584,865 research outputs found
Instances and connectors : issues for a second generation process language
This work is supported by UK EPSRC grants GR/L34433 and GR/L32699Over the past decade a variety of process languages have been defined, used and evaluated. It is now possible to consider second generation languages based on this experience. Rather than develop a second generation wish list this position paper explores two issues: instances and connectors. Instances relate to the relationship between a process model as a description and the, possibly multiple, enacting instances which are created from it. Connectors refers to the issue of concurrency control and achieving a higher level of abstraction in how parts of a model interact. We believe that these issues are key to developing systems which can effectively support business processes, and that they have not received sufficient attention within the process modelling community. Through exploring these issues we also illustrate our approach to designing a second generation process language.Postprin
Instances and connectors : issues for a second generation process language
This work is supported by UK EPSRC grants GR/L34433 and GR/L32699Over the past decade a variety of process languages have been defined, used and evaluated. It is now possible to consider second generation languages based on this experience. Rather than develop a second generation wish list this position paper explores two issues: instances and connectors. Instances relate to the relationship between a process model as a description and the, possibly multiple, enacting instances which are created from it. Connectors refers to the issue of concurrency control and achieving a higher level of abstraction in how parts of a model interact. We believe that these issues are key to developing systems which can effectively support business processes, and that they have not received sufficient attention within the process modelling community. Through exploring these issues we also illustrate our approach to designing a second generation process language.Postprin
A Robust Consensus Algorithm for Current Sharing and Voltage Regulation in DC Microgrids
In this paper a novel distributed control algorithm for current sharing and
voltage regulation in Direct Current (DC) microgrids is proposed. The DC
microgrid is composed of several Distributed Generation units (DGUs), including
Buck converters and current loads. The considered model permits an arbitrary
network topology and is affected by unknown load demand and modelling
uncertainties. The proposed control strategy exploits a communication network
to achieve proportional current sharing using a consensus-like algorithm.
Voltage regulation is achieved by constraining the system to a suitable
manifold. Two robust control strategies of Sliding Mode (SM) type are developed
to reach the desired manifold in a finite time. The proposed control scheme is
formally analyzed, proving the achievement of proportional current sharing,
while guaranteeing that the weighted average voltage of the microgrid is
identical to the weighted average of the voltage references.Comment: 12 page
Stabilization of grid frequency through dynamic demand control
Frequency stability in electricity networks is essential to the maintenance of supply quality and security. This paper investigates whether a degree of built-in frequency stability could be provided by incorporating dynamic demand control into certain consumer appliances. Such devices would monitor system frequency (a universally available indicator of supply-demand imbalance) and switch the appliance on or off accordingly, striking a compromise between the needs of the appliance and the grid. A simplified computer model of a power grid was created incorporating aggregate generator inertia, governor action and load-frequency dependence plus refrigerators with dynamic demand controllers. Simulation modelling studies were carried out to investigate the system's response to a sudden loss of generation, and to fluctuating wind power. The studies indicated a significant delay in frequency-fall and a reduced dependence on rapidly deployable backup generation
From Event-B models to code: sensing, actuating, and the environment
The Event-B method is a formal approach for modelling systems in safety-, and business-critical, domains. We focus, in this paper, on multi-tasking, embedded control systems. Initially, system specification takes place at a high level of abstraction; detail is added in refinement steps as the development proceeds toward implementation. In previous work, we presented an approach for generating code, for concurrent programs, from Event-B. Translators generate program code for tasks that access data in a safe way, using shared objects. We did not distinguish between tasks of the environment and those of the controller. The work described in this paper offers improved modelling and code generation support, where we separate the environment from the controller. The events in the system can participate in actuating or sensing roles. In the resulting code, sensing and actuation can be simulated using a form of subroutine call; or additional information can be provided to allow a task to read/write directly from/to a specfied memory location
A novel DSM philosophy for building integrated renewable systems
This paper presents an overview of a novel concept in IT network design and power control focused on matching building integrated renewable power generation with local demands. It describes how this is achieved through combination of energy demand reduction and dynamic utilisation of embedded energy storage in a robust, efficient and cost effective manner. A brief overview of the main features of the design is given in terms of its intended benefits as an integrated system. The load components and distribution topology are described for this experimental system within the limits set by the capacity, capabilities and desired function of the network. Power supply to the network is described as including a back-up source to the photovoltaic (PV) source to add functionality and stability with no requirements for undesirable exporting of excess PV generation. The necessary configuration of the renewable array integrating with the network is also highlighted with an example compatible solar module device. A trial of the technology and demand management control in a high profile office building is described. This trial in a live working environment is providing invaluable real world data to compare against modelling and network simulation results
Dynamic Modelling and Adaptive Traction Control for Mobile Robots
Mobile robots have received a great deal of research in recent years. A
significant amount of research has been published in many aspects related to
mobile robots. Most of the research is devoted to design and develop some
control techniques for robot motion and path planning. A large number of
researchers have used kinematic models to develop motion control strategy for
mobile robots. Their argument and assumption that these models are valid if the
robot has low speed, low acceleration and light load. However, dynamic
modelling of mobile robots is very important as they are designed to travel at
higher speed and perform heavy duty work. This paper presents and discusses a
new approach to develop a dynamic model and control strategy for wheeled mobile
robot which I modelled as a rigid body that roles on two wheels and a castor.
The motion control strategy consists of two levels. The first level is dealing
with the dynamic of the system and denoted as Low level controller. The second
level is developed to take care of path planning and trajectory generation
Review and Comparison of Intelligent Optimization Modelling Techniques for Energy Forecasting and Condition-Based Maintenance in PV Plants
Within the field of soft computing, intelligent optimization modelling techniques include
various major techniques in artificial intelligence. These techniques pretend to generate new business
knowledge transforming sets of "raw data" into business value. One of the principal applications of
these techniques is related to the design of predictive analytics for the improvement of advanced
CBM (condition-based maintenance) strategies and energy production forecasting. These advanced
techniques can be used to transform control system data, operational data and maintenance event data
to failure diagnostic and prognostic knowledge and, ultimately, to derive expected energy generation.
One of the systems where these techniques can be applied with massive potential impact are the
legacy monitoring systems existing in solar PV energy generation plants. These systems produce a
great amount of data over time, while at the same time they demand an important e ort in order to
increase their performance through the use of more accurate predictive analytics to reduce production
losses having a direct impact on ROI. How to choose the most suitable techniques to apply is one of
the problems to address. This paper presents a review and a comparative analysis of six intelligent
optimization modelling techniques, which have been applied on a PV plant case study, using the
energy production forecast as the decision variable. The methodology proposed not only pretends
to elicit the most accurate solution but also validates the results, in comparison with the di erent
outputs for the di erent techniques
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