The use of hardware-based data structures for accelerating real-time and embedded system applications is limited by the scarceness of hardware resources. Being limited by the silicon area available, hardware data structures cannot scale in size as easily as their software counterparts. We assert a hardware-software co-design approach is required to elegantly overcome these limitations. In this paper, we present a hybrid priority queue architecture that includes a hardware accelerated binary heap that can also be managed in software when the queue size exceeds hardware limits. A memory mapped interface provides software with access to priority-queue structured on-chip memory, which enables quick and low overhead transitions between hardware and software management. As an application of this hybrid architecture, we present a scalable task scheduler for real-time systems that reduces scheduler processing overhead and improves timing determinism of the scheduler.

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Hardware-software architecture for priority queue management in real-time and embedded systems

Mechatronic design of strongly nonlinear systems on a basis of three wheeled mobile platform

Control of nanopositioning and nanomeasuring machines with a modular FPGA based data processing system

﻿The subject of the present thesis is the development of a model-based
control method for multi-axis nanopositioning and nano-measuring machines
with large moving ranges up to several hundred millimeters The thesis
focuses on measuring machines which are guided by ball bearingsThe goal of
the developed control concept is a significant reduction of the tracking
errors compared to existing methods Due to the ball bearings the system
behavior is dominated by nonlinear friction especially at low speeds of
movement In addition, movement in one machine axis affects also the other
axesTo achieve the necessary positioning accuracy, the control system has
to compensate the friction force effectively and the couplings between the
machine axes must be taken into account explicitly at the same time
The target system is a prototype of a three-axis nano-positioning machine
with a moving range of 200 x 200 x 25 mm³, which was developed at the
Ilmenau University of Technology The starting point of the controller
design is a detailed modeling of the target system Special focus is given
to the description of the dynamic friction force A friction model with
multiple state variables based on a physically motivated approach is
developed
An adaptive state-space controller as well as a nonlinear compensation
controller is initially designed for a single axis with the aim of
effective friction force compensationThe friction parameters of the
adaptive state-space controller are updated online using the recursive
least squares algorithm While the compensation controller uses an extended
Kalman filter to estimate the unknown friction states The experimental
investigations of both methods show clearly the superiority of the
compensation controller against the adaptive state-space controller To
achieve simultaneous compensation of the friction force and the couplings,
the non-linear compensation controller is combined with the concept of a
decoupling controller The performance of this multi-variable control
concept is finally investigated on the target system Significant reduction
in the dynamic control error is achieved for both, movements along one axis
as well as movements in three dimensions

Mehrgrößenregelung von Nanopositionier- und Nanomessmaschinen mit großen Bewegungsbereichen

Parameters in a hydrological model play a pivotal role for prediction. Good estimates of the parameters and state variables enable the model to generate accurate forecasts. In this paper, a dual state-parameter estimation approach is realised based on the localised ensemble Kalman filter (EnKF) for estimation of both parameters and state variables of a groundwater flow model. The hydraulic head field (state variable) and the distribution of heterogeneous hydraulic conductivity (parameter) are simultaneously estimated through limited groundwater level observations and the localisation method. The localisation method is used to map updated weights and correlation distances from measured grid point to the grid point to be updated. The horizontal de-correlation length is determined by geostatistical method with a value L = 25 m. The analysed results indicate that the distribution of hydraulic conductivity estimated by the localised EnKF approach could well match the real field only after five data assimilation steps with few 25 observation wells. Meanwhile, the simulation of hydraulic conductivity is significantly improved by the localised EnKF approach.

Dual state-parameter simultaneous estimation using localised ensemble Kalman filter and application in environmental model

The development of industrial control and measurement systems is often based on modular commercial off the-shelf hardware. Lately, for these platforms reconfigurable I/O modules with field-programmable gate arrays (FPGA) have gained significance, since they allow the implementation of data processing functionality very close to the data acquisition interfaces. However, algorithm complexity and floating-point support are limited by FGPA resources and design methods. This contribution presents an application specific configurable DSP soft core architecture built around a scalable double precision floating-point arithmetic/logic unit. The core can be seamlessly utilized as a functional component in Lab VIEW based FPGA designs. A small case study shows the performance of an example application implemented on the presented core in comparison to other embedded architectures.

