Gaussian process approximations of stochastic differential equations

Stochastic differential equations arise naturally in a range of contexts, from financial to environmental modeling. Current solution methods are limited in their representation of the posterior process in the presence of data. In this work, we present a novel Gaussian process approximation to the posterior measure over paths for a general class of stochastic differential equations in the presence of observations. The method is applied to two simple problems: the Ornstein-Uhlenbeck process, of which the exact solution is known and can be compared to, and the double-well system, for which standard approaches such as the ensemble Kalman smoother fail to provide a satisfactory result. Experiments show that our variational approximation is viable and that the results are very promising as the variational approximate solution outperforms standard Gaussian process regression for non-Gaussian Markov processes.

The dynamics and control of a remotely piloted plan-symmetric helicopter

Prior to the development of a production standard control system for ML Aviation's plan-symmetric remotely piloted helicopter system, SPRITE, optimum solutions to technical requirements had yet to be found for some aspects of the work. This thesis describes an industrial project where solutions to real problems have been provided within strict timescale constraints. Use has been made of published material wherever appropriate, new solutions have been contributed where none existed previously. A lack of clearly defined user requirements from potential Remotely Piloted Air Vehicle (RPAV) system users is identified, A simulation package is defined to enable the RPAV designer to progress with air vehicle and control system design, development and evaluation studies and to assist the user to investigate his applications. The theoretical basis of this simulation package is developed including Co-axial Contra-rotating Twin Rotor (CCTR), six degrees of freedom motion, fuselage aerodynamics and sensor and control system models. A compatible system of equations is derived for modelling a miniature plan-symmetric helicopter. Rigorous searches revealed a lack of CCTR models, based on closed form expressions to obviate integration along the rotor blade, for stabilisation and navigation studies through simulation. An economic CCTR simulation model is developed and validated by comparison with published work and practical tests. Confusion in published work between attitude and Euler angles is clarified. The implementation of package is discussed. dynamic adjustment of assessment. the theory into a high integrity software Use is made of a novel technique basing the integration time step size on error Simulation output for control system stability verification, cross coupling of motion between control channels and air vehicle response to demands and horizontal wind gusts studies are presented. Contra-Rotating Twin Rotor Flight Control System Remotely Piloted Plan-Symmetric Helicopter Simulation Six Degrees of Freedom Motion ( i i)

Fast reconstruction of harmonic functions from Cauchy data using the Dirichlet-to-Neumann map and integral equations

We propose and investigate a method for the stable determination of a harmonic function from knowledge of its value and its normal derivative on a part of the boundary of the (bounded) solution domain (Cauchy problem). We reformulate the Cauchy problem as an operator equation on the boundary using the Dirichlet-to-Neumann map. To discretize the obtained operator, we modify and employ a method denoted as Classic II given in [J. Helsing, Faster convergence and higher accuracy for the Dirichlet–Neumann map, J. Comput. Phys. 228 (2009), pp. 2578–2576, Section 3], which is based on Fredholm integral equations and Nyström discretization schemes. Then, for stability reasons, to solve the discretized integral equation we use the method of smoothing projection introduced in [J. Helsing and B.T. Johansson, Fast reconstruction of harmonic functions from Cauchy data using integral equation techniques, Inverse Probl. Sci. Eng. 18 (2010), pp. 381–399, Section 7], which makes it possible to solve the discretized operator equation in a stable way with minor computational cost and high accuracy. With this approach, for sufficiently smooth Cauchy data, the normal derivative can also be accurately computed on the part of the boundary where no data is initially given.

A variational method and approximations of a Cauchy problem for elliptic equations

A Cauchy problem for general elliptic second-order linear partial differential equations in which the Dirichlet data in H½(?1 ? ?3) is assumed available on a larger part of the boundary ? of the bounded domain O than the boundary portion ?1 on which the Neumann data is prescribed, is investigated using a conjugate gradient method. We obtain an approximation to the solution of the Cauchy problem by minimizing a certain discrete functional and interpolating using the finite diference or boundary element method. The minimization involves solving equations obtained by discretising mixed boundary value problems for the same operator and its adjoint. It is proved that the solution of the discretised optimization problem converges to the continuous one, as the mesh size tends to zero. Numerical results are presented and discussed.

Boundary integral equations for acoustical inverse sound-soft scattering

The shape of a plane acoustical sound-soft obstacle is detected from knowledge of the far field pattern for one time-harmonic incident field. Two methods based on solving a system of integral equations for the incoming wave and the far field pattern are investigated. Properties of the integral operators required in order to apply regularization, i.e. injectivity and denseness of the range, are proved.

Some aspects of the solution of non-linear differential equations

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