Numerical evaluation of a robust self-triggered MPC algorithm

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

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


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
Issue number22
Publication statusPublished - 2016
Event6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2016 - Tokio, Japan
Duration: 8 Sept 20169 Sept 2016
Conference number: 6


  • predictive control
  • robustness
  • self-triggered control


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