Title
Frequency-Domain Analysis of Robust Monotonic Convergence of Norm-Optimal Iterative Learning Control.
Abstract
In this paper, we consider the norm-optimal iterative learning control (NO-ILC) framework and study its robust monotonic convergence (RMC) against model uncertainties in single-input-single-output linear time-invariant systems. Modeling errors in general degrade the convergence performance of NO-ILC, and hence ensuring RMC against model uncertainties is important. Although the robustness of NO-ILC has been studied in the literature, determining the allowable range of modeling errors for a given NO-ILC design is still an open research question. To fill this gap, a frequency-domain analysis with a multiplicity formulation of model uncertainty is developed in this paper to quantify and visualize the allowable modeling errors. Compared with the traditional formulation, the proposed new uncertainty formulation provides a less conservative representation of the allowable model uncertainty range by taking additional phase information into account and thus allows for a more complete evaluation of the robustness of NO-ILC. The analysis also clarifies how the RMC region changes as a function of NO-ILC weighting parameters and therefore can be used as a frequency-domain design tool to achieve RMC for given model uncertainties. Simulation examples are given to confirm the theoretical conclusions and demonstrate the utility of the developed analysis.
Year
DOI
Venue
2018
10.1109/TCST.2017.2692729
IEEE Trans. Contr. Sys. Techn.
Keywords
Field
DocType
Uncertainty,Frequency-domain analysis,Robustness,Convergence,Analytical models,Tools,Asymptotic stability
Frequency domain,Convergence (routing),Monotonic function,Mathematical optimization,Weighting,Control theory,Design tool,Robustness (computer science),Exponential stability,Iterative learning control,Mathematics
Journal
Volume
Issue
ISSN
26
2
1063-6536
Citations 
PageRank 
References 
6
0.43
10
Authors
3
Name
Order
Citations
PageRank
Xinyi Ge161.11
Jeffrey L. Stein215827.02
Tulga Ersal33315.63