Knowledge-Based Control Systems (SC4081)

Short Description

Theory and applications of knowledge-based and intelligent control systems. The course is motivated by the following topics: Fuzzy sets and systems, Fuzzy clustering for data analysis and system identification, Knowledge based fuzzy control, Artificial neural networks, Control based on fuzzy and neural models, Reinforcement learning, Applications.

Prerequisites & Target Group

B.Sc. in Electrical Engineering, mechanical Engineering, Computer Science, Applied Mathematics (or similar) with emphasis on control-related courses


Topics covered in this course include:

  • Introduction

  • Fuzzy sets and systems

  • Data analysis and system identification

  • Knowledge based fuzzy control

  • Artificial neural networks

  • Control based on fuzzy and neural models

  • Reinforcement learning

  • Applications

Study load hours (112 hours total per student)

  • 20 hours: 10 lectures

  • 25 hours: literature assignment

  • 25 hours: Matlab assignment

  • 10 hours: self-study during the 5 lecture weeks

  • 22 hours: study for the exam

  • 7 hours: symposium

  • 3 hours: exam


The exam grade counts for 60% of the final grade of the course. The solutions to the assignments (see Assignments) count for the remaining 40%: Matlab assignment 20% and Literature assignment 20%. Each activity must be approved separately to obtain the credits of this course.

Note: If you approved in previous years the exam, and/or the Matlab assignment, and/or the Literature assignment, the grade you obtained is automatically consider for this year, so you don't have to approve the activities again. Only if you want you get a better grade.