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arXiv 2018年

作者： Modos, Istvan Sucha, Premysl Hanzalek, Zdenek Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Czech Institute of Informatics Robotics and Cybernetics Czech Technical University

In this work, we consider a scheduling problem faced by production companies with large electricity consumption. Due to the contract with the electric utility, the production companies are obligated to comply with the total energy consumption limits in the specified time intervals (usually 15-minutes long);otherwise, the companies pay substantial penalty fees. Although it is possible to design production schedules that consider these limits as hard constraints, uncertainties occurring during the execution of the schedules are usually not taken into account. This may lead to situations in which the unexpected delays of the operations cause the violations of the energy consumption limits. Our goal is to design robust production schedules pro-actively guaranteeing that the energy consumption limits are not violated for the given set of uncertainty scenarios. We consider scheduling on one machine with release times of the operations and total tardiness as the objective function. To tackle this problem, we first propose a pseudo-polynomial algorithm for finding the optimal robust schedule for the given permutation of the operations. This algorithm is then utilised in three different algorithms for finding the optimal permutation: Two exact (Branch-and-Bound and logic-based Benders decomposition) and one heuristic algorithm (tabu search). All the algorithms were experimentally evaluated on random instances with different sizes of the uncertainty scenarios set. Using the tabu search algorithm, we are able to solve large instances within one minute. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric power utilization

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Algae Textile and Bioplastic Kit for Space Travel and Sustainable Living Applications for the Future of Wellbeing 19

Algae Textile and Bioplastic Kit for Space Travel and Sustai...

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19th IAA Symposium on Visions and Strategies 2021 at the 72nd International Astronautical Congress, IAC 2021

作者： Neidlinger, Kristin Musilova, Michaela Sensoree Therapeutic Biomedia San FranciscoCA United States DesignLab University Twente Netherlands International MoonBase Alliance United States Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology STU Bratislava Slovakia Bratislava Slovakia

ISBN: (纸本)9781713843146

Textile based wellness is a global need. As skin absorbs directly from the environment, ten percent of the chemicals in clothing transfer to the skin and body. What if we obtained vital nutrients like oxygen and vitamins directly with our textiles? This would have significant implications for the sustainability of human space travel. Current research shows algae as a lifeform suitable for growing in space orbit. It is small and weightless, and can be grown and implemented as a material resource from soft textiles to sturdy plastics. It also can be composted or reconstituted into new shapes and designs. For this research, an algae-based bioplastics and textiles kit was created for testing for space applications during the fourth EMMIHS analog lunar mission (February 1-15, 2020) at the Hawaii - Space Exploration Analog and Simulation (HI-SEAS) habitat in Hawai’i, USA. It was part of a collaboration between the EuroMoonMars initiative by ILWEG, the International Moonbase Alliance and HI-SEAS. For the simulation, a closed loop DIY kit for growing and composting Algae Textile for space habitats was studied. Soft textiles to hard plastics were iterated in the controlled air environment for potential use in space travel. It was found that astronauts may create unique textiles with oxygen prolific health benefits. The textiles have the potential to act as a portable source of photosynthesis, as well as be a sensor to record stress levels and note correlations with atmospheric events. It is possible to extract time dated scientific data at the end of the study to gain insights on human wellbeing during the mission. Finally, the textile may be composted then repurposed. The fabric may also be infused with the wearers’ DNA to become a surrogate skin to record growth and environmental stresses of microgravity, as it becomes an agent to monitor the effects of travel. As space travel is known to cause DNA and RNA degeneration, there is potential to counteract hardships with chlor

关键词： Algae

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Influence of power supply on airport navigation lamps photometric test accuracy

Influence of power supply on airport navigation lamps photom...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Kacper Podbucki Jakub Suder Tomasz Marciniak Adam Dąrowski Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Poznan University of Technology Poznań Poland

The paper presents research on the accuracy of measuring illuminance and chromaticity of airport lamps. The impact of the type of DC and AC power supply on measurement was assessed with the use of electronic sensors. BH1750 and BH1745 type sensors in a microprocessor system with an I 2 C interface were used for the measurements. A professional luxmeter was used for comparison purposes. Experimental tests were carried out under laboratory conditions for three types of halogen lamps: approach system lamps, runway centerline lamps, and touchdown zone lamps.

