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A null controllability data assimilation methodology applied to a large scale ocean circulation model

Galina C. García, Axel Osses, Jean Pierre Puel (2011)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

Data assimilation refers to any methodology that uses partial observational data and the dynamics of a system for estimating the model state or its parameters. We consider here a non classical approach to data assimilation based in null controllability introduced in [Puel, C. R. Math. Acad. Sci. Paris 335 (2002) 161–166] and [Puel, SIAM J. Control Optim. 48 (2009) 1089–1111] and we apply it to oceanography. More precisely, we are interested in developing this methodology to recover the unknown final...

A null controllability data assimilation methodology applied to a large scale ocean circulation model*

Galina C. García, Axel Osses, Jean Pierre Puel (2011)

ESAIM: Mathematical Modelling and Numerical Analysis

Data assimilation refers to any methodology that uses partial observational data and the dynamics of a system for estimating the model state or its parameters. We consider here a non classical approach to data assimilation based in null controllability introduced in [Puel, C. R. Math. Acad. Sci. Paris335 (2002) 161–166] and [Puel, SIAM J. Control Optim.48 (2009) 1089–1111] and we apply it to oceanography. More precisely, we are interested in developing this methodology to recover the unknown final...

A numerical method for the solution of the nonlinear observer problem

Rehák, Branislav (2021)

Programs and Algorithms of Numerical Mathematics

The central part in the process of solving the observer problem for nonlinear systems is to find a solution of a partial differential equation of first order. The original method proposed to solve this equation used expansions into Taylor polynomials, however, it suffers from rather restrictive assumptions while the approach proposed here allows to generalize these requirements. Its characteristic feature is that it is based on the application of the Finite Element Method. An illustrating example...

A numerical procedure for filtering and efficient high-order signal differentiation

Salim Ibrir, Sette Diop (2004)

International Journal of Applied Mathematics and Computer Science

In this paper, we propose a numerical algorithm for filtering and robust signal differentiation. The numerical procedure is based on the solution of a simplified linear optimization problem. A compromise between smoothing and fidelity with respect to the measurable data is achieved by the computation of an optimal regularization parameter that minimizes the Generalized Cross Validation criterion (GCV). Simulation results are given to highlight the effectiveness of the proposed procedure.

A parallel projection method for linear algebraic systems

Fridrich Sloboda (1978)

Aplikace matematiky

A direct projection method for solving systems of linear algebraic equations is described. The algorithm is equivalent to the algorithm for minimization of the corresponding quadratic function and can be generalized for the minimization of a strictly convex function.

A pension fund in the accumulation phase: a stochastic control approach

Salvatore Federico (2008)

Banach Center Publications

In this paper we propose and study a continuous time stochastic model of optimal allocation for a defined contribution pension fund in the accumulation phase. The level of wealth is constrained to stay above a "solvency level". The fund manager can invest in a riskless asset and in a risky asset, but borrowing and short selling are prohibited. The model is naturally formulated as an optimal stochastic control problem with state constraints and is treated by the dynamic programming approach. We show...

A perturbation approach to approximate value iteration for average cost Markov decision processes with Borel spaces and bounded costs

Óscar Vega-Amaya, Joaquín López-Borbón (2019)

Kybernetika

The present paper studies the approximate value iteration (AVI) algorithm for the average cost criterion with bounded costs and Borel spaces. It is shown the convergence of the algorithm and provided a performance bound assuming that the model satisfies a standard continuity-compactness assumption and a uniform ergodicity condition. This is done for the class of approximation procedures that can be represented by linear positive operators which give exact representation of constant functions and...

A Posteriori Error Estimation for Reduced Order Solutions of Parametrized Parabolic Optimal Control Problems

Mark Kärcher, Martin A. Grepl (2014)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

We consider the efficient and reliable solution of linear-quadratic optimal control problems governed by parametrized parabolic partial differential equations. To this end, we employ the reduced basis method as a low-dimensional surrogate model to solve the optimal control problem and develop a posteriori error estimation procedures that provide rigorous bounds for the error in the optimal control and the associated cost functional. We show that our approach can be applied to problems involving...

A practical solution to implement nonlinear output regulation via dynamic mappings

Carlos Armenta, Jorge Álvarez, Raymundo Márquez, Miguel Bernal (2019)

Kybernetika

This paper presents a novel error-feedback practical solution for real-time implementation of nonlinear output regulation. Sufficient and necessary conditions for both state- and error-feedback output regulation have been established for linear and nonlinear systems several decades ago. In their most general form, these solutions require solving a set of nonlinear partial differential equations, which may be hard or even impossible to solve analytically. In recent years, a methodology for dynamic...

A probabilistic method for certification of analytically redundant systems

Bin Hu, Peter Seiler (2015)

International Journal of Applied Mathematics and Computer Science

Analytical fault detection algorithms have the potential to reduce the size, power and weight of safety-critical aerospace systems. Analytical redundancy has been successfully applied in many non-safety critical applications. However, acceptance for aerospace applications will require new methods to rigorously certify the impact of such algorithms on the overall system reliability. This paper presents a theoretical method to assess the probabilistic performance for an analytically redundant system....

A problem of robust control of a system with time delay

Marina Blizorukova, Franz Kappel, Vyacheslav Maksimov (2001)

International Journal of Applied Mathematics and Computer Science

A problem of guaranteed control is under discussion. This problem consists in the attainment of a given target set by a phase trajectory of a system described by an equation with time delay. An uncontrolled disturbance (along with a control) is assumed to act upon the system. An algorithm for solving the problem in the case when information on a phase trajectory is incomplete (measurements of a 'part' of coordinates) is designed. The algorithm is stable with respect to informational noises and computational...

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