An optimal iterative learning control (ILC) is proposed to optimize an accumulative quadratic performance index in the iteration domain for the nominal dynamics of linear discrete-time systems. Properties of stability, convergence, robustness, and optimality are investigated and demonstrated. In the case that the system under consideration contains uncertain dynamics, the proposed ILC design ca...

This paper presents iterative learning control (ILC) schemes for batch-varying references. Generally, reference or target trajectory must be identical for all iterations to implement the ILC. However, references can be changed in dynamic systems such as robotics and chemical processes according to cycle or batch. ILC schemes for batch-varying references are proposed in three forms which are inv...

BACKGROUND Sentinel lymph node (SLN) biopsy is the standard of care for the surgical assessment of the axilla during breast cancer surgery. However, the diagnostic accuracy of intraoperative frozen section analysis for confirming metastatic involvement of SLNs in cases of invasive lobular carcinoma (ILC) versus that of invasive ductal carcinoma (IDC) has generated controversy secondary to a fre...

We examine statistical isotropy of large scale anisotropies of the Internal Linear Combination (ILC) map, based on three year WMAP data. Our study reveals no significant deviation from statistical isotropy on large angular scales of 3-year ILC map. Comparing statistical isotropy of 3-year ILC map and 1-year ILC map, we find a significant improvement in 3-year ILC map which can be due to the gai...

Iterative learning control (ILC) is a simple and efficient solution to improve tracking accuracy for systems that execute repetitively the same tracing operation. For engineering applications of ILC, the main concern is the monotonic decay of tracking errors, in the sense of infinity norm or peak error, along the trials. Low cost in implementation and robustness in performance are also critical...

The goal of Iterative Learning Control ILC is to improve the accuracy of a system that repeatedly follows a reference trajectory This paper proves that for any causal ILC there is an equivalent feedback that achieves or approaches the ultimate ILC error with no iterations Remarkably this equivalent feedback depends only on the ILC operators and hence requires no plant knowledge This equivalence...

This paper presents Two-Dimensional (2-D) system analysis based Iterative Learning Control (ILC) methods for Linear Time-Variant (LTV) discrete systems with multiple time delays. Both the state delays and the input delays are considered in the ILC design. The ILC research strategy for LTV discrete systems with multiple time delays is to rescontruct the derived ILC error equations into the 2-D R...