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By Sylvain Ervedoza

​​​​​​This ebook is dedicated to completely constructing and evaluating the 2 major ways to the numerical approximation of controls for wave propagation phenomena: the continual and the discrete. this can be entire within the summary useful surroundings of conservative semigroups.The major result of the paintings unify, to a wide quantity, those methods, which yield similaralgorithms and convergence premiums. The discrete strategy, notwithstanding, supplies not just effective numerical approximations of the continual controls, but in addition guarantees a few partial controllability houses of the finite-dimensional approximated dynamics. additionally, it has the good thing about resulting in iterative approximation methods that converge and not using a proscribing threshold within the variety of iterations. this kind of threshold, that is demanding to compute and estimate in perform, is an obstacle of the tools emanating from the continual strategy. to counterpoint this concept, the booklet presents convergence effects for the discrete wave equation while discretized utilizing finite ameliorations and proves the convergence of the discrete wave equation with non-homogeneous Dirichlet stipulations. the 1st booklet to discover those themes intensive, "On the Numerical Approximations of Controls for Waves" has wealthy purposes to info assimilation difficulties and may be of curiosity to researchers who care for wave approximations.​

Table of Contents


Numerical Approximation of actual Controls for Waves

ISBN 9781461458074 ISBN 9781461458081





Numerical Approximation of actual Controls for Waves

1.1 Introduction
1.1.1 An summary sensible Setting
1.1.2 Contents of Chap. 1
1.2 major effects 1.2.1 An "Algorithm" in an Infinite-Dimensional Setting
1.2.2 the continual Approach
1.2.3 The Discrete Approach
1.2.4 define of Chap. 1
1.3 evidence of the most outcome at the non-stop Setting
1.3.1 Classical Convergence Results
1.3.2 Convergence charges in Xs
1.4 the continual Approach
1.4.1 facts of Theorem 1.2
1.4.2 evidence of Theorem 1.3
1.5 greater Convergence charges: The Discrete Approach
1.5.1 evidence of Theorem 1.4
1.5.2 facts of Theorem 1.5
1.6 benefits of the Discrete Approach
1.6.1 The variety of Iterations
1.6.2 Controlling Non-smooth Data
1.6.3 different Minimization Algorithms
1.7 program to the Wave Equation
1.7.1 Boundary Control
1.7.2 disbursed Control
1.8 a knowledge Assimilation Problem
1.8.1 The Setting
1.8.2 Numerical Approximation Methods

Observability for the 1d Finite-Difference Wave Equation

2.1 Objectives
2.2 Spectral Decomposition of the Discrete Laplacian
2.3 Uniform Admissibility of Discrete Waves
2.3.1 The Multiplier Identity
2.3.2 evidence of the Uniform Hidden Regularity Result
2.4 An Observability Result
2.4.1 Equipartition of the Energy
2.4.2 The Multiplier id Revisited
2.4.3 Uniform Observability for Filtered Solutions
2.4.4 evidence of Theorem 2.3

Convergence of the Finite-Difference technique for the 1-d Wave Equation with Homogeneous Dirichlet Boundary Conditions

3.1 Objectives
3.2 Extension Operators
3.2.1 The Fourier Extension
3.2.2 different Extension Operators
3.3 Orders of Convergence for tender preliminary Data
3.4 extra Convergence effects 3.4.1 Strongly Convergent preliminary Data
3.4.2 delicate preliminary Data
3.4.3 common preliminary Data
3.4.4 Convergence premiums in Weaker Norms
3.5 Numerics

Convergence with Nonhomogeneous Boundary Conditions

4.1 The Setting
4.2 The Laplace Operator
4.2.1 normal useful Spaces
4.2.2 better Norms
4.2.3 Numerical Results
4.3 Uniform Bounds on yh
4.3.1 Estimates in C([0,T]; LLL222(((000,,,111))))))
4.3.2 Estimates on ...tyh
4.4 Convergence charges for gentle information 4.4.1 major Convergence Result
4.4.2 Convergence of yyyhhh
4.4.3 Convergence of ...tttyyyhhh
4.4.4 extra general Data
4.5 extra Convergence Results
4.6 Numerical Results

Further reviews and Open Problems

5.1 Discrete as opposed to non-stop Approaches
5.2 comparability with Russell's Approach
5.3 Uniform Discrete Observability Estimates
5.4 optimum keep an eye on Theory
5.5 absolutely Discrete Approximations


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Extra resources for Numerical Approximation of Exact Controls for Waves

Sample text

In Sect. 8 we show that some data assimilation problems can be treated by the methods developed in this book. 1. 8) hold. Given y0 ∈ Xs , Φ0 ∈ X is chosen to be the unique solution of Eq. 14). 18). 1 Classical Convergence Results First we prove Eq. 23) which is classical and corresponds to the usual proof of convergence of the steepest descent algorithm for quadratic convex functionals. We provide it only for completeness and later use. 23)). Using Eq. 18), and subtracting to it Φ0 , we get ϕ0k+1 − Φ0 = ϕ0k − Φ0 − ρ (ΛT ϕ0k + y0) = ϕ0k − Φ0 − ρΛT (ϕ0k − Φ0 ), where the last identity follows from the definition of Φ0 in Eq.

These remarks are of course related to the fact that in these two cases, the needed integrations by parts run smoothly, similarly as in [15]. 4 The Continuous Approach In this section, we suppose that Assumptions 1 and 2 hold. 2). 2. All the constants that will appear in the proof below, denoted by a generic C that may change from line to line, are independent of h > 0 and k ∈ N. Subtracting Eq. 18) to Eq. 32), we obtain k+1 k k ϕ0h −Rh ϕ0k+1 = ϕ0h −Rh ϕ0k −ρ (y0h −Rh y0 )−ρ ΛT h ϕ0h −RhΛT ϕ0k k = (I−ρΛT h ) ϕ0h −Rh ϕ0k −ρ (y0h −Rh y0 ) + ρ (RhΛT − ΛT h Rh ) ϕ0k .

2), γ we can introduce the orthogonal projection Ph of Vh onto Vh (γ /h) (with respect to the scalar product of Vh introduced in Eq. 84)) and the Gramian operator ΛTγ h = Phγ ΛT h Phγ . 89) The filtering operator Ph simply consists of doing a discrete Fourier transform and then removing the coefficients corresponding to frequency numbers k larger than γ /h. Assumptions 1 and 2 then hold for any γ ∈ (0, 1), with proofs similar to those in the continuous approach. Furthermore, using the results of [28], it can be shown that Assumption 3 also holds when the time T is greater than Tγ := 2/ cos(πγ /2).

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