The paper deals with the control of variablespeed wind energy conversion systems (WECS) in the context of linear parameter varying (LPV) systems, a recent formulation of the classic gain scheduling technique. The LPV approach is specially useful in…
Papers in Control and Optimization
Control and Optimization papers in Mathematics, G
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in Control and Optimization, G


A new approach to gain scheduling linear dynamic controllers is illustrated for a pitchaxis autopilot design problem. In this application the linear controllers are designed at distinct operating conditions by H∞ methods. The gain scheduling…

Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computationreliant results truly are. Galaxy http://usegalaxy.org, an open webbased platform for genomic…

Fixed point calculus is about the solution of recursive equations defined by a monotonic endofunction on a partially ordered set. This tutorial presents the basic theory of fixed point calculus together with a number of applications of direct…

For three different bankruptcy problems, the 2000year old Babylonian Talmud prescribes solutions that equal precisely the nucleoli of the corresponding coalitional games. A rationale for these solutions that is independent of game theory is given…

This paper introduces a model of 'theory of mind', namely, how we represent the intentions and goals of others to optimise our mutual interactions. We draw on ideas from optimum control and game theory to provide a 'game theory of mind'. First, we…

We consider the problem of Internet switching, where traffic is generated by selfish users. We study a packetized (TCPlike) traffic model, which is more accurate than the widely used fluid model. We assume that routers have FirstInFirstOut…

We comprehensively study the leastsquares Gaussian approximations of the diffractionlimited 2D3D paraxialnonparaxial pointspread functions (PSFs) of the wide field fluorescence microscope (WFFM), the laser scanning confocal microscope (LSCM),…

By considering the function variables rather than the binarybits as genes, new mutation operators can be devised for GAs used to optimise numeric functions. We implement Gaussian mutation operators for genetic algorithms used to optimise numeric…

Sequential Bayesian estimation for dynamic state space models involves recursive estimation of hidden states based on noisy observations. The update of filtering and predictive densities for nonlinear models with nonGaussian noise using Monte Carlo…

In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different candidate structures. In the Bayesian framework, this is done by…

We introduce a novel Bayesian approach to global optimiza tion using Gaussian processes. We frame the optimization of both noisy and noiseless functions as sequential decision problems, and introduce myopic and nonmyopic solutions to them. Here…

Hybrid Monte Carlo (HMC) is often the method of choice for computing\nBayesian integrals that are not analytically tractable. However the\nsuccess of this method may require a very large number of evaluations\nof the (unnormalized) posterior and…

We use the Gaussian particle filter to build several types of Gaussian sum particle filters. These filters approximate the filtering and predictive distributions by weighted Gaussian mixtures and are basically banks of Gaussian particle filters.…

One major objective for plant biology is the discovery of molecular subsystems underlying complex traits. The use of genetic and genomic resources combined in a systems genetics approach offers a means for approaching this goal. This study describes…

The elegant mechanisms by which naturally occurring selfish genetic elements, such as transposable elements, meiotic drive genes, homing endonuclease genes and Wolbachia, spread at the expense of their hosts provide some of the most fascinating and…

Population replacement strategies for controlling transmission of mosquitoborne diseases call for the introgression of antipathogen effector genes into vector populations. It is anticipated that these genes, if present at high enough frequencies,…

Sequence changes in coding region and regulatory region of the gene itself (cis) determine most of gene expression divergence between closely related species. But gene expression divergence between yeast species is not correlated with evolution of…

The mechanisms by which trisomy 21 leads to the characteristic Down syndrome (DS) phenotype are unclear. We used whole genome microarrays to characterize for the first time the transcriptome of human adult brain tissue (dorsolateral prefrontal…

We are beginning to elucidate transcriptional regulatory networks on a large scale and to understand some of the structural principles of these networks, but the evolutionary mechanisms that form these networks are still mostly unknown. Here we…
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