Search results for "Ability"

showing 10 items of 18559 documents

New results on stability analysis and stabilization of time-delay continuous Markovian jump systems with partially known rates matrix

2015

Summary In this note, the problems of stability analysis and controller synthesis of Markovian jump systems with time-varying delay and partially known transition rates are investigated via an input–output approach. First, the system under consideration is transformed into an interconnected system, and new results on stochastic scaled small-gain condition for stochastic interconnected systems are established, which are crucial for the problems considered in this paper. Based on the system transformation and the stochastic scaled small-gain theorem, stochastic stability of the original system is examined via the stochastic version of the bounded realness of the transformed forward system. Th…

0209 industrial biotechnologyStochastic stabilityMechanical EngineeringGeneral Chemical EngineeringBiomedical EngineeringRegular polygonStability (learning theory)Aerospace Engineering02 engineering and technologyIndustrial and Manufacturing EngineeringMarkovian jumpMatrix (mathematics)020901 industrial engineering & automationControl and Systems EngineeringSystem transformationControl theoryBounded function0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingElectrical and Electronic EngineeringMathematicsInternational Journal of Robust and Nonlinear Control
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Thermo-Hydraulic Modelling and Experimental Validation of an Electro-Hydraulic Compact Drive

2021

Electro-hydraulic compact drives (ECDs) are an emerging technology for linear actuation in a wide range of applications. Especially within the low power range of 5–10 kW, the plug-and-play capability, good energy efficiency and small space requirements of ECDs render this technology a promising alternative to replace conventional valve-controlled linear drive solutions. In this power range, ECDs generally rely on passive cooling to keep oil and system temperatures within the tolerated range. When expanding the application range to larger power classes, passive cooling may not be sufficient. Research investigating the thermal behaviour of ECDs is limited but indeed required for a successful …

0209 industrial biotechnologyTechnologyControl and OptimizationSelf-contained cylinder drivePassive coolingComputer scienceEnergy Engineering and Power TechnologyMechanical engineering02 engineering and technologyenergy efficient fluid powerEnergy efficient fluid power020901 industrial engineering & automationElectro-hydraulic compact drivesthermal modelling; energy efficient fluid power; direct driven hydraulic drives; pump-controlled cylinder; electro-hydraulic compact drives; self-contained cylinder driveThermal0202 electrical engineering electronic engineering information engineeringRange (statistics)thermal modellingElectrical and Electronic Engineeringdirect driven hydraulic drivesEngineering (miscellaneous)Conservation of massPump-controlled cylinderRenewable Energy Sustainability and the EnvironmentT020208 electrical & electronic engineeringself-contained cylinder drivepump-controlled cylinderelectro-hydraulic compact drivesDirect driven hydraulic drivesPower (physics)VDP::Teknologi: 500Thermal modellingSystems designTransient (oscillation)Energy (miscellaneous)Efficient energy useEnergies
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Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population

2019

We consider a multi-population, represented by a network of groups of individuals. Every player of each group can choose between two options, and we study the problem of reaching consensus. The dynamics not only depend on the dynamics within the group, but they also depend on the topology of the network, so neighboring groups influence individuals as well. First, we develop a mathematical model of this networked bio-inspired evolutionary behavior and we study its steady-state. We look at the special case where the underlying network topology is a regular and unweighted graph and show that the steady-state is a consensus equilibrium. A sufficient condition for exponential stability is given.…

0209 industrial biotechnologyTheoretical computer scienceComputer scienceMulti-agent system020208 electrical & electronic engineering02 engineering and technologyNetwork topologyGroup decision-making020901 industrial engineering & automationExponential stability0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)Special caseEvolutionary dynamicsTopology (chemistry)2019 18th European Control Conference (ECC)
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Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs

2020

Abstract Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF),…

0209 industrial biotechnologyTraceabilityComputer sciencebusiness.industry0211 other engineering and technologies02 engineering and technologycomputer.file_formatThread (computing)External Data Representation020901 industrial engineering & automationProduct lifecycleArtificial IntelligenceInformation model021105 building & constructionThreading (manufacturing)Software engineeringbusinessISO 10303computerQuality assuranceInformation SystemsAdvanced Engineering Informatics
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Adjusted bat algorithm for tuning of support vector machine parameters

2016

Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…

0209 industrial biotechnologyWake-sleep algorithmActive learning (machine learning)Computer scienceStability (learning theory)Linear classifier02 engineering and technologySemi-supervised learningcomputer.software_genreCross-validationRelevance vector machineKernel (linear algebra)020901 industrial engineering & automationLeast squares support vector machine0202 electrical engineering electronic engineering information engineeringMetaheuristicBat algorithmStructured support vector machinebusiness.industrySupervised learningOnline machine learningParticle swarm optimizationPattern recognitionPerceptronGeneralization errorSupport vector machineKernel methodComputational learning theoryMargin classifierHyperparameter optimization020201 artificial intelligence & image processingData miningArtificial intelligenceHyper-heuristicbusinesscomputer2016 IEEE Congress on Evolutionary Computation (CEC)
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Design of a telescopic tower for wind energy production with reduced environmental impact

