Multirate iterative learning control (ILC) systems have different sampling rates for feedback online loop and feedforward (or ILC) offline loop. The implementation of multirate ILC requires to downsample the signal first and, after processing, upsample the signal again. In the process of downsampling and upsampling, aliasing and imaging may occur and need to be handled properly. In this paper, ...

We review the physics potential of the GigaZ option of the International Linear Collider (ILC) for probing the Minimal Supersymmetric Standard Model (MSSM) via the sensitivity of the electroweak precision observables measured at the ILC to quantum corrections [1]. A particular focus is put on the effective leptonic weak mixing angle, sin θeff . The MSSM predictions take into account the complet...

This paper discusses the application of Iterative Learning Control (ILC) algorithms for the engagement of wet clutches. A two-level control scheme is presented, consisting of a high level ILC-type algorithmwhich iteratively updates parameterized reference trajectories which are tracked by the low level tracking control. At this low level, two standard ILC controllers are used to first track a p...

Postnatal development of Leydig cells can be divided into three distinct stages of differentiation: initially they exist as mesenchymal-like progenitors (PLC) by day 21; subsequently, as immature Leydig cells (ILC) by day 35, they acquire steroidogenic organelle structure and enzyme activities but metabolize most of the testosterone they produce; finally, as adult Leydig cells (ALC) by day 90 t...

Extrasynaptic GABAA receptors, often identified as those containing both α4 and δ subunits, demonstrate super-sensitivity to GABA and are involved in tonic inhibitory processes regulating activity within mesolimbocortical circuitry. Rodent studies testing the effects of the δ-subunit selective agonist Gaboxadol (THIP) on alcohol consumption have produced mixed results. The goal of this study wa...

Trial-varying disturbances are a key concern in Iterative Learning Control (ILC) and may lead to inefficient and expensive implementations and severe performance deterioration. The aim of this paper is to develop a general framework for optimization-based ILC that allows for enforcing additional structure, including sparsity. The proposed method enforces sparsity in a generalized setting throug...

Some initial results on the disturbance properties of high order iterative learning control (ILC) algorithms are presented. Of particular interest is to investigate how high order ILC algorithms cope with measurement and load disturbances of different character. Some results are obtained by assuming statistical properties of the involved disturbances and deriving equations for the covariance ma...

This paper presents a frequency domain based method to design iterative learning controllers (ILC) for monotonic convergence. This is an extension of a repetitive controller (RC) design that aims to achieve monotonic convergence of all frequency components of the tracking error from period to period. The monotonic convergence condition in the RC design requires a steady-state assumption that th...

In this paper, based on the prediction control performances defined over one cycle or multiple cycles, two higher-order ILC schemes have been developed by extending the Generalized Predictive Control (GPC) method to the two-dimensional (2D) system. The dynamics of the ILC system along time and cycle is taken as a 2D system, and the proposed designs integrate optimally the design and the combina...

This paper considers iterative learning control for linear systems with convex control input constraints. First, the constrained ILC problem is formulated in a novel successive projection framework. Then, based on this projection method, a constrained ILC algorithm is proposed to solve this constrained ILC problem. The results show that, when perfect tracking is possible, the proposed algorithm...