Advanced intelligent control systems

Course description

Introduction to intelligent systems. Basic principles of fuzzy and neural systems in control. Basic principles of adaptive systems: direct and indirect approaches, self-tuning controllers, gain-scheduling controlles. Basic principles and methods of predictive control. Fuzzy model based predictive and adaptive control. Examples of intelligent control in advanced technological processes.

Course is carried out on study programme

Objectives and competences

  • to present the problems of intelligent control systems
  • to present the methods of predictive and adaptive control
  • to present the implementation problems of advanced control systems
  • to present the tools for design of advanced control systems

Learning and teaching methods

Lectures, tutorials, seminar.

Intended learning outcomes

  • basic knowledge from intelligent  control systems
  • advanced approaches in modern control systems
  • use of obtained knowledge at project work

Reference nosilca

Nunez A, Schutter B de, Saez D, Škrjanc I (2014) Hybrid-fuzzy modeling and identification. Applied soft computing 17: 67-77.

Škrjanc I (2011) Fuzzy confidence interval for pH titration curve. Applied mathematical modelling 35: 4083-4090.

Hartmann B, Baenfer O, Nelles O, Sodja A, Teslić L, Škrjanc I (2011) Supervised hierarchical clustering in fuzzy model identification. IEEE transactions on fuzzy systems 19, 6: 1163-1176.

Dovžan D, Škrjanc I (2010) Predictive functional control based on an adaptive fuzzy model of a hybrid semi-batch reactor. Control engineering practice 18, 8: 979-989.

Škrjanc I (2009) Confidence interval of fuzzy models: an example using a waste-water treatment plant. Chemometrics and Intelligent Laboratory Systems 96, 2: 182-187.  

Study materials

Nelles O (2000) Nonlinear System Identification, Springer.

Karer G, Škrjanc I (2013) Predictive Approaches in Control of Complex Systems, Springer.

Škrjanc I (2014) Inteligentne metode v identifikaciji sistemov, skripta v pripravi.

Bodi na tekočem

Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana

E:  dekanat@fe.uni-lj.si T:  01 4768 411