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Projects / Programmes source: ARIS

Računalniško podprto vodenje in optimiranje zveznih in šaržnih procesov. (Študij kombinacij načrtovanih metod in vključevanje pristopov (Slovene)

Research activity

Code Science Field Subfield
2.06.00  Engineering sciences and technologies  Systems and cybernetics   

Code Science Field
T125  Technological sciences  Automation, robotics, control engineering 
P176  Natural sciences and mathematics  Artificial intelligence 
Keywords
System theory, Control theory, Process modelling, Identification, Simulation, Adaptive Systems, Multivariable systems, Intelligent Control, Supervisory Systems, Sequential Control, Predictive control, Industrial processes, Biomedical processes, Education aspects, Multimedia
Evaluation (rules)
source: COBISS
Researchers (14)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  04142  PhD Maja Atanasijević Kunc  Systems and cybernetics  Researcher  1996 - 2001  339 
2.  15395  PhD Aleš Belič  Systems and cybernetics  Researcher  1996 - 2001  323 
3.  16422  PhD Sašo Blažič  Systems and cybernetics  Researcher  1996 - 2001  329 
4.  05807  PhD Nadja Hvala  Systems and cybernetics  Researcher  1996 - 2001  208 
5.  01952  PhD Rihard Karba  Systems and cybernetics  Head  1998 - 2001  622 
6.  10598  PhD Juš Kocijan  Systems and cybernetics  Researcher  1996 - 2001  451 
7.  01951  PhD Drago Matko  Systems and cybernetics  Researcher  1996 - 2001  582 
8.  13565  PhD Gašper Mušič  Systems and cybernetics  Researcher  1996 - 2001  451 
9.  17133  Milan Simčič    Researcher  1999 - 2001  34 
10.  02830  PhD Stanislav Strmčnik  Systems and cybernetics  Researcher  1996 - 2001  488 
11.  01939  MSc Peter Šega  Systems and cybernetics  Researcher  1996 - 2001  116 
12.  10742  PhD Igor Škrjanc  Systems and cybernetics  Researcher  2000 - 2001  736 
13.  15583  Miroslav Štrubelj    Researcher  1996 - 2001  30 
14.  00172  PhD Borut Zupančič  Systems and cybernetics  Researcher  1996 - 2001  418 
Organisations (2)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  1538  University of Ljubljana, Faculty of Electrical Engineering  Ljubljana  1626965  27,861 
2.  0106  Jožef Stefan Institute  Ljubljana  5051606000  91,384 
Abstract
Project deals with the problems connected with three basic hypotheses. The first one tends to support the statement that combination of control design methods with included expert knowledge increases the efficacy of control design procedure as well as the simplicity of the multivariable control design methods completed with the corresponding expert system, the multivariable predictive controllers designed bz the aid of individual channel design approach and iterative procedure combining identification and control design steps are investigated. Second hypothesis indicates the possibility that fuzzy control systems and process identification with neural nets improve the properties and usefulness of the adaptive controllers. The latter base on the identification of the inverse fuzzy model given in the relational matrix form. Neural networks on the other hand exhibit very good results in identification of nonlinear processes, what is confirmed also by the trials on laboratory plants. The obtained knowledge enables the application on concrete industrial batch process controlled bz the aid of flexible recipes. Fuzzy-neural model was used also in the model based control scheme. Third hypothesis deals with the fact that the development of the environment enabling the simulation and direct application of the designed control algorithm on the target computer as well as the use of object oriented tools for modelling and simulation significantly simplify the transfer of theoretical results in practise. The main idea is to enable the implementation of selftuning, adaptive, fuzzy and other complex control algorithms on the low cost computer controllers and programmable logic controllers. In this sense the corresponding adaptations in the MATLAB - SIMULINK environment are proposed. Object oriented modelling and simulation tools completed with problem oriented libraries contribute to the simplification of model development procedure. Problem domains are mainly control technology and biomedicine.
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