Coursebooks 2017-2018

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Model predictive control

ME-425

Lecturer(s) :

Jones Colin Neil

Language:

English

Summary

Provide an introduction to the theory and practice of Model Predictive Control (MPC). Main benefits of MPC: flexible specification of time-domain objectives, performance optimization of highly complex multivariable systems and ability to explicitly enforce constraints on system behavior.

Content

Keywords

Multi-variable control, Constrained systems, Model-based Control, Optimization

Learning Prerequisites

Required courses

Recommended courses

Important concepts to start the course

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Lectures, exercises and course project

Expected student activities

Assessment methods

Supervision

Office hours No
Assistants Yes
Forum No

Resources

Bibliography

All material can be downloaded from the moodle site. Printed versions of the lecture notes can be ordered.

Websites
Moodle Link

In the programs

    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Energy Management and Sustainability, 2017-2018, Master semester 2
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Energy Management and Sustainability, 2017-2018, Master semester 4
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      3
    • Subject examined
      Model predictive control
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German