Improved robust model predictive control with structural uncertainty

Le Feng, Jianliang Wang, Engkee Poh, Fang Liao

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a dilation of the LMI characterization is presented to address constrained robust model predictive control (MPC) for a class of uncertain linear systems with structured time-varying uncertainties. The uncertainty is described in linear fractional transformation (LFT) form. It is known such uncertain systems are popularly used in nonlinear system modeling and many other circumstances. By using parameter dependent Lyapunov functions, the designing conservativeness is reduced compared with some well-known MPC approaches. The proposed approach is applied to a two-mass-spring benchmark system to demonstrate the merits.

Original languageEnglish
Title of host publication9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 - Singapore, Singapore
Duration: 5 Dec 20068 Dec 2006

Publication series

Name9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06

Conference

Conference9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
Country/TerritorySingapore
CitySingapore
Period5/12/068/12/06

Keywords

  • Linear matrix inequalities
  • Model predictive control
  • Parameter dependent lyapunov function
  • Structured uncertainty

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

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