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Content archived on 2024-05-07
Network for development and evaluation of numerically reliable software in control engineering and its implementation in production technologies

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Fostering control engineering in production technologies

A network for development and evaluation of numerically reliable software in control engineering and its implementation in production technologies has been developed. Among its objectives the so-called NICONET is also responsible for the SCILOT software tool for systems control and process identification.

Since September 2001, the NICONET network has been established between expert groups in the area of numerical software development for systems and control. This expertise was drawn from the consortium of a thematic network project that was formed to formalise and extend collaboration within this field. NICONET is acting as the information centre for the dissemination of the latest news on numeric computations in control software as well as the organisation of workshops and training courses. Another important activity of NICONET is the maintenance and coordination of further development of the library SLICOT. The freeware subroutine SLICOT offers basic tools for the analysis and design of control systems and allows Fortran 77 implementations of numerical algorithms for computations in control and systems theory. The latest version comprises around 400 user-centred and computational routines, on various domains of systems and control coming along with on-line documentation. The highly reusable SLICOT may be utilised as the computational basic module in different Computer-Aided Control System Design (CACSD) platforms. Additionally, SLICOT-based gateways to MATLAB and Scilab for various computational problems. Such problems include structured matrix decompositions, non-linear systems simulation, model and controller reduction as well as robust control. SLICOT has been successfully employed in a wide range of applications within intelligent manufacturing, automotive and process industries for controlling systems, reducing models and identifying processes. Implementation robustness, numerical stability and accuracy of algorithms, computational efficiency, standardisation and benchmarking are some of the system's strongest features. Furthermore, integration of this tool in industrial systems was found to resolve a lot of industrial problems related to complex and corrupted data and conditions resulting the improvement of the overall effectiveness of production technologies. For scientific uses SLICOT is freely available, while license agreements are required if commercial exploitation is sought. For more information, click: http://www.win.tue.nl/niconet/(opens in new window)

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