Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. A Multidisciplinary Approach for Model Predictive Control Education: A Lego Mindstorms NXT-based Framework
 
research article

A Multidisciplinary Approach for Model Predictive Control Education: A Lego Mindstorms NXT-based Framework

Canale, Massimo
•
Casale-Brunet, Simone
2014
International Journal Of Control Automation And Systems

This work introduces an educational framework based on the Lego Mindstorms NXT robotic platform used to outline both the theoretical and practical aspects of the Model Predictive Control (MPC) theory. The framework has been developed in the widely used MatLab/Simulink environment. A two-wheeled inverted pendulum is considered as hands-on experimental scenario. For such a system, starting from its mathematical modeling, an established design methodology is presented aiming to outline step-by-step the predictive controller implementation on a low power architecture. This methodology stress the design of a non-linear MPC controller on a low power embedded system, pruning the designer to deal with hard real time constraints without impacting the overall design requirements. The effectiveness of this multidisciplinary approach is shown through this presentation and demonstrated with experimental results.

  • Details
  • Metrics
Type
research article
DOI
10.1007/s12555-013-0282-7
Web of Science ID

WOS:000341491600014

Author(s)
Canale, Massimo
Casale-Brunet, Simone
Date Issued

2014

Publisher

Springer Verlag

Published in
International Journal Of Control Automation And Systems
Volume

12

Issue

5

Start page

1030

End page

1039

Subjects

Control education

•

mechatronics

•

model predictive control

•

nonlinear systems

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SCI-STI-MM  
Available on Infoscience
October 23, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/107629
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés