Search results for " optimization."

showing 10 items of 2333 documents

A passivity approach to control of Markovian jump systems with mixed time-varying delays

2013

This paper investigated the problem of control design for a class of stochastic systems with Markovian jump parameters and time-varying delays. For the model under consideration, a passivity-based approach is introduced for designing mode-dependent output feedback controllers with mixed discrete and distributed delays. A Lypunov-Krasovskii function (LKF) is defined to establish new required sufficient conditions for ensuring exponentially mean-square stability and the passivity criteria, simultaneously. Moreover, controller gains are calculated based on a convex optimization method by solving a Linear Matrix Inequality (LMI). Finally, simulation results are provided to illustrate the effect…

Mathematical optimizationExponential growthExponential stabilityControl theoryConvex optimizationPassivityLinear matrix inequalityFunction (mathematics)Stability (probability)Mathematics2013 XXIV International Conference on Information, Communication and Automation Technologies (ICAT)
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Delay-Range-Dependent Linear Matrix Inequality Approach to Quantized H∞ Control of Linear Systems with Network-Induced Delays and Norm-Bounded Uncert…

2010

This paper deals with a convex optimization approach to the problem of robust network-based H∞ control for linear systems connected over a common digital communication network with static quantizers. Both the polytopic and the norm-bounded uncertainties are taken into consideration separately. First, the effect of both the output quantization levels and the network conditions under static quantizers is investigated. Second, by introducing a descriptor technique, using a Lyapunov—Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-range-dependent linear matrix inequalities for the existence of the desired network-bas…

Mathematical optimizationExponential stabilityControl and Systems EngineeringControl theoryMechanical EngineeringQuantization (signal processing)Convex optimizationLinear systemLinear matrix inequalityRobust controlSystem of linear equationsMathematicsLinear dynamical systemProceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
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Multi Stage Strategies for Single Point Incremental Forming of a Cup

2008

A five stage forming strategy for Single Point Incremental Forming of a circular cylindrical cup with a height/radius ratio of one is presented. Geometrical relations are discussed and theoretical strains are calculated. The influence of forming direction (upwards or downwards) is investigated for the second stage comparing explicit FE analysis with experiments. Good agreement is found between calculated and measured thickness distribution, overall geometry and strains. Using the proposed multi stage strategy it is shown possible to produce a cup with a height close to the radius and sides parallel to the symmetry axis in about half of the depth.

Mathematical optimizationFEMMaterials scienceMulti stagemental forming - multi stage - FEMIncremental formingGeometryRadiusFinite element methodSymmetry (physics)Multi stageDistribution (mathematics)General Materials ScienceStage (hydrology)Single pointSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Geometric optimal control of the contrast problem in Magnetic Resonance Imaging

2012

Abstract The control of the dynamics of spin systems by magnetic fields has opened intriguing possibilities in quantum computing and in Nuclear Magnetic Resonance spectroscopy. In this framework, optimal control theory has been used to design control fields able to realize a given task while minimizing a prescribed cost such as the energy of the field or the duration of the process. However, some of the powerful tools of optimal control had not been used yet for NMR applications in medical imagery. Here, we show that the geometric control theory approach can be advantageously combined with NMR methods to crucially optimize the imaging contrast. This approach is applied to a benchmark proble…

Mathematical optimizationField (physics)Process (computing)Benchmark (computing)General MedicineOptimal controlSingular controlAlgorithmEnergy (signal processing)MathematicsMagnetic fieldQuantum computerIFAC Proceedings Volumes
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Limit Analysis of Structures with Stochastic Strength Variations∗

1972

Abstract On the basis of a probabilistic fomulation of the fundamental theorems of “limit analysis,” a procedure is developed which allows, with a very limited amount of computing work, the determination of a domain containing the probability distribution curve of the collapse load factor of any structure that satisfies the usual conditions for validity of the limit analysis, but has randomly distributed limit strengths. Further improvements of the bounds thus obtained can be achieved by the equivalent of either the equilibrium or the kinematic methods of limit analysis.

