Theory, algorithms and technology in the design of control systems

被引:24
作者
Bars, Ruth [1 ]
Colaneri, Patrizio
de Souza, Carlos E.
Dugard, Luc
Allgower, Frank
Kleimenov, Anatolii
Scherer, Carsten
机构
[1] Budapest Univ Technol & Econ, Dept Automat & Appl Informat, H-1521 Budapest, Hungary
[2] Politecn Milan, Dipartimento Elettron & Informaz, I-20133 Milan, Italy
[3] LNCC, Petropolis, Brazil
[4] ENSIEG, Lab Automat Grenoble, Grenoble, France
[5] Univ Stuttgart, Inst Syst Theory, D-7000 Stuttgart, Germany
[6] Russian Acad Sci, Ural Branch, Ekaterinburg, Russia
[7] Delft Univ Technol, Delft Ctr Syst & Control, NL-2600 AA Delft, Netherlands
基金
美国国家科学基金会;
关键词
control theory; current key problems; recent achievements; trends; forecasts;
D O I
10.1016/j.arcontrol.2006.01.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Control theory deals with disciplines and methods leading to an automatic decision process in order to improve the performance of a control system. The evolution of control engineering is closely related to the evolution of the technology of sensors and actuators, and to the theoretical controller design methods and numerical techniques to be applied in real-time computing. New control disciplines, new development in the technologies will fertilize quite new control application fields. The status report gives an overview of the current key problems in control theory and design, evaluates the recent major accomplishments and forecasts some new areas. Challenges for future theoretical work are modelling, analysis and design of systems in quite new applications fields. New effective real-time optimal algorithms are needed for 2D and 3D pattern recognition. Design of very large distributed systems has presented a new challenge to control theory including robust control. Control over the networks becomes an important application area. Virtual reality is developing in impressive rate arising new theoretical problems. Distributed hybrid control systems involving extremely large number of interacting control loops, coordinating large number of autonomous agents, handling very large model uncertainties will be in the center of future research. New achievements in bioinformatics will result in new applications. All these challenges need development of new theories, analysis and design methods. (C) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:19 / 30
页数:12
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