Towards an intelligent score following system: Handling of mistakes and jumps encountered during piano practicing

Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

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.

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

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.

Integrating wind power using intelligent electric water heating

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.