Fault tolerant control using Gaussian processes and model predictive control

Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control. © 2013 IEEE.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network

A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms.

20 Gb/s mode-group-division multiplexing employing Hermite-Gaussian launches over worst-case multimode fiber links

For the first time, mode group division multiplexing is achieved in a multimode fiber link using a 2-D Hermite-Gaussian mode launch. 20 Gb/s error-free transmission is achieved over a 250 m worst-case OM1 multimode fiber link. © OSA 2014.

Food web of macroinvertebrate community in a Yangtze shallow lake: trophic basis and pathways

No detailed food web research on macroinvertebrate community of lacustrine ecosystem was reported in China. The present study is the first attempt on the subject in Lake Biandantang, a macrophytic lake in Hubei Province. Food webs of the macroinvertebrate community were compiled bimonthly from March, 2002 to March, 2003. Dietary information was obtained from gut analysis. Linkage strength was quantified by combining estimates of energy flow (secondary production) with data of gut analysis. The macroinvertebrate community of Lake Biandantang was based heavily on detritus. Quantitative food webs showed the total ingestion ranged from 6930 to 36,340 mg dry mass m(-2) bimonthly. The ingestion of macroinvertebrate community was higher in the months with optimum temperature than that in other periods with higher or lower temperature. Through comparison, many patterns in benthic food web of Lake Biandantang are consistent with other detritus-based webs, such as stream webs, but different greatly from those based on autochthonous primary production (e.g. pelagic systems). It suggests that the trophic basis of the web is essential in shaping food web structure.

Modelling of settlement induced building damage

This thesis focuses on the modelling of settlement induced damage to masonry buildings. In densely populated areas, the need for new space is nowadays producing a rapid increment of underground excavations. Due to the construction of new metro lines, tunnelling activity in urban areas is growing. One of the consequences is a greater attention to the risk of damage on existing structures. Thus, the assessment of potential damage of surface buildings has become an essential stage in the excavation projects in urban areas (Chapter 1). The current damage risk assessment procedure is based on strong simplifications, which not always lead to conservative results. Object of this thesis is the development of an improved damage classification system, which takes into account the parameters influencing the structural response to settlement, like the non-linear behaviour of masonry and the soil-structure interaction. The methodology used in this research is based on experimental and numerical modelling. The design and execution of an experimental benchmark test representative of the problem allows to identify the principal factors and mechanisms involved. The numerical simulations enable to generalize the results to a broader range of physical scenarios. The methodological choice is based on a critical review of the currently available procedures for the assessment of settlement-induced building damage (Chapter 2). A new experimental test on a 1/10th masonry façade with a rubber base interface is specifically designed to investigate the effect of soil-structure interaction on the tunnelling-induced damage (Chapter 3). The experimental results are used to validate a 2D semi-coupled finite element model for the simulation of the structural response (Chapter 4). The numerical approach, which includes a continuum cracking model for the masonry and a non-linear interface to simulate the soil-structure interaction, is then used to perform a sensitivity study on the effect of openings, material properties, initial damage, initial conditions, normal and shear behaviour of the base interface and applied settlement profile (Chapter 5). The results assess quantitatively the major role played by the normal stiffness of the soil-structure interaction and by the material parameters defining the quasi-brittle masonry behaviour. The limitation of the 2D modelling approach in simulating the progressive 3D displacement field induced by the excavation and the consequent torsional response of the building are overcome by the development of a 3D coupled model of building, foundation, soil and tunnel (Chapter 6). Following the same method applied to the 2D semi-coupled approach, the 3D model is validated through comparison with the monitoring data of a literature case study. The model is then used to carry out a series of parametric analyses on geometrical factors: the aspect ratio of horizontal building dimensions with respect to the tunnel axis direction, the presence of adjacent structures and the position and alignment of the building with respect to the excavation (Chapter 7). The results show the governing effect of the 3D building response, proving the relevance of 3D modelling. Finally, the results from the 2D and 3D parametric analyses are used to set the framework of an overall damage model which correlates the analysed structural features with the risk for the building of being damaged by a certain settlement (Chapter 8). This research therefore provides an increased experimental and numerical understanding of the building response to excavation-induced settlements, and sets the basis for an operational tool for the risk assessment of structural damage (Chapter 9).

Bayesian inference and learning in Gaussian process state-space models with Particle MCMC

State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.

