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Combining Robust Control and Machine Learning for Uncertain Nonlinear systems Subject to Persistent Disturbances

Combining Robust Control and Machine Learning for Uncertain ...

引用

IEEE Conference on Decision and Control

作者： A. Banderchuk D. Coutinho E. Camponogara Post-graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis SC Brazil Department of Automation and Systems Universidade Federal de Santa Catarina Florianópolis SC Brazil

This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent disturbances. Firstly, the robust controller is designed to ensure that the closed-loop system is Input-to-State Stable (ISS) with a guaranteed stability region regardless of the ESN control action and exogenous disturbances. Then, the ESN-based controller is trained in order to mitigate the effects of disturbances on the system output. A numerical example demonstrates the potential of the proposed control design method.

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A weblab control experiment using the ball and beam system and multiobjective optimization 5

A weblab control experiment using the ball and beam system a...

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5th Experiment at International Conference, exp.at 2019

作者： Kagami, Ricardo Massao Kovalski Da Costa, Guinther Mendes, Luciano Antonio Freire, Roberto Zanetti Industrial and Systems Engineering Graduate Program-PPGEPS Pontifícia Universidade Católica Do Paraná-PUCPR Curitiba Brazil Department of Control and Automation Engineering Pontifícia Universidade Católica Do Paraná-PUCPR Curitiba Brazil

ISBN: (纸本)9781728136370

y associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with possibilities of increasing both students' knowledge and skills. Control engineering is an area where educational laboratories are usually costly, thus the use of virtual laboratories for remote experimentation became an interesting approach. In this work, it is presented a remote experimentation procedure for the ball and beam system, which is a nonlinear and unstable open loop process. Considering the advanced control topic, multiobjective optimization was introduced in the experiment in order to tune Proportional-Integral-Derivative (PID) controllers. Through the description of the system model, the multiobjective optimization technique, and the experiment configuration, students can simulate and test their controllers remotely in a real plant. © 2019 IEEE.

关键词： Multiobjective optimization

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Particle Swarm Optimization with Quasi-Newton Local Search for Solving Economic Dispatch Problem

Particle Swarm Optimization with Quasi-Newton Local Search f...

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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Viviana Cocco Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Curitiba Brazil

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper discusses the use of PSO with a Quasi-Newton (QN) local search method. The PSO is used to produce good potential solutions, and the QN is used to fine-tune of final solution of PSO. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects.

关键词： Particle swarm optimization Power generation Power generation economics Fuel economy Cost function Equations Power system economics System testing Character generation Constraint optimization

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Hardware-based parallel firefly algorithm for embedded applications

Hardware-based parallel firefly algorithm for embedded appli...

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2013 NASA/ESA Conference on Adaptive Hardware and systems, AHS 2013

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos Santos Coelho, Leandro Ayala-Rincón, Mauricio Electronics Engineering Graduate Program Faculty of Gama University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Departments of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781467363839

The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications. © 2013 IEEE.

关键词： Parallel architectures

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What can a big program teach us about optimization?

What can a big program teach us about optimization?

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5th International Symposium on Search-Based Software engineering, SSBSE 2013

作者： De Oliveira Barros, Márcio De Almeida Farzat, Fábio Post-graduate Information Systems Program PPGI/UNIRIO Av. Pasteur 458 Urca - Rio de Janeiro RJ Brazil Computers and System Engineering Program COPPE/UFRJ Cidade Universitária Cx Postal 68501 Rio de Janeiro RJ Brazil

ISBN: (纸本)9783642397417

In this paper we report on the evolution of Apache Ant, a build automation tool developed in Java. We observed a typical case of architectural mismatch in this system: its original simple design was lost due to maintenance and addition of new features. We have applied SBSE techniques to determine whether the search would be able to recover at least parts of the original design, in a metrics-based optimization. We observed that current SBSE techniques produce complex designs, but they also allow us to study the limitations of present design metrics. In the end, we propose a new research perspective joining software clustering and refactoring selection to improve software evolution. © 2013 Springer-Verlag.

关键词： Optimization

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Computation of resistance and potential of grounding grids in any geometry 16

Computation of resistance and potential of grounding grids i...