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Fast Prototyping of In-Pavement Airport Navigation Lamp Prism Classification

Fast Prototyping of In-Pavement Airport Navigation Lamp Pris...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Jakub Suder Tomasz Marciniak Division of Electronic Systems and Signal Processing Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań Poland

The paper presents an analysis of fast selection of neural network for the purpose of visual analysis of mechanical wear on prism lenses of in-pavement airport navigational lighting systems. This issue is particularly important in terms of aviation safety and navigational lighting control, regulated by EASA and ICAO. The article is the next stage of the development of the system for the vision control of lamps, in which the concept of using a different neural network with an increased data set prepared by the authors is presented. The Deep Network Designer tool included in the Matlab 2022b environment was used. The solution using the GoogLeNet neural network allows for the classification of lamps with an accuracy of 88.37%.

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Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Connected Inverters 49

Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Conne...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Hosseinabadi, Pooyan Alinaghi Kermadi, Mostefa Pota, Hemanshu Mekhilef, Saad Abadi, Ali Soltani Sharif The School of Engineering and Information Technology The University of New South Wales CanberraACT Australia Kuala Lumpur Malaysia The School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia Institute of Automatic Control and Robotics Warsaw University of Technology Faculty of Mechatronics Warsaw Poland

ISBN: (纸本)9798350331820

This paper proposes and experimentally implements new phase-locked loop algorithms using non-adaptive and adaptive terminal sliding modes for the three-phase grid-connected inverters. The proposed algorithms aim to extract the grid voltage phase and frequency and provide them for the inverter controller. The proposed sliding mode-based PLL algorithms provide faster, more robust, and more accurate detection of the grid voltage information compared to the conventional PI-PLL. This leads to better current controller performance and subsequently, improves the quality of the injected currents into the grid. The finite-time stability notion is incorporated with robust sliding modes to ensure a fast convergence rate. An adaptive law is proposed to determine a proper value for the switching gain which leads to a better overall performance of the PLL compared with a non-adaptive one. The Lyapunov stability theory is used to obtain the stability proofs of the closed-loop systems under both designed sliding modes-based PLLs. The proposed PLL algorithms are validated by simulation and experimental results for the three-phase grid-connected inverter under normal and various abnormal grid conditions. © 2023 IEEE.

关键词： Phase locked loops

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Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme

arXiv

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arXiv 2021年

作者： Weibel, Jean-Baptiste Patten, Timothy Vincze, Markus Vision for Robotics Laboratory Automation and Control Institute TU Wien Austria Robotics Institute Faculty of Engineering and Information Technology University of Technology Sydney Australia

While object semantic understanding is essential for most service robotic tasks, 3D object classification is still an open problem. Learning from artificial 3D models alleviates the cost of annotation necessary to approach this problem, but most methods still struggle with the differences existing between artificial and real 3D data. We conjecture that the cause of those issue is the fact that many methods learn directly from point coordinates, instead of the shape, as the former is hard to center and to scale under variable occlusions reliably. We introduce spherical kernel point convolutions that directly exploit the object surface, represented as a graph, and a voting scheme to limit the impact of poor segmentation on the classification results. Our proposed approach improves upon state-of-the-art methods by up to 36% when transferring from artificial objects to real objects. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Remote Labolatory with Modular Inertial Measuring Unit Platform

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Procedia engineering 2014年 96卷 345-354页

作者： Lukáš Palkovič Jozef Rodina Ľuboš Chovanec Anežka Chovancová Peter Hubinský Faculty of Electrical Engineering and Information Technology Institute of Control Engineering and Industrial Informatics Slovak University of Technology Ilkovičova 3 812 19 Bratislava Slovakia

The document describes the usage of an inertial measurement unit platform in a remote laboratory. The platform is based on widely used modern MEMS components, such as accelerometers and gyroscopes, in combination with digital signal processing and web technologies. Students can work on the real device from anywhere in the world. They can measure data from a real process remotely and subsequently train various signal processing techniques using this data. They can also get familiar with the properties and drawbacks of the inertial sensors used on the remotely controlled device.

