A Fault-Tolerant Two-Motor Drive With FCS-MP-Based Flux and Torque Control

Independently controlled multi-motor drives are typically realized by using a common dc link and independent sets of three-phase inverters and motors. In the case of an open-circuit fault in an inverter leg, one motor becomes single-phase. To enable continued controllable operation by eliminating single-phasing, the supply for the motor phase with the faulted inverter leg can be paralleled to a healthy leg of another inverter, using hardware reconfiguration. Hence, the two motors are now supplied from a five-leg inverter, which has inherent voltage and current limitations. Theoretically, violating the voltage limit leads to inverter over-modulation and large torque oscillations. It is shown here that the finite-control-set model predictive control (FCS-MPC), designed to control the machines’ stator flux and torque, can consider the inherent voltage limit dynamically in the control loop. Apart from preserving the independent control of the two machines, the additional constraint consideration significantly widens the operating speed ranges of the machines. In particular, it is shown that whenever the voltage limit is entered, the controller reduces the stator flux level automatically, without requiring external flux reference change. The obtained performance is illustrated using experimental results and is also compared to the conventional two-motor field-oriented control scheme. The control concept is thus fully experimentally verified

A Comparative Study of Synchronous Current Control Schemes Based on FCS-MPC and PI-PWM for a Two-Motor Three-Phase Drive

A two-motor drive, supplied by a five-leg inverter, is considered in this paper. The independent control of machines with full dc-bus voltage utilization is typically achieved using an existing pulsewidth modulation (PWM) technique in conjunction with field-oriented control, based on PI current control. However, model predictive control (MPC), based on a finite number of control inputs [finite-control-set MPC (FCS-MPC)], does not utilize a pulsewidth modulator. This paper introduces three FCS-MPC schemes for synchronous current control in this drive system. The first scheme uses all of the available switching states. The second and third schemes are aimed at reducing the computational burden and utilize a reduced set of voltage vectors and a duty ratio partitioning principle, respectively. Steady-state and transient performances are analyzed and compared both against each other and with respect to the field-oriented control based on PI controllers and PWM. All analyses are experimental and use the same experimental rig and test conditions. Comparison of the predictive schemes leads to the conclusion that the first two schemes have the fastest transient response. The third scheme has a much smaller current ripple while achieving perfect control decoupling between the machines and is of low computational complexity. Nevertheless, at approximately the same switching loss, the PI-PWM control yields the lowest current ripple but with slower electrical transient response. © 1982-2012 IEEE

The experience of gambling problems in British professional footballers: A preliminary qualitative study

Media reports suggest high rates of gambling amongst professional footballers but little is known about how footballers develop and then seek help for gambling problems. Here, we report the findings of in-depth, qualitative interviews with 11 British professional footballers who had, or who were, being treated for gambling problems at a residential clinic. These individuals experienced gambling as a highly salient feature of life as a professional football player in UK professional leagues. Often gambling began as part of social networks of young players, but then progressed to gambling problematically in isolation. Factors that facilitated this transition included structural aspects of professional football as an occupation (e.g. high salaries, spare time, gambling as a shared leisure pursuit) as well as the competitive and emotional challenges of the game (e.g. loss of form, injury or contract release and their effects upon mood). Seeking help was delayed by a reluctance to disclose problems to peers and club managers, but facilitated by recommendations from other players with similar experiences

Evidence for a pervasive 'idling-mode' activity template in flying and pedestrian insects

