A control problem for a linear stochastic system with an arbitrary fractional Brownian motion and a cost functional that is quadratic in the system state and the control is solved. An optimal control is given explicitly as the sum of a prediction of the future fractional Brownian motion and the well known linear feedback control for the associated deterministic linear-quadratic control problem....

This paper describes a volume rendering system for unstructured data, especially nite element data, that creates images with very high accuracy. The system will currently handle meshes whose cells are either linear or quadratic tetrahedra. Compromises or approximations are not introduced for the sake of eeciency. Whenever possible, exact mathematical solutions for the radiance integrals involve...

In this work we present an algorithm for the solution of multiparametric linear and quadratic programming problems.With linear constraints and linear or convex quadratic objective functions, the optimal solution of these optimization problems is given by a conditional piecewise linear function of the varying parameters. This function results from first-order estimations of the analytical nonlin...

In this paper we describe a possible way to make reinforcement learning more applicable in the context of industrial manufacturing processes. We achieve this by formulating the optimization task in the linear quadratic regulation framework, for which a conventional control theoretic solution exist. By rewriting the Q-learning approach into a linear least squares approximation problem, we can ma...

A new quasi-Newton scheme for updating a low rank positive semi-definite Hessian approximation is described, primarily for use in sequential quadratic programming methods for nonlinear programming. Where possible the symmetric rank one update formula is used, but when this is not possible a new rank two update is used, which is not in the Broyden family, although invariance under linear transfo...

We adapt a method of Schur to determine the sign in the quadratic Gauss sum and derive from this, the law of quadratic reciprocity.

Self-triggered control is a recently proposed paradigm that abandons the more traditional periodic timetriggered execution of control tasks with the objective of reducing the utilization of communication resources, while still guaranteeing desirable closed-loop behavior. In this paper, we introduce a selftriggered strategy based on performance levels described by a quadratic discounted cost. Th...

The use of linear quadratic theory in bumpless transfer is discussed and a modification to a similar scheme proposed in [9] is suggested. Formulae are given for a feedback element which minimises a cost function deemed appropriate for ensuring bumpless transfer. The formulae are algebraic and depend only on given matrices and the solution to a single Riccati equation. The differences between th...

The use of piecewise quadratic cost functions is extended from stability analysis of piecewise linear systems to performance analysis and optimal control. Lower bounds on the optimal control cost are obtained by semi-definite programming based on the Bellman inequality. This also gives an approximation to the optimal control law. An upper bound to the optimal cost is obtained by another convex ...

This paper studies linear quadratic games with set up costs monotonic on the number of active players, namely, players whose action is non-zero. Such games arise naturally in joint replenishment inventory systems. Building upon a preliminary analysis of the properties of the best response strategies and Nash equilibria for the given game, the main contribution is the study of the same game unde...