Dymkou,S. Dymkou +4 more
- 15 Nov 2011
TL;DR: A model for the dynamics of a sorption process from the industrial water supply and sewage treatment industries that is a continuous version of the Roesser state-space model for 2D discrete systems is introduced.
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z - Transform and Volterra-Operator Based Approaches to Controllability and Observability Analysis for Discrete Linear Repetitive Processes
TL;DR: This paper contributes substantial news results to this general task in the areas of controllability and observability for the sub-class of so-called discrete linear repetitive processes which arise in key applications areas and, in particular, iterative learning control.
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Controllability of discrete linear repetitive processes - a Volterra operator approach
M. Dymkov,I. V. Gaishun,Krzysztof Galkowski,Eric Rogers,David H. Owens +4 more
- 01 Jan 2000
TL;DR: This paper uses a Volterra operator setting to produce significant new results on the controllabiltiy of the sub-class of so-called discrete linear repetitive processes which are of particular interest in a number of areas, eg the modeling and analysis of a wide class of iterative learning control schemes.
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