Robust control algorithm for grid-interfaced three-phase inverters with high-bandwidth LCL filter

The paper introduces the design of robust current and voltage control algorithms for a grid-connected three-phase inverter which is interfaced to the grid through a high-bandwidth three-phase LCL filter. The algorithms are based on the state feedback control which have been designed in a systematic approach and improved by using oversampling to deal with the issues arising due to the high-bandwidth filter. An adaptive loop delay compensation method has also been adopted to minimize the adverse effects of loop delay in digital controller and to increase the robustness of the control algorithm in the presence of parameter variations. Simulation results are presented to validate the effectiveness of the proposed algorithm.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Ongoing Adaptation as a Feature of Complexity : Further Thoughts and Possible Ideas for Pedagogy in Physical Activity

This chapter takes as its central premise the human capacity to adapt to changing environments. It is an idea that is central to complexity theory but receives only modest attention in relation to learning. To do this we will draw from a range of fields and then consider some recent research in motor control that may extend the discussion in ways not yet considered, but that will build on advances already made within pedagogy and motor control synergies. Recent work in motor control indicates that humans have far greater capacity to adapt to the ‘product space’ than was previously thought, mainly through fast heuristics and on-line corrections. These are changes that can be made in real (movement) time and are facilitated by what are referred to as ‘feed-forward’ mechanisms that take advantage of ultra-fast ways of recognizing the likely outcomes of our movements and using this as a source of feedback. We conclude by discussing some possible ideas for pedagogy within the sport and physical activity domains, the implications of which would require a rethink on how motor skill learning opportunities might best be facilitated.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Cross Talk between Receptor Guanylyl Cyclase C and c-src Tyrosine Kinase Regulates Colon Cancer Cell Cytostasis

Increased activation of c-src seen in colorectal cancer is an indicator of a poor clinical prognosis, suggesting that identification of downstream effectors of c-src may lead to new avenues of therapy. Guanylyl cyclase C (GC-C) is a receptor for the gastrointestinal hormones guanylin and uroguanylin and the bacterial heat-stable enterotoxin. Though activation of GC-C by its ligands elevates intracellular cyclic GMP (cGMP) levels and inhibits cell proliferation, its persistent expression in colorectal carcinomas and occult metastases makes it a marker for malignancy. We show here that GC-C is a substrate for inhibitory phosphorylation by c-src, resulting in reduced ligand-mediated cGMP production. Consequently, active c-src in colonic cells can overcome GC-C-mediated control of the cell cycle. Furthermore, docking of the c-src SH2 domain to phosphorylated GC-C results in colocalization and further activation of c-src. We therefore propose a novel feed-forward mechanism of activation of c-src that is induced by cross talk between a receptor GC and a tyrosine kinase. Our findings have important implications in understanding the molecular mechanisms involved in the progression and treatment of colorectal cancer.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Correct biological timing in Arabidopsis requires multiple light-signaling pathways.

Circadian oscillators provide rhythmic temporal cues for a range of biological processes in plants and animals, enabling anticipation of the day/night cycle and enhancing fitness-associated traits. We have used engineering models to understand the control principles of a plant's response to seasonal variation. We show that the seasonal changes in the timing of circadian outputs require light regulation via feed-forward loops, combining rapid light-signaling pathways with entrained circadian oscillators. Linear time-invariant models of circadian rhythms were computed for 3,503 circadian-regulated genes and for the concentration of cytosolic-free calcium to quantify the magnitude and timing of regulation by circadian oscillators and light-signaling pathways. Bioinformatic and experimental analysis show that rapid light-induced regulation of circadian outputs is associated with seasonal rephasing of the output rhythm. We identify that external coincidence is required for rephasing of multiple output rhythms, and is therefore important in general phase control in addition to specific photoperiod-dependent processes such as flowering and hypocotyl elongation. Our findings uncover a fundamental design principle of circadian regulation, and identify the importance of rapid light-signaling pathways in temporal control.

Asymptotic Hyperstability of a Class of Linear Systems under Impulsive Controls Subject to an Integral Popovian Constraint

This paper is focused on the study of the important property of the asymptotic hyperstability of a class of continuous-time dynamic systems. The presence of a parallel connection of a strictly stable subsystem to an asymptotically hyperstable one in the feed-forward loop is allowed while it has also admitted the generation of a finite or infinite number of impulsive control actions which can be combined with a general form of nonimpulsive controls. The asymptotic hyperstability property is guaranteed under a set of sufficiency-type conditions for the impulsive controls.

Force ripple compensation in a tubular linear generator for marine renewable generation

Tubular permanent magnet linear generators are a promising generator technology for use in marine renewables. One aspect of their design relates to the conditions necessary for achieving a smooth thrust response from the generator, free from cogging and periodic variations due to spatial harmonics of the flux cutting the generator coils. This paper presents an experimental and finite element study of the sources of thrust ripple in a prototype linear generator for marine generation. A simple self-commutated control scheme is shown, which uses linear Hall-effect sensors and look-up-table based feed-forward compensation to derive the excitation currents required to drive the machine with constant force. Details of the controller's FPGA based implementation are given, including its strategy for detecting sensor failure. © 2011 IEEE.

