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CONVEX MODIFICATIONS TO AN ITERATIVE LEARNING CONTROL LAW
D.H. Owens* J. Hätönen**,*
* Department of Automatic Control and Systems Engineering,
University of Sheffield, Mappin Street, Sheffield S1 3JD
** Systems Engineering Laboratory, University of Oulu, P.O.BOX 4300,
FIN-90014 University of Oulu
In this paper an optimal predictive iterative learning control algorithm proposed earlier in the research literature is analyzed in detail. As a new major result is is shown that by using the future inputs from the predictive algorithm a faster convergence rate can be achieved when compared to the current approach which utilizes the reciding horizon principle. Furthermore, the nature of the convergence of this new scheme is analyzed in detail in terms of the free parameters of the algorithm.
Keywords: Iterative learning control, optimal control, predictive control
Session slot T-Mo-M03: Mathematical Methods in Adaptive Control/Area code 3b : Adaptive Control and Tuning
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