Numerical evaluation of a robust self-triggered MPC algorithm

F.D. Brunner, W.P.M.H. Heemels, F. Allgöwer

Research output: Contribution to journalConference articleAcademicpeer-review

Abstract

We present numerical examples demonstrating the efficacy of a recently proposed self-triggered model predictive control scheme for disturbed linear discrete-time systems with hard constraints on the input and state. In order to reduce the amount of communication between the controller and the actuator, the control input is not re-computed at each point in time but only at certain sampling instances. These instances are determined in a self-triggered fashion in the sense that at every sampling instant the next sampling instant is computed as a function of the current system state. A compact set in the state space, whose size is a design parameter in the control scheme, is stabilized.

Original languageEnglish
Pages (from-to)151-156
Number of pages6
JournalIFAC-PapersOnLine
Volume49
Issue number22
DOIs
Publication statusPublished - 2016
Event6th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NECSYS 2016), September 8-9, 2016, Tokio, Japan - Tokio, Japan
Duration: 8 Sep 20169 Sep 2016

Keywords

  • predictive control
  • robustness
  • self-triggered control

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