Advanced Control Design Methods

Subject description

Introduction, definitions of important concepts, identification of the needs for the extension of control design approaches

Large-scale systems, multivariable systems, phase-nonminimal systems, systems with a dead time, nonlinear systems

Presentation and analysis of complex systems in time and frequency domain, with emphasis on parallelisms and differences to the conventional presentations

Control design quality criteria in time and frequency domain 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

Usage 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

Illustrative examples of control design of complex laboratory pilot plants.

The subject is taught in programs

Objectives and competences

Course goals are:

  • 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,
  • to acquaint students with appropriate literature search, research work, and appropriate written and oral presentation of design results.

Teaching and learning methods

Lectures, homeworks, laboratory exercises, seminar and project work

Expected study results

Gained knowledge will enable:

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

Basic sources and literature

  1. ATANASIJEVIĆ-KUNC, Maja. Napredne metode vodenja sistemov, Študijsko gradivo. Fakulteta za elektrotehniko, Univerza v Ljubljani, 2016.
  2. KARBA, Rihard, ATANASIJEVIĆ-KUNC, Maja. Multivariabilni sistemi. Fakulteta za elektrotehniko, Univerza v Ljubljani, Založba FE in FRI, 2010.
  3. ATANASIJEVIĆ-KUNC, Maja. Multivariabilni sistemi: Zbirka kompleksnejših problemov. Fakulteta za elektrotehniko, Univerza v Ljubljani, Založba FE in FRI, 2004.
  4. ATANASIJEVIĆ-KUNC, Maja. Multivariabilni sistemi: Predstavitev, analiza in načrtovanje skozi primere. Fakulteta za elektrotehniko, Založba FE in FRI, 2003.
  5. SKOGESTAD, Sigurd. POSTLETHWAITE, Ian. Multivariable Feedback Control, Analysis and Design, John Wiley and Sons, Chichester, 1996.
  6. MORARI, M., and ZAFIRIOU, E.. Robust Process Control, Prentice-Hall, 1989.
  7. JAMSHIDI, M.. Large-Scale Systems: Modeling, Control and Fuzzy Logic, Prentice Hall PRT, New Jersey, 199
  8. LYSHEVSKI, S. E.. Control Systems Theory with Engineering Applications, Birkhauser, Boston, 2001.
  9. ÅSTRÖM, Karl Johan, WITTENMARK, Björn. Adaptive control, Addison-Wesley Longman Publishing Co., Boston, MA, USA, 1994.
  10. ÅSTRÖM, Karl Johan, HÄGGLUND, Tore. Advanced PID Control. With. ISA, 2005.
  11. TEWARI, A.. Modern Control Design with Matlab and Simulink, John Wiley & Sons Ltd, Chichester, 2002.

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