No description available.

The concept of consensus filters for sensor fusion is not an entirely new proposition but one with an internally implemented Bayesian fusion is. This work documents a novel state update algorithm for sensor fusion which works using the principle of Bayesian fusion of data with variance implemented on a single integrator consensus algorithm. Comparative demonstrations of how consensus over a pinning network is reached are presented along with a weighted Bayesian Luenberger type observer and a ’Consensus on estimates’ algorithm. This type of a filter is something that is novel and has not been encountered in previous literature related to this topic to the best of our knowledge. In this work, we also extend the proof for a distributed Luenberger type observer design to include the case where the network being considered is a strongly connected digraph.

Study One aimed to provide a current understanding of pupils’ attitudes towards people who are overweight and the prevalence and significance of weight-based unkindness in school. Methods: The study followed a mixed method, sequential qualitative and quantitative research design. Part One of the study used exploratory focus groups to ascertain that weight-based unkindness was a valid concern for children and young people, when compared against unkindness of other content. The focus group also ensured that the vignettes used in the survey (Part Two) were ecologically valid. Part Two included an existing measure of weight-stigma (attitude scale) and three sets of vignette-based questions to measure pupils’ perceptions of the frequency and severity of different incidents of unkindness. Part Two, was administered to 214 participants via a computerised survey. Results: The majority of pupils (61%) judged the overweight characters to be the least accepted. Participants also perceived significantly greater hurt, anger, embarrassment and humour to follow episodes of weight-based unkindness. Study Two aimed to better understand why, how and what is ‘different’ about pupils’ understanding of weight-based unkindness when compared to other types of unkindness. Methods: This study adopted an explorative approach to hear the lived experiences of six teachers and 29 children in two South West Primary Schools. Data was collected via semi-structured interviews, administered through focus groups (pupils) and paired interviews (teachers). Data was analysed using latent thematic analysis (Braun & Clarke, 2006). Results: The study found that pupils used the language of personal choice to attribute personal responsibility to overweight CYP, whilst teachers attributed this blame to their parents. Teachers espoused acceptance for the overweight whilst their behaviours implicitly reinforced the ‘thin-ideal’. Key findings are discussed from a theoretical perspective and their implication for supporting attitude change is highlighted.

Microgrid is an emerging technology in the eld of electrical engineering which employs the concept of Distributed Energy Resources (DERs) in order to generate electricity in a small sized power system. The main objectives of this dissertation are to: 1- design a new control for lower level control of DERs in microgrids, 2- implement distributed upper level control for DERs in microgrids and 3- apply analytical approaches in order to analyze DERs in microgrids. The control in each DER can be divided into two main categories: lower and upper level. Lower level control is the main objective of control in each DER. For example, the lower level control in Photovoltaic (PV) is in charge of transferring the maximum power from sun into the main grid. Unlike the lower level control, the upper level control is an additional control loop on top of the lower level controls. For example, Voltage/Frequency (VF) controllers are installed on top of Active/Reactive (PQ) power controller in energy storage devices as upper level control. In this dissertation, for the lower level control improvements, two widely used DERs are selected (PV, and oshore wind farm) and new control algorithms are developed in order to improve the performance of lower level controllers in these DERs. For the PV lower level improvement, a new control methodology is proposed in order to minimize the maximum power tracking error in PV lower level controller. Second contribution in lower level control is for the oshore wind farm applications based on Multi-Terminal High Voltage Direct Current (MTDC) transmission; a new control is designed in order to minimize the losses in transmission lines through lower level control of High Voltage Direct Current (HVDC) converters. For the upper level control, this dissertation considers the energy storage as another mostly used type of DER in microgrids. The lower level control for energy storage is in charge of controlling the PQ of the energy storage. The main contribution in the upper level control is to implement the distributed control algorithm based on consensus theory for battery energy storages in order to maximize the efficiency, energy management as well as synchronizing the performance of parallel energy storage devices in microgrids. In this case, the consensus based distributed control algorithm with limited information exchange between neighboring energy storage units is proposed and implemented to validate the claim. The third contribution of this research is to apply advanced analysis techniques to evaluate the performance of the DERs in microgrids. Two approaches are introduced for microgrid modeling in this research. Firstly, an impedance modeling technique is used to model the oshore wind farm connected to the main AC grid through HVDC transmission line. Multiple Input Multiple Output (MIMO) Nyquist analysis and singular value analysis are used to assess the interactions between HVDC converter and grid. Secondly, an unbalanced microgrid is considered and Dynamic Phasor (DP) analysis is applied in order to nd the stability limitations under different scenarios. This dissertation has led to seven journal papers (five published, one journal in revision process and one journal submitted recently) and four conference papers.

Les architectures régulières intégrant plusieurs cœurs de traitement sont davantage utilisées dans les systèmes embarqués. Dans cette thèse, on s'intéresse aux mécanismes d'optimisation d'énergie dans des architectures avec une dimension étendue; pour faire face aux problèmes de variabilité technologique et aux changements du contexte applicatif, le processus d'optimisation se déroule en temps réel. Des capteurs in-situ détectent le degré de dégradation du circuit. Quant a la variabilité applicative, des moniteurs d'activité sont insérés sur un niveau architectural pour estimer la charge de travail engendrée par l'application en cours et la consommation qui en découle. Nous avons développé une méthode systématique pour l'intégration de ces capteurs avec un moindre coût en surface. Leurs sorties alimentent un processus d'optimisation basé sur la théorie de consensus et dupliqué dans chaque cœur. Ce contrôle vise à fixer la meilleure configuration locale à chaque cœur permettant d'optimiser la consommation globale du système tout en respectant les contraintes temps réel de l'application en cours. Ce schéma opère d'une manière complètement distribuée afin de garantir la scalabilité de notre solution, et donc sa faisabilité, compte tenu de la complexité des circuits actuels et futurs. / Regular architectures embedding several processing elements are increasingly used in embedded systems. They require careful design to avoid high power consumption and to improve their flexibility. This thesis work deals with optimization mechanisms of large scale architectures; to meet variability issues, optimization is processed at run-time. The target design implements in-situ features to collect physical information about its yield and to monitor application workload and generated consumption. As for workload monitoring, we use activity counters connected at architecture level to a set of critical signals. We developed an automated method to optimally place these features with a minimal area overhead. The collected information are used further jointly with a power model to estimate the dissipated power and then driven appropriate optimization process. Optimal frequency for each core is set by means of a distributed controller based on consensus theory. The resulting settings aim to reduce the whole system power while fulfilling application constraints. The scheme needs to be fully distributed to garantee the control scalability, and so feasibility, as the number of cores scales.