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MATHICSE Technical Report : A Multilevel Stochastic Gradient method for PDE-constrained Optimal Control Problems with uncertain parameters

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Robust Ultrasound Travel-time Tomography Using the Bent Ray Model

Martin Vetterli, Olivier Roy, Ali Hormati, Ivana Jovanovic

We present a bent ray reconstruction algorithm for an ultrasound tomography (UT) scanner designed for breast screening. The scanner consists of a circular array of transmitters and receivers which encloses the object to be imaged. By solving a nonlinear sy ...

Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2010

A Simple Learning Strategy for High-Speed Quadrocopter Multi-Flips

Raffaello D'Andrea

We describe a simple and intuitive policy gradient method for improving parametrized quadrocopter multi-flips by combining iterative experiments with information from a first-principles model. We start by formulating an N-flip maneuver as a five-step primi ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous Time

Daniel Kuhn

Dynamic stochastic optimization problems with a large (possibly infinite) number of decision stages and high-dimensional state vectors are inherently difficult to solve. In fact, scenario tree-based algorithms are unsuitable for problems with many stages, ...

2009

Incremental Global Parameter Estimation in Dynamical Systems

Benoît Chachuat

Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model's quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is e ...

American Chemical Society2009

A sparse grid stochastic collocation method for partial differential equations with random input data

Fabio Nobile

This work proposes and analyzes a Smolyak-type sparse grid stochastic collocation method for the approximation of statistical quantities related to the solution of partial differential equations with random coeffcients and forcing terms ( input data of the ...

Society for Industrial and Applied Mathematics2008

Iterative minimization of H2 control performance criteria

Ljubisa Miskovic

Data-based control design methods most often consist of iterative adjustment of the controller&psila;s parameters towards the parameter values which minimize an H2 performance criterion. Typically, batches of input-output data collected from the system are ...

2008

Generalized Bounds for Convex Multistage Stochastic Programs

Daniel Kuhn

This book investigates convex multistage stochastic programs whose objective and constraint functions exhibit a generalized nonconvex dependence on the random parameters. Although the classical Jensen and Edmundson-Madansky type bounds or their extensions ...

Springer-Verlag2005

A new method for solving broadband matching problems

Catherine Dehollain, Jacques Neirynck

A new method for computing the component values of LC ladder equalizers for broadband matching purposes is presented. The method is inspired by the theory of recursive identification and results in a very compact algorithm. As in the usual real frequency t ...

1994

Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters

Fabio Nobile, Sebastian Krumscheid, Matthieu Claude Martin

We consider the numerical approximation of a risk-averse optimal control problem for an elliptic partial differential equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes th ...

...available as Mathicse-Report nr 04.20180