22,943 research outputs found
Communicating Processes with Data for Supervisory Coordination
We employ supervisory controllers to safely coordinate high-level
discrete(-event) behavior of distributed components of complex systems.
Supervisory controllers observe discrete-event system behavior, make a decision
on allowed activities, and communicate the control signals to the involved
parties. Models of the supervisory controllers can be automatically synthesized
based on formal models of the system components and a formalization of the safe
coordination (control) requirements. Based on the obtained models, code
generation can be used to implement the supervisory controllers in software, on
a PLC, or an embedded (micro)processor. In this article, we develop a process
theory with data that supports a model-based systems engineering framework for
supervisory coordination. We employ communication to distinguish between the
different flows of information, i.e., observation and supervision, whereas we
employ data to specify the coordination requirements more compactly, and to
increase the expressivity of the framework. To illustrate the framework, we
remodel an industrial case study involving coordination of maintenance
procedures of a printing process of a high-tech Oce printer.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence
This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation
NL4Py: Agent-Based Modeling in Python with Parallelizable NetLogo Workspaces
NL4Py is a NetLogo controller software for Python, for the rapid, parallel
execution of NetLogo models. NL4Py provides both headless (no graphical user
interface) and GUI NetLogo workspace control through Python. Spurred on by the
increasing availability of open-source computation and machine learning
libraries on the Python package index, there is an increasing demand for such
rapid, parallel execution of agent-based models through Python. NetLogo, being
the language of choice for a majority of agent-based modeling driven research
projects, requires an integration to Python for researchers looking to perform
statistical analyses of agent-based model output using these libraries.
Unfortunately, until the recent introduction of PyNetLogo, and now NL4Py, such
a controller was unavailable.
This article provides a detailed introduction into the usage of NL4Py and
explains its client-server software architecture, highlighting architectural
differences to PyNetLogo. A step-by-step demonstration of global sensitivity
analysis and parameter calibration of the Wolf Sheep Predation model is then
performed through NL4Py. Finally, NL4Py's performance is benchmarked against
PyNetLogo and its combination with IPyParallel, and shown to provide
significant savings in execution time over both configurations
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Designing algorithms to aid discovery by chemical robots
Recently, automated robotic systems have become very efficient, thanks to improved coupling between sensor systems and algorithms, of which the latter have been gaining significance thanks to the increase in computing power over the past few decades. However, intelligent automated chemistry platforms for discovery orientated tasks need to be able to cope with the unknown, which is a profoundly hard problem. In this Outlook, we describe how recent advances in the design and application of algorithms, coupled with the increased amount of chemical data available, and automation and control systems may allow more productive chemical research and the development of chemical robots able to target discovery. This is shown through examples of workflow and data processing with automation and control, and through the use of both well-used and cutting-edge algorithms illustrated using recent studies in chemistry. Finally, several algorithms are presented in relation to chemical robots and chemical intelligence for knowledge discovery
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