LiSARD: LabVIEW Integrated Softcore Architecture for Reconfigurable Devices

Developing machines capable of positioning and measuring in nano-metre dimensions is an overall challenging endeavour, which not at least includes providing a highly dynamic and precise trajectory tracking control system. To effectively employ such a control system an adequately performing implementation on an embedded real-time processing system is essential for process performance and quality. In this article an implementation study of a Kalman filter component is presented, comparing the solutions for general purpose processor and digital signal processor to a range of designs for field-programmble gate arrays. Evaluating the performance of the respective implementations for a PXI platform and thus indicating the feasibility of industrial and standard-compliant application is the emphasis of this contribution.

Performance evaluation of platform-specific implementations of numerically complex control designs for nano-positioning applications

Mixing bromine and iodine within lead halide perovskites is a common strategy to tune their optical properties. This comes at the cost of instability, as illumination induces halide segregation and degrades device performances. Hence, understanding the behavior of mixed-halide perovskites is crucial for applications. In 3D perovskites such as MAPb(BrxI1–x)3 (MA = methylammonium), all of the halide crystallographic sites are similar, and the consensus is that bromine and iodine are homogeneously distributed prior to illumination. By analogy, it is often assumed that Ruddlesden–Popper layered perovskites such as (BA)2MAPb2(BrxI1–x)7 (BA = butylammonium) behave alike. However, these materials possess a much wider variety of halide sites featuring diverse coordination environments, which might be preferentially occupied by either bromine or iodine. This leaves an open question: are mixed-halide Ruddlesden–Popper perovskites really mixed? By combining powder and single-crystal diffraction experiments, we demonstrate that this is not the case: bromine and iodine in RP perovskites preferentially occupy different sites, regardless of the crystallization speed.

Are Mixed-Halide Ruddlesden–Popper Perovskites Really Mixed?

ADVERTISEMENT RETURN TO ISSUEViewpointNEXTNo One Size Fits All: Semiconductor Nanocrystal Sizing CurvesMasaru Kuno*Masaru KunoDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United StatesDepartment of Physics, University of Notre Dame, Notre Dame, Indiana 46556, United States*[email protected]More by Masaru Kunohttps://orcid.org/0000-0003-4210-8514, Irina GushchinaIrina GushchinaDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United StatesMore by Irina Gushchina, Stefano TosoStefano TosoDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United StatesItalian Institute of Technology, Via Morego, 30 16163 Genova, ItalyInternational Doctoral Program in Science, Università Cattolica del Sacro Cuore, 25121 Brescia, ItalyMore by Stefano Tosohttps://orcid.org/0000-0002-1621-5888, and Vadim TrepalinVadim TrepalinDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United StatesMore by Vadim TrepalinCite this: J. Phys. Chem. C 2022, 126, 29, 11867–11874Publication Date (Web):July 15, 2022Publication History Received5 July 2022Published online15 July 2022Published inissue 28 July 2022https://doi.org/10.1021/acs.jpcc.2c04734Copyright © Published 2022 by American Chemical SocietyRIGHTS & PERMISSIONSArticle Views1566Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (3 MB) Get e-AlertsSUBJECTS:Absorption,Cadmium selenide,Energy,Transmission electron microscopy,X-ray scattering Get e-Alerts 

Irina Gushchina

Papers

Control of nanopositioning and nanomeasuring machines with a modular FPGA based data processing system

LiSARD: LabVIEW Integrated Softcore Architecture for Reconfigurable Devices

Performance evaluation of platform-specific implementations of numerically complex control designs for nano-positioning applications

Are Mixed-Halide Ruddlesden–Popper Perovskites Really Mixed?

No One Size Fits All: Semiconductor Nanocrystal Sizing Curves