Some recent papers have extended the concept of finite-time stability (FTS) to the context of 2-D linear systems, where it has been referred to as finite-region stability (FRS). To this regard, the novel contribution of our work considers an interesting application of FRS to the context of iterative learning control (ILC). In particular, a new procedure is proposed so that the tracking error of the ILC law converges within the desired bound in a finite number of iterations. The results provided in the paper lead to an optimization problem constrained by linear matrix inequalities (LMIs), that can be solved via widely available software. A numerical example illustrates the effectiveness of the proposed technique.
When Finite-Region Stability meets iterative learning control / Liang, Chao; Cosentino, Carlo; Merola, Alessio; Romano, Maria; Amato, Francesco. - (2021), pp. 388-393. ( IEEE RTSI 2021 Napoli, Italy 6-9 settembre 2021).
When Finite-Region Stability meets iterative learning control
Maria Romano;Francesco Amato
2021
Abstract
Some recent papers have extended the concept of finite-time stability (FTS) to the context of 2-D linear systems, where it has been referred to as finite-region stability (FRS). To this regard, the novel contribution of our work considers an interesting application of FRS to the context of iterative learning control (ILC). In particular, a new procedure is proposed so that the tracking error of the ILC law converges within the desired bound in a finite number of iterations. The results provided in the paper lead to an optimization problem constrained by linear matrix inequalities (LMIs), that can be solved via widely available software. A numerical example illustrates the effectiveness of the proposed technique.| File | Dimensione | Formato | |
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