2019

A prototype of a telescopic pole for wind energy production with low environmental impact and its lifting system for a 60 to 250 kW turbine and a height of 30 m have been designed and manufactured. A telescopic tower, which is raised and lowered by automation or by remote control, allows to differentiate the presence of the generator within the landscape over time. The technology currently available for lifting and lowering wind turbines is made up of telescopic poles of heights of less than 10 meters and with tilting posts of height below 30 m. Without a state of the art to refer to, the telescopic pole and its lifting system have been designed starting from scratch and solving with innova…

0209 industrial biotechnologyWind powerRenewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industryMechanical Engineering02 engineering and technology021001 nanoscience & nanotechnologyTurbineAutomationIndustrial and Manufacturing Engineeringlaw.inventionSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationlawManagement of Technology and InnovationTelescopic tower wind turbine tower mechanical design finite element methodGeneral Materials ScienceEnvironmental impact assessment0210 nano-technologybusinessRemote controlDecoupling (electronics)Efficient energy useMarine engineering
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VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS

2014

International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…

0209 industrial biotechnologybusiness.industryComputer scienceInstrumental variablePosterior probabilityBayesian probabilityPattern recognitionFeature selection02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingLogistic regression01 natural sciences010104 statistics & probability020901 industrial engineering & automationCohortProbability distributionBayesian hierarchical modelingArtificial intelligence0101 mathematicsbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSelection (genetic algorithm)[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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New delay-dependent stability of Markovian jump neutral stochastic systems with general unknown transition rates

2015

This paper investigates the delay-dependent stability problem for neutral Markovian jump systems with generally unknown transition rates GUTRs. In this neutral GUTR model, each transition rate is completely unknown or only its estimate value is known. Based on the study of expectations of the stochastic cross-terms containing the integral, a new stability criterion is derived in terms of linear matrix inequalities. In the mathematical derivation process, bounding stochastic cross-terms, model transformation and free-weighting matrix are not employed for less conservatism. Finally, an example is provided to demonstrate the effectiveness of the proposed results.

0209 industrial biotechnologygeneral uncertain transition rateStability criterionModel transformationDelay-dependent stability02 engineering and technologyTransition rate matrixStability (probability)neutral-type stochastic systemTheoretical Computer ScienceDelay dependentMatrix (mathematics)Markovian jump020901 industrial engineering & automationControl theoryBounding overwatch0202 electrical engineering electronic engineering information engineeringApplied mathematicsMathematicscomputer.programming_languageDelay-dependent stability; neutral-type stochastic system;Markovian switching; general uncertain transition rate; mean-square exponentially stable; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern RecognitionMarkovian switchingComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsControl and Systems Engineeringmean-square exponentially stable020201 artificial intelligence & image processingcomputerInternational Journal of Systems Science
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A Hybrid Control Strategy for Quadratic Boost Converters with Inductor Currents Estimation

2020

International audience; This paper deals with a control strategy for a DC-DC quadratic boost converter. In particular, a hybrid control scheme is proposed to encompass a control law and an observer for the estimation of the system states, based only on the measurements of the input and output voltages. Differently from classical control methods, where the controller is designed from a small-signal model, here the real model of the system is examined without considering the average values of the discrete variables. Using hybrid dynamical system theory, asymptotic stability of a neighborhood of the equilibrium point is established, ensuring practical stability of the origin, which contains es…

0209 industrial biotechnologyhybrid dynamical systemsObserver (quantum physics)Computer science02 engineering and technologyDynamical systemStability (probability)020901 industrial engineering & automationQuadratic equationExponential stabilitySettore ING-INF/04 - AutomaticaControl theoryswitching systems[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic Engineeringlinear matrix inequalitiesEquilibrium pointApplied Mathematics020208 electrical & electronic engineeringobserverConvertersComputer Science ApplicationsHybrid dynamical systems Linear matrix inequalities Observer Quadratic boost converter Switching systemsControl and Systems EngineeringQuadratic boost converter
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Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

0209 industrial biotechnologyrandom projectionlcsh:Computer engineering. Computer hardwareComputational complexity theoryComputer scienceRandom projectionlcsh:TK7885-789502 engineering and technologyMachine learningcomputer.software_genresupervised learningapproximate algorithmsSet (abstract data type)regressioanalyysi020901 industrial engineering & automationdistance–based regressionalgoritmit0202 electrical engineering electronic engineering information engineeringordinary least–squaresbusiness.industrySupervised learningsingular value decompositionminimal learning machineMultilaterationprojektioRandomized algorithmkoneoppiminenmachine learningScalabilityFeedforward neural network020201 artificial intelligence & image processingArtificial intelligenceapproksimointibusinesscomputerMachine Learning and Knowledge Extraction
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