关键词： Remote laboratory Teaching aids Inertial Measuring Unit MEMS sensors Sensor fusion

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Using AdaBoost-based Multiple Functional Neural Fuzzy Classifiers Fusion for Classification Applications

Using AdaBoost-based Multiple Functional Neural Fuzzy Classi...

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3rd International Conference on Inventions, ICI 2017

作者： Jhang, Jyun-Yu Lee, Chin-Ling Lin, Cheng-Jian Lin, Chin-Teng Young, Kuu-Young Institute of Electrical and Control Engineering National Chiao-Tung University Hsinchu300 Taiwan National Taichung University of Science and Technology Taichung411 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung411 Taiwan Department of Electrical and Control Engineering National Chiao Tung University Hsinchu300 Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Sydney2007 Australia

In this study, two intelligent classifiers, the AdaBoost-based incremental functional neural fuzzy classifier (AIFNFC) and the AdaBoost-based fixed functional neural fuzzy classifier (AFFNFC), are proposed for solving the classification problems. The AIFNFC approach will increase the amount of functional neural fuzzy classifiers based on the corresponding error during the training phase;while the AFNFC approach is equipped with a fixed amount of functional neural fuzzy classifiers. Then, the weights of AdaBoost procedure are assigned for classifiers. The proposed methods are applied to different classification benchmarks. Results of this study demonstrate the effectiveness of the proposed AIFNFC and AFFNFC methods. © The Authors, published by EDP Sciences, 2018.

关键词： Adaptive boosting

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Design of Neuro-controllers for Nonlinear Continuous-time Systems using Evolutionary Algorithm*

Design of Neuro-controllers for Nonlinear Continuous-time Sy...

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International Conference on control, Decision and information Technologies (CoDIT)

作者： Ivan Sekaj Ivan Kenický Filip Zúbek Jaromír Skirkanič Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Slovak Republic

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper presents the design of controllers for nonlinear continuous-time dynamic systems based on neuroevolution. The controller employs an artificial neural network of the MLP type, with network elements of weights and thresholds, parameterized by a genetic algorithm by minimization of a selected criterion function, which measures the closed-loop's performance index. Two distinct neural network architectures are introduced: a feedforward neural network and a proposed summation-differentiation recurrent neural network. Experimental comparisons are made between the two neural controllers and a conventional PID controller. This study employs a parallel genetic algorithm for neural network learning to address the challenge of finding (sub-)optimal neural network parameters, which is able to eliminate the convergence in some weak local optima. Despite increased computational complexity, these architectures deliver high performance, reliable and robust results.

关键词： Weight measurement Recurrent neural networks Computer architecture Artificial neural networks Search problems Performance analysis Reliability Optimization Genetic algorithms Convergence

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Convergence Analysis of the Short-Memory Principle for Fractional Models

Convergence Analysis of the Short-Memory Principle for Fract...

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European control Conference (ECC)

作者： Oliver Stark Felix Strehle Sören Hohmann Faculty of Electrical Engineering and Information Technology Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

This paper deals with the convergence analysis of a closed-form solution for fractional models with the short-memory principle. Fractional models are increasingly used to describe complex physical, chemical, or biological systems. However, calculating the output signal of a fractional model necessitates an actual closed-form solution, which in turn requires the system to be at rest at the beginning of the simulation. In this work, we drop the restriction of a system at rest by presenting a closed-form solution based on the short-memory principle. This extension then allows, for example, to perform parameter identification during run time. The second contribution is the convergence analysis of the closed-form solution with the short-memory principle. A necessary property regarding the fractional order is derived such that the closed-form solution with the short-memory principle converges to the closed-form solution of the system at rest.

关键词： Analytical models Closed-form solutions Parameter estimation Biological system modeling Europe Linear programming Error correction codes

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