Search results for "optimal"

showing 10 items of 706 documents

Common best proximity points and global optimal approximate solutions for new types of proximal contractions

2015

Let $(\mathcal{X},d)$ be a metric space, $\mathcal{A}$ and $\mathcal{B}$ be two non-empty subsets of $\mathcal{X}$ and $\mathcal{S},\mathcal{T}: \mathcal{A} \to \mathcal{B}$ be two non-self mappings. In view of the fact that, given any point $x \in \mathcal{A}$, the distances between $x$ and $\mathcal{S}x$ and between $x$ and $\mathcal{T}x$ are at least $d(\mathcal{A}, \mathcal{B}),$ which is the absolute infimum of $d(x, \mathcal{S} x)$ and $d(x, \mathcal{T} x)$, a common best proximity point theorem affirms the global minimum of both the functions $x \to d(x, \mathcal{S}x)$ and $x \to d(x, \mathcal{T}x)$ by imposing the common approximate solution of the equations $\mathcal{S}x = x$ and $…

common best proximity pointproximally commuting mappingsSettore MAT/05 - Analisi Matematicaoptimal approximate solution
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Second order optimality conditions with applications

2007

International audience; The aim of this article is to present the algorithm to compute the first conjugate point along a smooth extremal curve. Under generic assump- tions, the tra jectory ceases to be optimal at such a point. An implementation of this algorithm, called cotcot, is available online and based on recent devel- opments in geometric optimal control. It is applied to analyze the averaged optimal transfer of a satellite between elliptic orbits.

conjugate points[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]time optimal control49K15 70Q05Orbital transfer[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Riemannian systems with drift
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Second order optimality conditions in optimal control with applications

2006

The aim of this article is to present the algorithm to compute the first conjugate point along a smooth extremal curve. Under generic assumptions, the trajectory ceases to be optimal at such a point. An implementation of this algorithm, called \texttt{cotcot}, is available online and based on recent developments in geometric optimal control. It is applied to analyze the averaged optimal transfer of a satellite between elliptic orbits.

conjugate points[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]time optimal control49K15 70Q05orbital transfer[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Riemannian systems with drift
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Estabilización de modelos económicos dinámicos con control óptimo en tiempo continuo

1990

En esta Tesis de Licenciatura se lleva a cabo el estudio de un problema determinado de optimización dinámica y sus aplicaciones en el campo de la Ciencia Económica. Un problema de optimización consiste, fundamentalmente, en la búsqueda de un extremo de una función o un funcional objetivo que proporcione un máximo o un mínimo para esa función. Cuando se habla de optimización dinámica hay que incorporar el factor tiempo al problema, en todas y cada una de las diferentes variables que intervienen, lo que afectará a los modelos matemáticos que se empleen para representar el comportamiento y las relaciones existentes entre dichas variables. También afecta al funcional objetivo a optimizar. Así, …

continuous timeUNESCO::MATEMÁTICAS::Investigación operativa::Inventariostiempo continuoUNESCO::CIENCIAS ECONÓMICASUNESCO::CIENCIAS ECONÓMICAS::Teoría económicaUNESCO::MATEMÁTICAS::Investigación operativa::Sistemas de controlcontrol óptimostabilizationoptimal controlUNESCO::CIENCIAS ECONÓMICAS::Teoría económica::Teorías de la estabilizaciónUNESCO::MATEMÁTICAS::Investigación operativa::Programación dinámicadynamical systems in Economicsestabilizaciónmodelos económicos dinámicos
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Predictive control of convex polyhedron LPV systems with Markov jumping parameters

2012

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon…

convex polyhedronMarkov chainlinear parameter varying systemsLinear systemMathematicsofComputing_NUMERICALANALYSISLinear matrix inequalityOptimal controlModel predictive controlControl theoryConvex polytopeConvex optimizationMarkov jumping parametersInvariant (mathematics)predictive controlMathematics2012 24th Chinese Control and Decision Conference (CCDC)
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Disease dispersion as a spatial interaction: The case of Flavescence Dorée

