CAutoCSD-evolutionary search and optimisation enabled computer automated control system design
نویسندگان
چکیده
منابع مشابه
Grid Services in Action: Grid Enabled Optimisation and Design Search
We are developing a Grid Enabled Optimisation and Design Search system (GEODISE). It offers grid-based access to a state-of-the-art collection of optimisation and design search tools, industrial strength analysis codes, and distributed computing and data resources.
متن کاملCFD-Based Shape Optimisation with Grid-Enabled Design Search Toolkits
This paper presents an application of applying Grid computing technologies in the field of engineering design optimisation using computational fluid dynamics (CFD). Three essential elements in CFD-based shape optimisation problems (CAD, mesh generation, and solution) are integrated and automated within the Matlab scripting environment augmented with Grid-enabled computation and database toolkit...
متن کاملGenerative Representations for Computer-Automated Evolutionary Design
With the increasing computational power of computers, software design systems are progressing from being tools enabling architects and designers to express their ideas, to tools capable of creating designs under human guidance. One of the main limitations for these computer-automated design systems is the representation with which they encode designs. If the representation cannot encode a certa...
متن کاملComputer Automated Multi-Paradigm Modeling in Control System Design
The complete control system design effort involves many stages during which partial design tasks are completed. Each of these tasks requires different modeling paradigms and different tools. Furthermore, the designed embedded control system entails a wide variety of implementation technologies that all require different specification formalisms. To handle such a multitude of modeling paradigms ...
متن کاملDouble Shock Control Bump Design Optimisation Using Hybridised Evolutionary Algorithms
The paper investigates the application of two advanced optimisation methods for solving active flow control device shape design problem and compares their optimisation efficiency in terms of computational cost and design quality. The first optimisation method uses Hierarchical Asynchronous Parallel Multi-Objective Evolutionary Algorithm (HAPMOEA) and the second uses Hybridized EA with Nash-Game...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Automation and Computing
سال: 2004
ISSN: 1476-8186,1751-8520
DOI: 10.1007/s11633-004-0076-8