An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed herein. Local control networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer linear quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.

Impact of weather conditions on electric vehicle performance

Seasonal and day-to-day variations in travel behaviour and performance of private passenger vehicles can be partially explained by changes in weather conditions. Likewise, in the electricity sector, weather affects energy demand. The impact of weather conditions on private passenger vehicle performance, usership statistics and travel behaviour has been studied for conventional, internal combustion engine, vehicles. Similarly, weather-driven variability in electricity demand and generation has been investigated widely. The aim of these analyses in both sectors is to improve energy efficiency, reduce consumption in peak hours and reduce greenhouse gas emissions. However, the potential effects of seasonal weather variations on electric vehicle usage have not yet been investigated. In Ireland the government has set a target requiring 10% of all vehicles in the transport fleet to be powered by electricity by 2020 to meet part of its European Union obligations to reduce greenhouse gas emissions and increase energy efficiency. This paper fills this knowledge gap by compiling some of the published information available for internal combustion engine vehicles and applying the lessons learned and results to electric vehicles with an analysis of historical weather data in Ireland and electricity market data in a number of what-if scenarios. Areas particularly impacted by weather conditions are battery performance, energy consumption and choice of transportation mode by private individuals.

An Analysis of the Effect of Electric Vehicle Charging on the Operation of the Single Electricity Market

To meet European Union renewable energy and greenhouse gas emissions reduction targets the Irish government set a target in 2008 that 10% of all vehicles in the transport fleet be powered by electricity by 2020. Similar electric vehicle targets have been introduced in other countries. However, reducing energy consumption and decreasing greenhouse gas emissions in transport is a considerable challenge due to heavy reliance on fossil fuels. In fact, transport in the Republic of Ireland in 2009 accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the effect of electric vehicle charging on the operation of the single wholesale electricity market for the Republic of Ireland and Northern Ireland is analysed. The energy consumed, greenhouse gas emissions generated and changes to the wholesale price of electricity under peak and off-peak charging scenarios are quantified and discussed. Results from the study show that off-peak charging is more beneficial than peak charging.

Politeness and social signals

In the literature, politeness has been researched within many disciplines. Although Brown and Levinson’s theory of politeness (1978, 1987) is often cited, it is primarily a linguistic theory and has been criticized for its lack of generalizability to all cultures. Consequently, there is a need for a more comprehensive approach to understand and explain politeness. We suggest applying a social signal framework that considers politeness as a communicative state. By doing so, we aim to unify and explain politeness and its corresponding research and identify further research needed in this area.

Low flow water quality in rivers; septic tank systems and high-resolution phosphorus signals

Rural point sources of phosphorus (P), including septic tank systems, provide a small part of the overall phosphorus budget to surface waters in agricultural catchments but can have a disproportionate impact on the low flow P concentration of receiving rivers. This has particular importance as the discharges are approximately constant into receiving waters and these have restricted dilution capacity during ecologically sensitive summer periods. In this study, a number of identified high impact septic systems were replaced with modern sequential batch reactors in three rural catchments during a monitoring period of 4 years. Sub-hourly P monitoring was conducted using bankside-analysers. Results show that strategic replacement of defective septic tank systems with modern systems and polishing filters decreased the low flow P concentration of one catchment stream by 0.032 mg TP L- 1 (0.018 mg TRP L- 1) over the 4 years. However two of the catchment mitigation efforts were offset by continued new-builds that increased the density of septic systems from 3.4 km- 2 to 4.6 km- 2 and 13.8 km- 2 to 17.2 km- 2 and subsequently increased low flow P concentrations. Future considerations for septic system mitigation should include catchment carrying capacity as well as technology changes.