洁净机器人手臂的转动惯量分析及运动控制

针对洁净机器人手臂的转动惯量对系统动态性能的影响,在利用动能公式分析得到其转动惯量与位置关系的基础上,提出了一种位置PI闭环加前馈参数整定的控制方法。该控制方法是由位置值实时得到转动惯量,再由转动惯量来实时整定PI参数。仿真结果表明了该控制方法能有效抑制转动惯量的变化对系统动态性能的影响,且简单可行。

Campamento de verano.

El centro organiza un campamento de verano para favorecer el desarrollo de la autonomía y socialización del alumnado mediante un tiempo de convivencia continuado. Dicha actividad, aunque de carácter extraescolar, se incluye en el proceso general educativo y rehabilitador diseñado en la programación anual. Los objetivos son: acercar al niño al campo y al hábitat rural; desarrollar la autonomía social y personal; aprender a desenvolverse fuera de su ámbito familiar, afrontando situaciones nuevas; fomentar un aprendizaje lúdico; y potenciar el equilibrio emocional. Se utiliza una metodología diferente en función de los objetivos que se han de alcanzar y que se aplican tanto en el trabajo individual como grupal (moldeado, modelado, refuerzo, encadenamiento hacia detrás, resolución de problemas, feed-back, feed-forward, etc.). Entre las actividades programadas a lo largo de cada jornada, destacan: estudios de la flora, fauna y accidentes geográficos; paseos y deportes; actividades culturales (cine, pintura, fiestas y bailes); juegos al aire libre; representaciones teatrales y de guiñol, etc. Además, se trabajan de forma cotidiana aspectos fundamentales para el desarrollo de la autonomía personal como control de esfínteres, aseo y vestido, hábitos en la mesa, cuidado de sus pertenencias, normas de convivencia, etc. Se realiza una evaluación a corto plazo mediante hojas de registros que se centra en la valoración de aquellos objetivos medibles, es decir, que se traducen en acciones con una repercusión material. No tiene memoria.

ASSET: moving forward through feedback

Providing high quality and timely feedback to students is often a challenge for many staff in higher education as it can be both time-consuming and frustratingly repetitive. From the student perspective, feedback may sometimes be considered unhelpful, confusing and inconsistent and may not always be provided within a timeframe that is considered to be ‘useful’. The ASSET project, based at the University of Reading, addresses many of these inherent challenges by encouraging the provision of feedback that supports learning, i.e. feedback that contains elements of ‘feed-forward’, is of a high quality and is delivered in a timely manner. In particular, the project exploits the pedagogic benefits of video/audio media within a Web 2.0 context to provide a new, interactive resource, ‘ASSET’, to enhance the feedback experience for both students and staff. A preliminary analysis of both our quantitative and qualitative pedagogic data demonstrate that the ASSET project has instigated change in the ways in which both staff and students think about, deliver, and engage with feedback. For example, data from our online questionnaires and focus groups with staff and students indicate a positive response to the use of video as a medium for delivering feedback to students. In particular, the academic staff engaged in piloting the ASSET resource indicated that i) using video has made them think more, and in some cases differently, about the ways in which they deliver feedback to students and ii) they now see video as an effective means of making feedback more useful and engaging for students. Moreover, the majority of academic staff involved in the project have said they will continue to use video feedback. From the student perspective, 60% of those students whose lecturers used ASSET to provide video feedback said that “receiving video feedback encouraged me to take more notice of the feedback compared with normal methods” and 80% would like their lecturer to continue to use video as a method for providing feedback. An important aim of the project was for it to complement existing University-wide initiatives on feedback and for ASSET to become a ‘model’ resource for staff and students wishing to explore video as a medium for feedback provision. An institutional approach was therefore adopted and key members of Senior Management, academics, T&L support staff, IT support and Student Representatives were embedded within the project from the start. As with all initiatives of this kind, a major issue is the future sustainability of the ASSET resource and to have had both ‘top-down’ and ‘bottom-up’ support for the project has been extremely beneficial. In association with the project team the University is currently exploring the creation of an open-source, two-tiered video supply solution and a ‘framework’ (that other HEIs can adopt and/or adapt) to support staff in using video for feedback provision. In this way students and staff will have new opportunities to explore video and to exploit the benefits of this medium for supporting learning.

A dynamic model of neurovascular coupling: Implications for blood vessel dilation and constriction

Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

A situation awareness interface for a bi-wheeled industrial hovercraft: design, development and evaluation

The intention of this thesis is to develop a prototype interface that enables an operator to control a bi-wheeled industrial hovercraft that will work within a fusion power plant if the automation system fails. This fusion power plant is part of the ITER project a conjoint effort of various industrialized countries to develop cleaner sources of energy. The development of the interface prototype will be based on situation awareness concepts, which provide a means to understand how human operators perceive the world around, then process that information and make decisions based on the knowledge that they already have and the projected knowledge of the reactions that will occur in the world in response to the actions the operator makes. Two major situation awareness methods will be used, GDTA as a means to discover the requirements the interface needs to solve, and SAGAT to conduct the evaluation on the three interfaces. This technique can isolate the differences an operator has in situation awareness when presented with relevant information given by each of the three interfaces that were built for this thesis. Where the first interface presents the information within the operator’s focal point of view in a pictorial style, the second interface shows the same information within the same point of view has the first interface but only shows it in a textual manner. While the third interface shows the relevant information in the operator’s peripheral field of view. Also SAGAT can provide insight on the question to know if providing the operator with feed-forward information about the stoppage distances of the bi-wheeled industrial hovercraft has any effect on the operator’s decision making.