Sparse Iterative Learning Control with Application to a Wafer Stage: Achieving Performance, Resource Efficiency, and Task Flexibility

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 through convex relaxations using $\ell_1$ norms. The proposed ILC framework is applied to the optimization of sampling sequences for resource efficient implementation, trial-varying disturbance attenuation, and basis function selection. The framework has a large potential in control applications such as mechatronics, as is confirmed through an application on a wafer stage.Comment: 12 pages, 14 figure

Internalisation by electronic FX spot dealers

Dealers in over-the-counter financial markets provide liquidity to customers on a principal basis and manage the risk position that arises out of this activity in one of two ways. They may internalise a customer's trade by warehousing the risk in anticipation of future offsetting flow, or they can externalise the trade by hedging it out in the open market. It is often argued that internalisation underlies much of the liquidity provision in the currency markets, particularly in the electronic spot segment, and that it can deliver significant benefits in terms of depth and consistency of liquidity, reduced spreads, and a diminished market footprint. However, for many market participants, the internalisation process can be somewhat opaque, data on it are scarcely available, and even the largest and most sophisticated customers in the market often do not appreciate or measure the impact that internalisation has on their execution costs and liquidity access. This paper formulates a simple model of internalisation and uses queuing theory to provide important insights into its mechanics and properties. We derive closed form expressions for the internalisation horizon and demonstrate—using data from the Bank of International Settlement's triennial FX survey—that a representative tier 1 dealer takes on average several minutes to complete the internalisation of a customer's trade in the most liquid currencies, increasing to tens of minutes for emerging markets. Next, we analyse the costs of internalisation and show that they are lower for dealers that are willing to hold more risk and for those that face more price-sensitive traders. The key message of the paper is that a customer's transaction costs and liquidity access are determined both by their own trading decisions as well as the dealer's risk management approach. A customer should not only identify the externalisers but also distinguish between passive and aggressive internalisers, and select those that provide liquidity compatible with their execution objectives

Signing NOT (or not): A typological perspective on standard negation in Sign Language of the Netherlands

The expression of standard negation by means of manual and/or non-manual markers has been described for a considerable number of sign languages. Typological comparisons have revealed an intriguing dichotomy: while some sign languages require a manual negative element in negative clauses (manual-dominant sign languages), in others negation can be realized by a non-manual marker alone (in particular a headshake; non-manual-dominant sign languages). We are here adding data from Sign Language of the Netherlands (NGT) to the picture, and we demonstrate that NGT belongs to the latter group. Still, detailed comparison suggests that NGT patterns differently from other non-manual-dominant sign languages, thereby improving our understanding of the typological variation in this domain. A novel contribution of the present study is that it is based on naturalistic corpus data, showing more variation than often found in elicitation and grammaticality judgment studies of sign languages, but also presenting new problems of interpretation

Symmetry of massive Rarita-Schwinger fields

We derive the general lagrangian and propagator for a vector-spinor field in $d$-dimensions and show that the physical observables are invariant under the so-called point transformation symmetry. Until now the symmetry has not been exploited in any non-trival way, presumably because it is not an invariance of the classical action nor is it a gauge symmetry. Nevertheless, we develop a technique for exploring the consequences of the symmetry leading to a conserved vector current and charge. The current and charge are identically zero in the free field case and only contribute in a background such as a electromagnetic or gravitational field. The current can couple spin-3/2 fields to vector and scalar fields and may have important consequences in intermediate energy hadron physics as well as linearized supergravity. The consistency problem which plagues higher spin field theories is then discussed and and some ideas regarding the possiblity of solutions are presented.Comment: 26 pages, 1 figure; revised using referee comments, Journal ref. adde

Iterative learning control and feedforward for LPV systems : applied to a position-dependent motion system

Iterative Learning Control (ILC) enables performance improvement by learning from previous tasks. The aim of this paper is to develop an ILC approach for Linear Parameter Varying (LPV) systems to enable improved performance and increased convergence speed compared to the linear time-invariant approach. This is achieved through dedicated analysis and norm-optimal synthesis of LPV learning filters. Application to a position-dependent motion system shows a significant improvement in accuracy and convergence rate, thereby confirming the potential of the proposed approach.</p

Iterative learning control and feedforward for LPV systems : applied to a position-dependent motion system

Iterative Learning Control (ILC) enables performance improvement by learning from previous tasks. The aim of this paper is to develop an ILC approach for Linear Parameter Varying (LPV) systems to enable improved performance and increased convergence speed compared to the linear time-invariant approach. This is achieved through dedicated analysis and norm-optimal synthesis of LPV learning filters. Application to a position-dependent motion system shows a significant improvement in accuracy and convergence rate, thereby confirming the potential of the proposed approach.</p

Predicting the subcellular localization of viral proteins within a mammalian host cell

BACKGROUND: The bioinformatic prediction of protein subcellular localization has been extensively studied for prokaryotic and eukaryotic organisms. However, this is not the case for viruses whose proteins are often involved in extensive interactions at various subcellular localizations with host proteins. RESULTS: Here, we investigate the extent of utilization of human cellular localization mechanisms by viral proteins and we demonstrate that appropriate eukaryotic subcellular localization predictors can be used to predict viral protein localization within the host cell. CONCLUSION: Such predictions provide a method to rapidly annotate viral proteomes with subcellular localization information. They are likely to have widespread applications both in the study of the functions of viral proteins in the host cell and in the design of antiviral drugs