A second order cone formulation of min-max MPC with zone control for LPV systems

Alejandro Marquez-Ruiz, Julian Patino, Leyla Ozkan, Jairo Espinosa

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper proposes a Second Order Cone Formulation of min-max MPC with zone control for LPV Systems. The min-max strategy in model predictive control (MPC) allows computing the optimal control actions where the worst-case performance to the system uncertainties is assumed. Zone control is used instead of a reference trajectory, as the MPC performance for several complex systems with uncertainty improves with a control range rather than a reference path. Unfortunately, min-max formulations of predictive controllers often produce intractable optimization problems as the number of states, inputs, and outputs of the system increase. Hence, in this paper uncertainty is treated in such a way that the min-max optimization problem can be solved through a second-order cone programming problem. This equivalent solution has a polynomial complexity for the min-max solution, a fact that constitutes the most remarkable feature of the proposed formulation. Performance of the method is verified in simulation through the application on a stirred tank reactor (CSTR) system.

Original languageEnglish
Title of host publication4th IEEE Colombian Conference on Automatic Control
Subtitle of host publicationAutomatic Control as Key Support of Industrial Productivity, CCAC 2019 - Proceedings
EditorsJose Garcia-Tirado, Diego Munoz-Durango, Hernan Alvarez, Hector Botero-Castro
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-5386-6962-4
DOIs
Publication statusPublished - Oct 2019
Event4th IEEE Colombian Conference on Automatic Control, CCAC 2019 - Medellin, Colombia
Duration: 15 Oct 201918 Oct 2019

Conference

Conference4th IEEE Colombian Conference on Automatic Control, CCAC 2019
CountryColombia
CityMedellin
Period15/10/1918/10/19

Keywords

  • LPV systems
  • Model predictive control
  • Robust Quadratic Programming
  • Zone control

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