EPN

ACIT4810 Advanced Methods in Modelling, Simulation, and Control Course description

Course name in Norwegian
Advanced Methods in Modelling, Simulation, and Control
Study programme
Master's Programme in Applied Computer and Information Technology
Weight
10.0 ECTS
Year of study
2020/2021
Curriculum
FALL 2020
Schedule
Course history

Introduction

The course covers several aspects related to modelling, simulation and control. The focus is on industrial applications, implementation, real life problems, and hands-on experience. The course gives an overview of state-of-the-art techniques, and provides students with tools to analyse and solve further industrial and research problems. Strong emphasis is given to the use of numerical simulation and scientific programming with Matlab/Simulink or similar. 

Recommended preliminary courses

Basic course in control, signals and systems. Basic understanding of matrix algebra, statistics, and programming using MATLAB or similar. 

Required preliminary courses

No formal requirements over and above the admission requirements. 

Learning outcomes

Upon successful completion of the course, the student: 

Knowledge: 

  • is familiar with data-driven dynamic modelling methods 
  • is familiar with state estimation techniques
  • is familiar with multivariable feedback control algorithms 
  • is familiar with predictive control algorithms 

Skills: 

  • can obtain dynamic models with data-driven dynamic modelling methods for a chosen industrial application 
  • can implement some techniques for state estimation
  • can implement some multivariable feedback control algorithms 
  • can implement some predictive control algorithms
  • can choose an advanced control algorithm suitable for a chosen industrial application. 
  • can implement and test the algorithm in a simulation environment. 

General competence: 

  • can evaluate different methods for advanced control for a chosen industrial application. 
  • can choose a suitable method, develop and implement it for a chosen industrial application. 

Content

  • Data driven dynamic modelling (system identification) 
  • State estimation
  • Multivariable control algorithms 
  • Predictive control algorithms 
  • Simulation and control of dynamic systems 

Teaching and learning methods

Weekly lectures and exercises, one project work in groups of between 2 - 5 students. Two guest lectures on selected topics given by experts from industry and academia.

Course requirements

The following required coursework must be approved before the student can take the exam:

Four individual compulsory assignments and one group project. The project groups will be between 2 and 5 students. The resulting project report is about 15-25 pages. 

Assessment

Exam autumn 2020 due to Covit-19:

3 days written digital home exam.

The exam grade can be appealed.

In the event of a resit or rescheduled exam, an oral examination may be used instead. In case an oral exam is used, the examination result cannot be appealed. 

[Exam earlier]:

Written exam, 3 hours. 

The exam grade can be appealed.

In the event of a resit or rescheduled exam, an oral examination may be used instead. In case an oral exam is used, the examination result cannot be appealed. 

Permitted exam materials and equipment

Aids autumn 2020:

All aids allowed

[Aids earlier:]

Open book exam, computer with MATLAB and Simulink. 

Grading scale

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail. 

Examiners

Two internal examiners. External examiner is used periodically. 

Course contact person

Associate Professor Tiina Komulainen