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16th International Conference on Environment and Electrical engineering, EEEIC 2016

作者： Pires, Thyago G. Nerys, Jose W. L. Silva, Carlos L. B. Oliveira, Diogo N. Filho, Antonio M. Silva Calixto, Wesley P. Alves, Aylton J. School of Electric and Computing Engineering Federal University of Goias Goiania Brazil Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil Experimental and Technologic Research and Study Group Federal Institute of Education Science and Technology Goiania Brazil

ISBN: (纸本)9781509023196

This paper deals with the computation of ground resistance, surface voltage, touch voltage and step voltage, to mesh with horizontal wires arranged in different angles. The computer program implemented used in the mathematical modeling is based on the method proposed by Heppe, which allows obtaining the grounding parameters for homogeneous soil and soil stratified in two layers. The results obtained with the proposed method will be compared with other methods in literature. Also will be presented the results of a grounding grid using wires at various angles. © 2016 IEEE.

关键词： Mesh generation

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Optimization of grounding grid's multidesign geometry 16

Optimization of grounding grid's multidesign geometry

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16th International Conference on Environment and Electrical engineering, EEEIC 2016

作者： Silva, Carlos L. B. Oliveira, Diogo N. Pires, Thyago G. Nerys, Jose W. L. Barbosa, Paulo H. S. Calixto, Wesley P. Alves, Aylton J. Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil School of Electric and Computing Engineering Federal University of Goias Goiania Brazil Experimental Technologic Research and Study Group Federal Institute of Education Science and Technology Goiania Brazil

ISBN: (纸本)9781509023196

This paper deals with the optimization of grounding grids geometry. The goal is to reduce the amount of material to deploy a grounding grid, while keeping the system security. The touch voltages, step voltages, GPR and ground resistance are parameters of grounding grids and are related to safety aspect. Also discussed is a genetic algorithm used for optimizing ground grids, which can assume any form in a limited space of the project. The simulation is based in images method. The results are presented and discussed. © 2016 IEEE.

关键词： Ground penetrating radar systems

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Training Swinging Door Trending Compression Algorithm for IoT devices

Training Swinging Door Trending Compression Algorithm for Io...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Juan David Arias Correa Alex Sandro Roschildt Pinto Carlos Montez Post-graduate Program of Automation Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms.

关键词： Training Performance evaluation Communication systems Data compression Prediction algorithms Market research Internet of Things Computational complexity Compression algorithms

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Capacitance Estimation Algorithm for Condition Monitoring of Electrolytic DC-Link Capacitors Using Artificial Neural Network in Front-End Diode Rectifier Three-Phase Motor Drive systems

Capacitance Estimation Algorithm for Condition Monitoring of...

引用

IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Mateus Abreu de Andrade Rodolfo César Costa Flesch Graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis Brazil

A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.

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Creating Mathematical Models to Help Formulate Company Strategies for Knowledge Management System Implementation 9

Creating Mathematical Models to Help Formulate Company Strat...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Pranata, Dewi Sagita BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jakarta13220 Indonesia King's College London Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences Department of Informatics Strands West MinsterWC2R 2LS United Kingdom

ISBN: (纸本)9798350390025

This research aims to build a mathematical model to formulate the problems of implementing knowledge management systems in companies that often face obstacles in achieving the desired objectives and goals. With increasing competition in the business sector, organizations or organizations realize the importance of utilizing the knowledge assets that reside in each individual and organization. If this knowledge can be managed optimally, it can become a competitive advantage for the company due to the emergence of innovative ideas by the concepts of knowledge management theory. By implementing optimal knowledge management (KM), companies can design innovative solutions to improve business operations and increase overall revenue. The factor analysis method will be used to find the determining factors for the success of the implementation of knowledge management systems (KMS) and the regression analysis method will also be used to form a mathematical model of several new factors which are formed as independent variables with the current level of community understanding of KMS as the dependent variable. The research results provide insight into strategies to improve success factors to successfully facilitate KMS implementation. This study contributes to existing knowledge management by providing insight into dynamics that go beyond the technical aspects of KMS, ultimately developing strategies for more effective and efficient utilization of knowledge and organizational growth and supporting competitive advantage for companies. © 2024 IEEE.

关键词： Knowledge organization system (KOS)

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