Comparison of different scheduling techniques for H-infinity controllers

Several approaches to designing schedule H-infinity control systems are compared. These include a controller switching approach and also parameter scheduling of an observer representation of the controller. They are illustrated by application to a Generic VSTOI. Aircraft Model (GVAM) supplied by The Royal Aerospace Establishment (RAE) at Bedford. The switched design has been tested on the simulator at RAE Bedford. The linear H-infinity designs make use of a loop-shaping followed by robust stabilisation to additive perturbations of a normalised coprime factorisation of the shaped plans. The different scheduling approaches are compared with respect to achieved robust stability levels. performance and complexity of implementation.

Multiple object tracking using evolutionary MCMC-based particle algorithms

Algorithms are presented for detection and tracking of multiple clusters of co-ordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a population of different chain realizations, and 2) exchanging genetic material between samples in this population. The performance of the resulting evolutionary filtering algorithms is demonstrated in two different settings. In the first, both group and target properties are estimated whereas in the second, which consists of a very large number of targets, only the clustering structure is maintained. © 2009 IFAC.

Performance optimization of adaptive loading algorithms for SMF-based optical OFDM transceivers

Detailed investigations of the effectiveness of three widely adopted optical orthogonal frequency division multiplexing (OOFDM) adaptive loading algorithms, including power loading (PL), bit loading (BL), and bit-and-power loading (BPL), are undertaken, over < 100km single-mode fibre (SMF) system without incorporating inline optical amplification and chromatic dispersion (CD) compensation. It is shown that the BPL (PL) algorithm always offers the best (worst) transmission performance. The absolute transmission capacity differences between these algorithms are independent of transmission distance and launched optical power. Moreover, it is shown that in comparison with the most sophisticated BPL algorithm, the simplest PL algorithm is effective in escalating the OOFDM SMF links performance to its maximum potential. On the other hand, when employing a large number of subcarriers and a high digital-to-analogue DAC)/analogue-to-digital (ADC) sampling rate, the sophisticated BPL algorithm has to be adopted. © 2011 IEEE.

Solving problems in production scheduling

Traditionally, production scheduling has been viewed as a problem-solving task that involves a single problem - generation of a suitable schedule. This paper presents an alternative model in which individual difficulties are viewed as problems, and the task is to maintain a suitable schedule by resolving as many of these problems as possible. Decision support software is described that has facilities for defining policies to handle numerous minor problems and complete problem-solving strategies to deal with major problems. The paper then discusses the potential for this style of decision support to improve the performance of human schedulers. © 1995.

Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit

This paper describes a derivation of the adjoint low Mach number equations and their implementation and validation within a global mode solver. The advantage of using the low Mach number equations and their adjoints is that they are appropriate for flows with variable density, such as flames, but do not require resolution of acoustic waves. Two versions of the adjoint are implemented and assessed: a discrete-adjoint and a continuous-adjoint. The most unstable global mode calculated with the discrete-adjoint has exactly the same eigenvalue as the corresponding direct global mode but contains numerical artifacts near the inlet. The most unstable global mode calculated with the continuous-adjoint has no numerical artifacts but a slightly different eigenvalue. The eigenvalues converge, however, as the timestep reduces. Apart from the numerical artifacts, the mode shapes are very similar, which supports the expectation that they are otherwise equivalent. The continuous-adjoint requires less resolution and usually converges more quickly than the discrete-adjoint but is more challenging to implement. Finally, the direct and adjoint global modes are combined in order to calculate the wavemaker region of a low density jet. © 2011 Elsevier Inc.

Closing the gap: Improved bounds on optimal POMDP solutions

POMDP algorithms have made significant progress in recent years by allowing practitioners to find good solutions to increasingly large problems. Most approaches (including point-based and policy iteration techniques) operate by refining a lower bound of the optimal value function. Several approaches (e.g., HSVI2, SARSOP, grid-based approaches and online forward search) also refine an upper bound. However, approximating the optimal value function by an upper bound is computationally expensive and therefore tightness is often sacrificed to improve efficiency (e.g., sawtooth approximation). In this paper, we describe a new approach to efficiently compute tighter bounds by i) conducting a prioritized breadth first search over the reachable beliefs, ii) propagating upper bound improvements with an augmented POMDP and iii) using exact linear programming (instead of the sawtooth approximation) for upper bound interpolation. As a result, we can represent the bounds more compactly and significantly reduce the gap between upper and lower bounds on several benchmark problems. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

Information theory, inference, and learning algorithms

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.