Classification using log Gaussian Cox processes

McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing properties. Conditioned on the covariates, the distribution over labels is given by a type of conditional Markov random field. In the supervised case, computation of the predictive probability of a single test point scales linearly with the number of training points and the multiclass generalization is straightforward. We show new links between the supervised method and classical nonparametric methods. We give a detailed analysis of the pairwise graph representable Markov random field, which we use to extend the model to semi-supervised learning problems, and propose an inference method based on graph min-cuts. We give the first experimental analysis on supervised and semi-supervised datasets and show good empirical performance.

Molecular basis of transferrin polymorphism in goldfish (Carassius auratus)

Transferrin (TF) polymorphism was investigated in a color variety of goldfish (Carassius auratus), and its molecular basis analyzed. Three TF variants (A(1), A(2) and B-1) were identified from an inbred strain of the goldfish, of which A(1) and B-1 displayed a large electrophoretic difference on both native and SDS-PAGE gels. The TF cDNAs corresponding to variants A(1) and B-1 were cloned and sequenced from A(1)A(1), A(1)B(1) and B1B1 individuals, and their deduced amino acid sequences were analyzed. Substantial amino acid variation occurred between variants A(1) and B-1, with significant differences in peptide length, theoretical molecular weight (Mw) and isoelectric point (pI). No potential glycosylation sites were observed in the two amino acid sequences, which excluded the possibility that carbohydrate difference might cause electrophoretic variation among the TF variants. Further analysis suggested that the distinct electrophoretic mobility of the two variants A(1) and B-1 by SDS-PAGE resulted from their Mw difference, while the difference by the native PAGE could be explained by their pI variation. Furthermore, genomic DNA fragments containing the transferrin alleles were amplified and subjected to RFLP analysis in A(1)A(1), A(1)B(1) and B1B1 individuals. The data revealed characteristic banding patterns for each TF genotype, and demonstrated that the TF alleles A(1) and B-1 could be used as a co-dominant marker system. The initial work relating to the goldfish TF variants will benefit the understanding of the evolutionary and functional significance of TF polymorphism in fish.

A criterion for local interconvertibility between all-tripartite Gaussian states

We arrive at a necessary and sufficient criterion that can be readily used for interconvertibility between general, all-tripartite Gaussian states under local quantum operation. The derivation involves a systematic reduction that converts the original complex conditions in high-dimensional, 6n x 6n matrix space eventually into 2 x 2 matrix problems.

Dynamics of quantum dissipation systems interacting with fermion and boson grand canonical bath ensembles: Hierarchical equations of motion approach

A hierarchical equations of motion formalism for a quantum dissipation system in a grand canonical bath ensemble surrounding is constructed on the basis of the calculus-on-path-integral algorithm, together with the parametrization of arbitrary non-Markovian bath that satisfies fluctuation-dissipation theorem. The influence functionals for both the fermion or boson bath interaction are found to be of the same path integral expression as the canonical bath, assuming they all satisfy the Gaussian statistics. However, the equation of motion formalism is different due to the fluctuation-dissipation theories that are distinct and used explicitly. The implications of the present work to quantum transport through molecular wires and electron transfer in complex molecular systems are discussed. (c) 2007 American Institute of Physics.

Conditions for the local manipulation of all bipartite Gaussian states

We provide a general, necessary, and sufficient condition for the possibility of transforming a mixed bipartite Gaussian state with arbitrarily many modes to another one under arbitrary local Gaussian channels, which do not include classical communication. Moreover, by means of this condition we present a necessary criterion that can be used to check the possibility of a state transformation between two mixed Gaussian states. At the same time, we prove that our criterion can be reduced to the Eisert-Plenio criterion when the mode number is chosen as 1 per side.

Conditions for the local manipulation of tripartite Gaussian states

We present the normal form of the covariance matrix for three-mode tripartite Gaussian states. By means of this result, the general form of a necessary and sufficient criterion for the possibility of a state transformation from one tripartite entangled Gaussian state to another with three modes is found. Moreover, we show that the conditions presented include not only inequalities but equalities as well.

An adaptive controller for a class of nonlinear system using direction basis function

For a class of nonlinear dynamical systems, the adaptive controllers are investigated using direction basis function (DBF) in this paper. Based on the criterion of Lyapunov' stability, DBF is designed which guarantees that the output of the controlled system asymptotically tracks the reference signals. Finally, the simulation shows the good tracking effectiveness of the adaptive controller.