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Content available remote Iterative learning control — monotonicity and optimization
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EN
The area if Iterative Learning Control (ILC) has great potential for applications to systems with a naturally repetitive action where the transfer of data from repetition (trial or iteration) can lead to substantial improvements in tracking performance. There are several serious issues arising from the "2D" structure of ILC and a number of new problems requiring new ways of thinking and design. This paper introduces some of these issues from the point of view of the research group at Sheffield University and concentrates on linear systems and the potential for the use of optimization methods and switching strategies to achieve effective control.
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Content available remote Linear Repetitive Process Control Theory Applied to a Physical Example
80%
EN
In the case of linear dynamics, repetitive processes are a distinct class of 2D linear systems with uses in areas ranging from long-wall coal cutting and metal rolling operations to iterative learning control schemes. The main feature which makes them distinct from other classes of 2D linear systems is that information propagation in one of the two independent directions only occurs over a finite duration. This, in turn, means that a distinct systems theory must be developed for them for onward translation into efficient routinely applicable controller design algorithms for applications domains. In this paper, we introduce the dynamics of these processes by outlining the development of models for various metal rolling operations. These models are then used to illustrate some recent results on the development of a comprehensive control theory for these processes.
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Content available remote From Continuous to Discrete Models of Linear Repetitive Processes
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EN
Differential linear repetitive processes are a distinct class of 2D linear systems which pose problems which cannot (except in a few very restrictive special cases) be solved by application for computer aided annalysis and simulation. One such problem area is the construction of accurate numerically well conditioned discrete approximations of the dynamics of differential processes which could, as one example of number of immediate applications areas, from the basis for digital implementation of control laws. In this paper, we undertake a detailed investigation of the critical problems which arise when attempting to construct usefull discrete approximations of the dynamics of differential linear repetitive processes and develop solutions to them. Numerical examples to support the results obtained are also given using a specially developed MATLAB based toolbox.
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