2020

International audience; Flavescence dorée is a serious and incurable vine disease transmitted by an insect vector. Focusing on its spatial diffusion and on its control with pesticides, this paper investigates the private strategies of wine producers and their socially optimal counterparts. The socially optimal regulation has to address two externalities regarding private treatment decisions: (a) the insufficient consideration of collective benefits from controlling the vector populations; (b) the failure to take into account environmental damage related to pesticide application. The probability of infection is estimated on French data from a spatial econometric specification. Three alternat…

cost‐benefit analysisMandatory treatmentJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q12 - Micro Analysis of Farm Firms Farm Households and Farm Input MarketsCompulsory treatmentEnvironmental Science (miscellaneous)environmental externalityAnalyse cout-benefice0502 economics and businessEconometricsStatistical dispersion050207 economicsExternalité environnementaleMathematicsGestion des nuisibles2. Zero hungercompulsory treatmentJEL: H - Public Economics/H.H2 - Taxation Subsidies and Revenue/H.H2.H21 - Efficiency • Optimal Taxation[QFIN]Quantitative Finance [q-fin]Spatial interactioncost-benefit analysis05 social sciencesTraitement obliatoire[SHS.ECO]Humanities and Social Sciences/Economics and Financespatial spilloverspest management13. Climate actionModeling and SimulationFlavescence doréeJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q51 - Valuation of Environmental Effects050202 agricultural economics & policy
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Exploratory remarks and discussion on a potential program for interlock even more the mathematics and physics

2021

These remarks are endowed with exploratory argumentation for disrupt further discussion and in favor of the in-depth consolidation of a mathematical and physics identification based on 2 key concepts: 1) finite support and 2) a notion of infinite intrinsic to the usage of the complex numbers. General relativity shows up linked to a kind of a Gelfand representation as an approximation of an analog of a hidden Markov Model. This has deep connections with the Stone–Weierstrass theorem and these discussion are an invitation to the physics community to study the physics x mathematics identification in the case of a holding true multiverse hypothesis. Photon in this setup stands to the analog of …

covariance matrix:FÍSICA [UNESCO]UNESCO::FÍSICAwhitening transformationconvolutioncombinatorics polynomialsoptimal basis
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A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem

2017

A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. peerReviewed

data-driven optimizationPareto optimalityEngineeringBlast furnaceMathematical optimizationOptimization problemmodel managementblast furnaceEvolutionary algorithm02 engineering and technologyMulti-objective optimizationIndustrial and Manufacturing Engineering020501 mining & metallurgyData-drivenironmakingoptimointi0202 electrical engineering electronic engineering information engineeringGeneral Materials Scienceta113business.industrypareto-tehokkuusMechanical EngineeringProcess (computing)metamodelingMetamodeling0205 materials engineeringmulti-objective optimizationMechanics of MaterialsPrincipal component analysis020201 artificial intelligence & image processingbusinessrautateollisuus
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LPV model identification for gain scheduling control: An application to rotating stall and surge control problem

2006

Abstract We approach the problem of identifying a nonlinear plant by parameterizing its dynamics as a linear parameter varying (LPV) model. The system under consideration is the Moore–Greitzer model which captures surge and stall phenomena in compressors. The control task is formulated as a problem of output regulation at various set points (stable and unstable) of the system under inputs and states constraints. We assume that inputs, outputs and scheduling parameters are measurable. It is worth pointing out that the adopted technique allows for identification of an LPV model's coefficients without the requirements of slow variations amongst set points. An example of combined identification…

decentralized controlEngineeringbusiness.industryApplied MathematicsSystem identificationStall (fluid mechanics)Control engineeringconsensus protocolOptimal controlconsensus protocolsDecentralised systemComputer Science Applicationsoptimal controlNonlinear systemGain schedulingControl and Systems EngineeringControl theorynetworksSettore MAT/09 - Ricerca OperativaElectrical and Electronic EngineeringSurgebusinessSurge controlconsensus protocols; decentralized control; optimal control; networksControl Engineering Practice
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An analysis of model predictive control with integral action applied to digital displacement cylinders

2020

This article aims to analyze Model Predictive Control (MPC) for the control of multi-chamber cylinders. MPC with and without integral action has been introduced. Three different algorithms have been used to solve the optimization problem in the MPC. The different algorithms have been compared with an industrial solver. The influence of changing mass, choosing a different middle line pressure, system delays, signal noise, velocity estimation, and changing pressure levels has been investigated. It is concluded that for the small prediction horizon used in the paper a simple algorithm such as A can produce results as good as the previously used Differential Evolution algorithm in less than hal…

digital displacement cylindersOptimizationbusiness.industryStructural engineeringVDP::Mechanical engineering: 570lcsh:QA75.5-76.95Computer Science ApplicationsDigital Displacement CylindersIntegral actionModel predictive controlModell-prediktiv reguleringControl and Systems EngineeringVDP::Maskinfag: 570Modeling and SimulationOptimaliseringDisplacement (orthopedic surgery)lcsh:Electronic computers. Computer scienceModel predictive controlbusinessSoftwareModel Predictive ControlMathematics
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