Numerical evaluation of a robust self-triggered MPC algorithm

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

Onderzoeksoutput: Bijdrage aan tijdschriftCongresartikelAcademicpeer review

Samenvatting

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.

Originele taal-2Engels
Pagina's (van-tot)151-156
Aantal pagina's6
TijdschriftIFAC-PapersOnLine
Volume49
Nummer van het tijdschrift22
DOI's
StatusGepubliceerd - 2016
Evenement6th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NECSYS 2016), September 8-9, 2016, Tokio, Japan - Tokio, Japan
Duur: 8 sep 20169 sep 2016

Vingerafdruk Duik in de onderzoeksthema's van 'Numerical evaluation of a robust self-triggered MPC algorithm'. Samen vormen ze een unieke vingerafdruk.

Citeer dit