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Stability of Constrained Adaptive Model Predictive Control Algorithms

Title data

Jahn, Thomas U. ; Pannek, Jürgen:
Stability of Constrained Adaptive Model Predictive Control Algorithms.
Department of Mathematics, University of Bayreuth
Bayreuth , 2011 . - 6 p.

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Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
DFG Grant
Gr1569/12-1
Leopoldina Fellowship Programme
LPDS 2009-36

Abstract in another language

Recently, suboptimality estimates for model predictive controllers (MPC) have been derived for the case without additional stabilizing endpoint constraints or a Lyapunov function type endpoint weight. The proposed methods yield a posteriori and a priori estimates of the degree of suboptimality with respect to the infinite horizon optimal control and can be evaluated at runtime of the MPC algorithm. Our aim is to design automatic adaptation strategies of the optimization horizon in order to guarantee stability and a predefined degree of suboptimality for the closed loop solution. Here, we present a stability proof for an arbitrary adaptation scheme and state a simple shortening and prolongation strategy which can be used for adapting the optimization horizon.

Further data

Item Type: Preprint, postprint
Keywords: adaptive control; model predictive control; stability; suboptimality; sampled-data
control; sampled-data systems
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Advanced Fields > Nonlinear Dynamics
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 28 Mar 2015 22:00
Last Modified: 30 Mar 2015 07:10
URI: https://eref.uni-bayreuth.de/id/eprint/9473

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