Search results for "Stochastic process"

showing 10 items of 346 documents

A Fokker–Planck control framework for multidimensional stochastic processes

2013

AbstractAn efficient framework for the optimal control of probability density functions (PDFs) of multidimensional stochastic processes is presented. This framework is based on the Fokker–Planck equation that governs the time evolution of the PDF of stochastic processes and on tracking objectives of terminal configuration of the desired PDF. The corresponding optimization problems are formulated as a sequence of open-loop optimality systems in a receding-horizon control strategy. Many theoretical results concerning the forward and the optimal control problem are provided. In particular, it is shown that under appropriate assumptions the open-loop bilinear control function is unique. The res…

Stochastic controlMathematical optimizationContinuous-time stochastic processOptimization problemoptimal control stochastic processesStochastic processApplied MathematicsOptimal controlComputational MathematicsModel predictive controlMultidimensional stochastic processOptimal control theoryLimit cycleProbability density functionFokker–Planck equationFokker–Planck equationModel predictive controlMathematicsJournal of Computational and Applied Mathematics
researchProduct

Solving fully randomized first-order linear control systems: Application to study the dynamics of a damped oscillator with parametric noise under sto…

2022

[EN] This paper is devoted to study random linear control systems where the initial condition, the final target, and the elements of matrices defining the coefficients are random variables, while the control is a stochastic process. The so-called Random Variable Transformation technique is adapted to obtain closed-form expressions of the probability density functions of the solution and of the control. The theoretical findings are applied to study the dynamics of a damped oscillator subject to parametric noise.

Stochastic controlStochastic processApplied MathematicsRandom damped linear oscillatorsProbability density functionNoise (electronics)Computational MathematicsTransformation (function)Random control systemsInitial value problemApplied mathematicsFirst probability density functionMATEMATICA APLICADARandom variableRandom Variable Transformation techniqueMathematicsParametric statistics
researchProduct

Stochastic Control Problems

2003

The general theory of stochastic processes originated in the fundamental works of A. N. Kolmogorov and A. Ya. Khincin at the beginning of the 1930s. Kolmogorov, 1938 gave a systematic and rigorous construction of the theory of stochastic processes without aftereffects or, as it is customary to say nowadays, Markov processes. In a number of works, Khincin created the principles of the theory of so-called stationary processes.

Stochastic controlsymbols.namesakeMarkov chainWiener processComputer scienceStochastic processsymbolsStochastic matrixApplied mathematicsMarkov processStochastic optimizationStochastic programming
researchProduct

Stochastic Differential Calculus

1993

In many cases of engineering interest it has become quite common to use stochastic processes to model loadings resulting from earthquake, turbulent winds or ocean waves. In these circumstances the structural response needs to be adequately described in a probabilistic sense, by evaluating the cumulants or the moments of any order of the response (see e.g. [1, 2]). In particular, for linear systems excited by normal input, the response process is normal too and the moments or the cumulants up to the second order fully characterize the probability density function of both input and output processes. Many practical problems involve processes which are approximately normal and the effect of the…

Stochastic differential equationQuantum stochastic calculusStochastic processComputer scienceLinear systemStochastic calculusTime-scale calculusStatistical physicsMalliavin calculusCumulant
researchProduct

On Malliavin calculus and approximation of stochastic integrals for Lévy processes

2012

Stochastic integralsApproximation theoryMalliavian calculusStochastic analysisapproksimointiLévy processStochastic processstokastiset prosessit
researchProduct

Stochastic integro-differential and differential equations of non-linear systems excited by parametric Poisson pulses

1997

Abstract The connection between stochastic integro-differential equation and stochastic differential equation of non-linear systems driven by parametric Poisson delta correlated processes is presented. It is shown that the two different formulations are fully equivalent in the case of external excitation. In the case of parametric type excitation the two formulation are equivalent if the non-linear argument in the integral representation is related by means of a series to the corresponding non-linear parametric term in the stochastic differential equation. Differential rules for the two representations to find moment equations of every order of the response are also compared.

Stochastic partial differential equationNonlinear systemStochastic differential equationMechanics of MaterialsStochastic processDifferential equationApplied MathematicsMechanical EngineeringNumerical analysisMathematical analysisFirst-order partial differential equationParametric statisticsMathematics
researchProduct

Exact stationary solution for a class of non-linear systems driven by a non-normal delta-correlated process

1995

In this paper the exact stationary solution in terms of probability density function for a restricted class of non-linear systems under both external and parametric non-normal delta-correlated processes is presented. This class has been obtained by imposing a given probability distribution and finding the corresponding dynamical system which satisfies the modified Fokker-Planck equation. The effectiveness of the results has been verified by means of a Monte Carlo simulation.

Stochastic processApplied MathematicsMechanical EngineeringMonte Carlo methodProbability density functionStationary sequenceDynamical systemMechanics of MaterialsApplied mathematicsProbability distributionFokker–Planck equationStatistical physicsMathematicsParametric statisticsInternational Journal of Non-Linear Mechanics
researchProduct

Itô formula for an integro-differential operator without an associated stochastic process

2010

Stochastic processApplied mathematicsItō's lemmaDifferential operatorMathematicsProgress in Analysis and Its Applications
researchProduct

Bounded Drift-Diffusion Motion

2009

Stochastic processBounded functionMathematical analysisMotion (geometry)Sturm–Liouville theoryDiffusion (business)Liouville field theoryMathematics
researchProduct

Stochastic response of combined primary-secondary structures under seismic input

1992

A technique for non-stationary stochastic analysis of linear combined primary and secondary subsystems subjected to a zero-mean Gaussian base excitation is presented. The proposed technique, based on the use of the Taylor's expansion in evaluating the operators which appear in the step-by-step procedure, does not require the evaluation of the complex eigenproperties of the combined system. Operating in this way, even though the numerical procedure is a conditionally stable one, appears to be more efficient than existing methods to evaluate the dynamic response of such composite systems. It is also shown that the proposed procedure is available whether the seismic input is idealized as a fil…

Stochastic processDifferential equationGaussianAutocorrelationWhite noiseGeotechnical Engineering and Engineering GeologyBase (topology)symbols.namesakeEarth and Planetary Sciences (miscellaneous)Taylor seriessymbolsCalculusAlgorithmMathematics
researchProduct