Slovensko

Advanced Control Design Methods

Higher education teachers: Atanasijević-Kunc Maja



Subject description

Prerequisits:

  • Inscription to 2nd cycle masters study programme in Electrical Engineering

Content (Syllabus outline):

  • introduction , definitions of important concepts, identification of needs for the extension of control design approaches;
  • large-scale systems, multivariable systems, phase-nonminimal systems, systems with a dead time, nonlinear systems, difficult-controlable systems;
  • presentation and analysis of complex systems in the time and frequency domains, with emphasis on parallelisms and differences to the conventional presentations;
  • control design quality criteria in time and frequency domains and concepts of optimality (classical approaches and problems in complex systems, which are reflected in the corresponding definition of fitness function and convergence of classical methods, the usage of evolutionary computation and some relative advantages );
  • introduction of control design approaches that rely on direct extensions of classical methods (hierarchical and decentralized control, tuning, decoupling, INA , IMC , pole placement using dyadic contoller structures);
  • adaptive controllers and some of design approaches;
  • the use of evolutionary computation methods in the design of complex systems with emphasis on the effective combination of the presented algorithms;
  • concepts of expert systems in control design;
  • usage of program Matlab with corresponding Toolboxes.

Objectives and competences:

  • to classify complex controlled systems,
  • to describe analytical methods which explain important properties of such systems,
  • to present parallelisms and necessary extensions in relation to classical control design approaches,
  • to present some of efficiant control design approaches with emphasis on different aspects of optimality,
  • to present some of Matlab toolboxes and their usefulness in support of the issues being discussed.

Intended learning outcomes:

Gained knowledge will enable:

  • systems' recognition that are complex and difficult to control;
  • the use of control algorithms which are suitable for such systems;
  • their implementation in the form of expert system;
  • controllers’ implementation in closed-loop operation of real complex systems;
  • quantitative and qualitative evaluation of closed-loop system design.

Learning and teaching methods:

  • Lecture,
  • laboratory exercises,
  • project work.





Study materials

  1. M. Atanasijević-Kunc, Napredne metode vodenja sistemov, Študijsko gradivo, Fakulteta za elektrotehniko, Univerza v Ljubljani, 2013.
  2. KARBA, Rihard, ATANASIJEVIĆ-KUNC, Maja. Multivariabilni sistemi. 1. izd. Ljubljana: Založba FE in FRI, 2010. IV, 199 str., ilustr. ISBN 978-961-243-161-7. [COBISS.SI-ID 253526784] R. Karba, Multivariabilni sistemi, Univerza v Ljubljani, Založba FE in FRI, 2008.
  3. S. Skogestad, I. Postlethwaite, Multivariable Feedback Control, Analysis and Design, John Wiley and Sons Ltd, Chichester, 1996.
  4. M. Morari, E. Zafiriou, Robust Process Control, Prentice-Hall, Inc. 1989.
  5. J.M. Maciejowski, Multivariable Feedback Design, Addison-Wesley Publishing Company, 1989.
  6. M. Jamshidi, Large-Scale Systems: Modeling, Control and Fuzzy Logic, Prentice Hall PRT, New Jersey, 1997.
  7. P. Albertos, A. Sala, Multivariable Control Systems, An Engineering Approach, Springer-Verlag, London, 2004.
  8. S. E. Lyshevski, Control Systems Theory with Engineering Applications, Birkhauser, Boston, 2001.
  9. A. Tewari, Modern Control Design with Matlab and Simulink, John Wiley & Sons Ltd, Chichester, 2002.
  10. D.B. Fogel, Evolutionary Computation, Toward a New Philosophy of Machine Intelligence, IEEE Press Series on Computational Intelligence, 2006.
  11. Astrom, Wittenmark, Adaptive control, Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 1994.







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