Marek B. Zaremba

Learn More
This note demonstrates that the design of a robust iterative learning control is straightforward for uncertain linear time-invariant systems satisfying the robust performance condition. It is shown that once a controller is designed to satisfy the well-known robust performance condition, a convergent updating rule involving the performance weighting(More)
This paper deals with robust iterative learning control design for uncertain single-input–single-output linear time-invariant systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the μ-synthesis approachto obtain a feedback controller. Thereafter, a convergent iterative learning law is(More)
In this paper, a new skeletonization algorithm suitable for the skeletonization of sparse shape is described. It is based on Self-Organizing Maps (SOM) – a class of neural networks with unsupervised learning. The so-called structured SOM with local shape attributes such as scale and connectivity of vertices are used to determine the object shape in the form(More)