This is the final version. Available on open access from the Royal Society via the DOI in this recordUnderstanding the complex movement patterns of animals in natural environments is a key objective of 'movement ecology'. Complexity results from behavioural responses to external stimuli but can also arise spontaneously in their absence. Drawing on theoretical arguments about decision-making circuitry, we predict that the spontaneous patterns will be scale-free and universal, being independent of taxon and mode of locomotion. To test this hypothesis, we examined the activity patterns of the European honeybee, and multiple species of noctuid moth, tethered to flight mills and exposed to minimal external cues. We also reanalysed pre-existing data for Drosophila flies walking in featureless environments. Across these species, we found evidence of common scale-invariant properties in their movement patterns; pause and movement durations were typically power law distributed over a range of scales and characterized by exponents close to 3/2. Our analyses are suggestive of the presence of a pervasive scale-invariant template for locomotion which, when acted on by environmental cues, produces the movements with characteristic scales observed in nature. Our results indicate that scale-finite complexity as embodied, for instance, in correlated random walk models, may be the result of environmental cues overriding innate behaviour, and that scale-free movements may be intrinsic and not limited to 'blind' foragers as previously thought.Rothamsted research receives grant aided support from the Biotechnology and Biological Sciences Research Council. S.W. was funded jointly by a grant from BBSRC, Defra, NERC, the Scottish Government and the Wellcome Trust, under the Insect Pollinators Initiative (grant nos. BB/I00097/1). A.J.P. was funded by a BBSRC Doctoral Training Partnership in Food Security awarded to K.W. and J.W.C. H.B.C.J. was funded by a BBSRC Quota studentship awarded to J.W.C. and J.K.

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg$^2$ region about 1000 times during the anticipated 10 years of operations (distributed over six bands, $ugrizy$). Each 30-second long visit will deliver 5$\sigma$ depth for point sources of $r\sim24.5$ on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be 1) rapid and robust classification of sources detected in difference images, and 2) {\it simultaneous} treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects.Comment: Presented at the "Classification and Discovery in Large Astronomical Surveys" meeting, Ringberg Castle, 14-17 October, 200

Impairments in reinforcement learning do not explain enhanced habit formation in cocaine use disorder

Abstract: Rationale: Drug addiction has been suggested to develop through drug-induced changes in learning and memory processes. Whilst the initiation of drug use is typically goal-directed and hedonically motivated, over time, drug-taking may develop into a stimulus-driven habit, characterised by persistent use of the drug irrespective of the consequences. Converging lines of evidence suggest that stimulant drugs facilitate the transition of goal-directed into habitual drug-taking, but their contribution to goal-directed learning is less clear. Computational modelling may provide an elegant means for elucidating changes during instrumental learning that may explain enhanced habit formation. Objectives: We used formal reinforcement learning algorithms to deconstruct the process of appetitive instrumental learning and to explore potential associations between goal-directed and habitual actions in patients with cocaine use disorder (CUD). Methods: We re-analysed appetitive instrumental learning data in 55 healthy control volunteers and 70 CUD patients by applying a reinforcement learning model within a hierarchical Bayesian framework. We used a regression model to determine the influence of learning parameters and variations in brain structure on subsequent habit formation. Results: Poor instrumental learning performance in CUD patients was largely determined by difficulties with learning from feedback, as reflected by a significantly reduced learning rate. Subsequent formation of habitual response patterns was partly explained by group status and individual variation in reinforcement sensitivity. White matter integrity within goal-directed networks was only associated with performance parameters in controls but not in CUD patients. Conclusions: Our data indicate that impairments in reinforcement learning are insufficient to account for enhanced habitual responding in CUD

Impairments in reinforcement learning do not explain enhanced habit formation in cocaine use disorder

Rationale Drug addiction has been suggested to develop through drug-induced changes in learning and memory processes. Whilst the initiation of drug use is typically goal-directed and hedonically motivated, over time, drug-taking may develop into a stimulus-driven habit, characterised by persistent use of the drug irrespective of the consequences. Converging lines of evidence suggest that stimulant drugs facilitate the transition of goal-directed into habitual drug-taking, but their contribution to goal-directed learning is less clear. Computational modelling may provide an elegant means for elucidating changes during instrumental learning that may explain enhanced habit formation. Objectives We used formal reinforcement learning algorithms to deconstruct the process of appetitive instrumental learning and to explore potential associations between goal-directed and habitual actions in patients with cocaine use disorder (CUD). Methods We re-analysed appetitive instrumental learning data in 55 healthy control volunteers and 70 CUD patients by applying a reinforcement learning model within a hierarchical Bayesian framework. We used a regression model to determine the influence of learning parameters and variations in brain structure on subsequent habit formation. Results Poor instrumental learning performance in CUD patients was largely determined by difficulties with learning from feedback, as reflected by a significantly reduced learning rate. Subsequent formation of habitual response patterns was partly explained by group status and individual variation in reinforcement sensitivity. White matter integrity within goal-directed networks was only associated with performance parameters in controls but not in CUD patients. Conclusions Our data indicate that impairments in reinforcement learning are insufficient to account for enhanced habitual responding in CUD