Wavelet analysis of bender element signals

Accurate determination of shear wave arrival time using bender elements may be severely affected by a combination of near-field effects and reflected waves. These may mask the first arrival of the shear wave, making its detection difficult in the time domain. This paper describes an approach for measuring the shear wave arrival time through analysis of the output signal in the time-scale domain using a multi-scale wavelet transform. The local maxima lines of the wavelet transform modulus are observed at different scales, and all singularities are mathematically characterised, allowing subsequent detection of the singularity relating to the first arrival. Examples of the use of this approach on typical synthetic and experimental bender element signals are also supplied, and these results are compared with those from other time and frequency domain approaches. The wavelet approach is not affected by near-field effects, but instead is characterised by a relatively consistent singularity related to the shear wave arrival time, across a range of frequencies and noise levels.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Holocene tephras highlight complexity of volcanic signals in Greenland ice cores

Acidity peaks in Greenland ice cores have been used as critical reference horizons for synchronizing ice core records, aiding the construction of a single Greenland Ice Core Chronology (GICC05) for the Holocene. Guided by GICC05, we examined sub-sections of three Greenland cores in the search for tephra from specific eruptions that might facilitate the linkage of ice core records, the dating of prehistoric tephras and the understanding of the eruptions. Here we report the identification of 14 horizons with tephra particles, including 11 that have not previously been reported from the North Atlantic region and that have the potential to be valuable isochrons. The positions of tephras whose major element data are consistent with ash from the Katmai AD 1912 and Öraefajökull AD 1362 eruptions confirm the annually resolved ice core chronology for the last 700 years. We provide a more refined date for the so-called “AD860B” tephra, a widespread isochron found across NW Europe, and present new evidence relating to the 17th century BC Thera/Aniakchak debate that shows N. American eruptions likely contributed to the acid signals at this time. Our results emphasize the variable spatial and temporal distributions of volcanic products in Greenland ice that call for a more cautious approach in the attribution of acid signals to specific eruptive events.

A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle

Previous research based on theoretical simulations has shown the potential of the wavelet transform to detect damage in a beam by analysing the time-deflection response due to a constant moving load. However, its application to identify damage from the response of a bridge to a vehicle raises a number of questions. Firstly, it may be difficult to record the difference in the deflection signal between a healthy and a slightly damaged structure to the required level of accuracy and high scanning frequencies in the field. Secondly, the bridge is going to have a road profile and it will be loaded by a sprung vehicle and time-varying forces rather than a constant load. Therefore, an algorithm based on a plot of wavelet coefficients versus time to detect damage (a singularity in the plot) appears to be very sensitive to noise. This paper addresses these questions by: (a) using the acceleration signal, instead of the deflection signal, (b) employing a vehicle-bridge finite element interaction model, and (c) developing a novel wavelet-based approach using wavelet energy content at each bridge section which proves to be more sensitive to damage than a wavelet coefficient line plot at a given scale as employed by others.

Self-potential and spectral induced polarization signals associated with microbial sulphate reduction

Self-potential and spectral induced polarization responses associated with microbial processes involved in sulphate reduction have been monitored in a Perspex Winogradsky column filled with glass beads and growth medium. Salt-bridge is utilized as an electrolytic contact between experiment and control column. Equally spaced SP electrodes are used in combination of Ag-AgCl electrodes to compare electrodic and SP signals associated with the microbial processes involved in sulphate reduction. This study reveals that magnitude of SP varies from 5 to -2 mV and Electrodic potential 0 to -20 mV at the time of domination (day 39) of sulphate reducing bacteria which are very small in comparison to those measured by fixing both measuring and reference Ag-AgCl electrodes in experiment column. We observed that real and imaginary parts of complex conductivities increase with increase in production of H2S and CO in the experiment column. Both real and imaginary parts of surface complex conductivity vary at low frequencies similar to typical growth curve of bacterial population. Sodium lactate as a carbon source, dissolved in Lagan River water was flushed into the column for biostimulation on 144th day. The dissolved oxygen in flushed fluid might have killed the anaerobes in the column and decrease in complex conductivities similar to death phase of bacteria is observed for one week. The results obtained from this experiment should contribute to further understanding the biogeophysical responses involved in complex environments.


Read More: http://library.seg.org/doi/abs/10.1190/segj092009-001.57