Mathematical optimizationFinite element limit analysisMechanical EngineeringGeneral MathematicsGeneral EngineeringProbabilistic logicAerospace EngineeringOcean EngineeringCondensed Matter PhysicsLimit superior and limit inferiorOne-sided limitLimit analysisMechanics of MaterialsAutomotive EngineeringThermodynamic limitProbability distributionApplied mathematicsLimit (mathematics)Civil and Structural EngineeringMathematicsJournal of Structural Mechanics
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Limit analysis of arch-beam structures by dynamic programming

1974

We study one-dimensional structures like arch-beams in the limit state of plastic collapse, on the ground of a two-dimensional yielding surface (bending moment and normal generalized stress). The proposed method, which is able to give a numerical solution of the problem of finding the limit load, rests on the upper bound theorem of limit analysis and uses dynamic programming. We examine also some questions linked with numerical procedures. A future work devoted to applications will complete the treatment.

Mathematical optimizationFinite element limit analysisMechanical EngineeringMathematical analysisCondensed Matter PhysicsLimit analysisMechanics of MaterialsBending momentLimit loadLimit state designArchBeam (structure)Upper bound theoremMathematicsMeccanica
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A non-hydrostatic pressure distribution solver for the nonlinear shallow water equations over irregular topography

2016

Abstract We extend a recently proposed 2D depth-integrated Finite Volume solver for the nonlinear shallow water equations with non-hydrostatic pressure distribution. The proposed model is aimed at simulating both nonlinear and dispersive shallow water processes. We split the total pressure into its hydrostatic and dynamic components and solve a hydrostatic problem and a non-hydrostatic problem sequentially, in the framework of a fractional time step procedure. The dispersive properties are achieved by incorporating the non-hydrostatic pressure component in the governing equations. The governing equations are the depth-integrated continuity equation and the depth-integrated momentum equation…

Mathematical optimizationFinite volume method010504 meteorology & atmospheric sciencesDiscretization0208 environmental biotechnology02 engineering and technologyMechanicsSolver01 natural sciencesSettore ICAR/01 - Idraulica020801 environmental engineeringUnstructured gridlaw.inventionNonlinear systemContinuity equationlawDynamic pressure Shallow waters Dispersive process Finite volume Wetting and drying Unstructured gridHydrostatic equilibriumShallow water equationsPhysics::Atmospheric and Oceanic Physics0105 earth and related environmental sciencesWater Science and TechnologyMathematicsAdvances in Water Resources
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Monotonic solution of flow and transport problems in heterogeneous media using Delaunay unstructured triangular meshes

2013

Transport problems occurring in porous media and including convection, diffusion and chemical reactions, can be well represented by systems of Partial Differential Equations. In this paper, a numerical procedure is proposed for the fast and robust solution of flow and transport problems in 2D heterogeneous saturated media. The governing equations are spatially discretized with unstructured triangular meshes that must satisfy the Delaunay condition. The solution of the flow problem is split from the solution of the transport problem and it is obtained with an approach similar to the Mixed Hybrid Finite Elements method, that always guarantees the M-property of the resulting linear system. The…

Mathematical optimizationFinite volume methodDiscretizationTransport problem porous media anisotropic diffusion tensor heterogeneous medium M-matrix Delaunay mesh edge swap numerical methods finite elementsDelaunay triangulationAnisotropic diffusionLinear systemMonotonic functionFinite element methodSettore ICAR/01 - IdraulicaApplied mathematicsPolygon meshWater Science and TechnologyMathematics
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Biased Modern Heuristics for the OCST Problem

2011

Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.

Mathematical optimizationFitness functionOperator (computer programming)Computer scienceSimulated annealingGenetic algorithmDesign elements and principlesRepresentation (mathematics)HeuristicsSpan tree
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Genetic algorithms for 3d reconstruction with supershapes

2009

Supershape model is a recent primitive that represents numerous 3D shapes with several symmetry axes. The main interest of this model is its capability to reconstruct more complex shape than superquadric model with only one implicit equation. In this paper we propose a genetic algorithms to re-construct a point cloud using those primitives. We used the pseudo-Euclidean distance to introduce a threshold to handle real data imperfection and speed up the process. Simulations using our proposed fitness functions and a fitness function based on inside-outside function show that our fitness function based on the pseudo-Euclidean distance performs better.

Mathematical optimizationFitness functionSpeedupImplicit functionFitness approximation3D reconstructionPoint cloudFunction (mathematics)Iterative reconstructionAlgorithmMathematics2009 16th IEEE International Conference on Image Processing (ICIP)
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