The variables in multidimensional systems are functions of more than one indeterminate, and such systems cannot be controlled by standard systems theory. This paper considers a subclass of these systems that operate over a subset of the upper-right quadrant of the two-dimensional (2D) plane in the discrete domain with a specified recursive structure known as repetitive processes. Physical examples of such processes are known and also their representations can be used in the analysis of other classes of systems, such as iterative learning control. This paper gives new results on the use of the parameter-dependent Lyapunov functions for stability analysis and controls law design of a subclass of repetitive processes that arise in application areas. These results aim to eliminate or reduce the effects of model parameter uncertainty.
Parameter-Dependent Lyapunov Functions in the Robust Control of Discrete Linear Repetitive Processes Using Previous Pass-Windowed Information
Manuscript received August 23, 2014; final manuscript received February 24, 2015; published online April 20, 2015. Assoc. Editor: Athanasios Pantelous.
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Cichy, B., Galkowski, K., and Rogers, E. (April 20, 2015). "Parameter-Dependent Lyapunov Functions in the Robust Control of Discrete Linear Repetitive Processes Using Previous Pass-Windowed Information." ASME. ASME J. Risk Uncertainty Part B. June 2015; 1(2): 021008. https://doi.org/10.1115/1.4029971
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