Subject 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.
The subject is taught in programs
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
Teaching and learning methods
Lectures, tutorials, seminar.
Expected study results
- basic knowledge from intelligent control systems
- advanced approaches in modern control systems
- use of obtained knowledge at project work
Basic sources and literature
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.
Stay up to date
University of Ljubljana, Faculty of Electrical Engineering Tržaška cesta 25, 1000 Ljubljana