Genomewide transcriptional signatures of migratory flight activity in a globally invasive insect pest

Migration is a key life history strategy for many animals and requires a suite of behavioural, morphological and physiological adaptations which together form the migratory syndrome'. Genetic variation has been demonstrated for many traits that make up this syndrome, but the underlying genes involved remain elusive. Recent studies investigating migration-associated genes have focussed on sampling migratory and nonmigratory populations from different geographic locations but have seldom explored phenotypic variation in a migratory trait. Here, we use a novel combination of tethered flight and next-generation sequencing to determine transcriptomic differences associated with flight activity in a globally invasive moth pest, the cotton bollworm Helicoverpa armigera. By developing a state-of-the-art phenotyping platform, we show that field-collected H.armigera display continuous variation in flight performance with individuals capable of flying up to 40km during a single night. Comparative transcriptomics of flight phenotypes drove a gene expression analysis to reveal a suite of expressed candidate genes which are clearly related to physiological adaptations required for long-distance flight. These include genes important to the mobilization of lipids as flight fuel, the development of flight muscle structure and the regulation of hormones that influence migratory physiology. We conclude that the ability to express this complex set of pathways underlines the remarkable flexibility of facultative insect migrants to respond to deteriorating conditions in the form of migratory flight and, more broadly, the results provide novel insights into the fundamental transcriptional changes required for migration in insects and other taxa

Interpreting and acting upon home blood pressure readings: A qualitative study

This article is made available through the Brunel Open Access Publishing Fund. Copyright @ 2013 Vasileiou et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Recent guidelines recognize the importance of home blood pressure monitoring (HBPM) as an adjunct to clinical measurements. We explored how people who have purchased and use a home blood pressure (BP) monitor make sense of, and act upon, readings and how they communicate with their doctor about the practice of home monitoring. Methods: A qualitative study was designed and participants were purposively recruited from several areas in England, UK. Semi-structured in-depth interviews were conducted with 18 users of home BP monitors. The transcribed data were thematically analysed. Results: Interpretation of home BP readings is complex, and is often characterised by uncertainty. People seek to assess value normality using ‘rules of thumb’, and often aim to identify the potential causes of the readings. This is done by drawing on lay models of BP function and by contextualising the readings to personal circumstances. Based on the perceived causes of the problematic readings, actions are initiated, mostly relating to changes in daily routines. Contacting the doctor was more likely when the problematic readings persisted and could not be easily explained, or when participants did not succeed in regulating their BP through their other interventions. Most users had notified their doctor of the practice of home monitoring, but medical involvement varied, with some participants reporting disinterest or reservations by doctors. Conclusions: Involvement from doctors can help people overcome difficulties and resolve uncertainties around the interpretation of home readings, and ensure that the rules of thumb are appropriate. Home monitoring can be used to strengthen the patient-clinician relationship

Evidence for a pervasive 'idling-mode' activity template in flying and pedestrian insects

Understanding the complex movement patterns of animals in natural environments is a key objective of ‘movement ecology’. Complexity results from behavioural responses to external stimuli but can also arise spontaneously in their absence. Drawing on theoretical arguments about decision-making circuitry, we predict that the spontaneous patterns will be scale-free and universal, being independent of taxon and mode of locomotion. To test this hypothesis, we examined the activity patterns of the European honeybee, and multiple species of noctuid moth, tethered to flight mills and exposed to minimal external cues. We also reanalysed pre-existing data for Drosophila flies walking in featureless environments. Across these species, we found evidence of common scale-invariant properties in their movement patterns; pause and movement durations were typically power law distributed over a range of scales and characterized by exponents close to 3/2. Our analyses are suggestive of the presence of a pervasive scale-invariant template for locomotion which, when acted on by environmental cues, produces the movements with characteristic scales observed in nature. Our results indicate that scale-finite complexity as embodied, for instance, in correlated random walk models, may be the result of environmental cues overriding innate behaviour, and that scale-free movements may be intrinsic and not limited to ‘blind’ foragers as previously thought