Abstract
| Language | English |
|---|---|
| Title of host publication | Proceedings of the 2016 IEEE International Symposium on Intelligent Control (ISIC), 20-22 september 2016, Buenos Aires, Argentina |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 354-359 |
| DOIs | |
| State | Published - 2016 |
| Event | 2016 IEEE International Symposium on Intelligent Control - Buenos Aires, Argentina Duration: 20 Sep 2016 → 22 Sep 2016 |
Conference
| Conference | 2016 IEEE International Symposium on Intelligent Control |
|---|---|
| Abbreviated title | ISIC |
| Country | Argentina |
| City | Buenos Aires |
| Period | 20/09/16 → 22/09/16 |
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MPC for linear parameter-varying systems in input-output representation. / Hanema, J.; Tóth, R.; Lazar, M.; Abbas, H.S.
Proceedings of the 2016 IEEE International Symposium on Intelligent Control (ISIC), 20-22 september 2016, Buenos Aires, Argentina. Piscataway : Institute of Electrical and Electronics Engineers, 2016. p. 354-359.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - MPC for linear parameter-varying systems in input-output representation
AU - Hanema,J.
AU - Tóth,R.
AU - Lazar,M.
AU - Abbas,H.S.
PY - 2016
Y1 - 2016
N2 - In this paper, we propose a method for model predictive control of linear parameter-varying (LPV) systems described in an input-output (IO) representation and subject to input- and output constraints. By assuming exact knowledge of the future trajectory of the scheduling variable, the on-line computations reduce to the solution of a nominal predictive control problem. An incremental non-minimal state-space representation is used as a prediction model, giving a controller with integral action suitable for tracking piecewise-constant reference signals. Closed-loop asymptotic stability is guaranteed by a terminal cost and terminal set constraint, and the computation of an ellipsoidal terminal set is discussed. Numerical examples demonstrate the properties of the proposed approach. When exact future knowledge of the scheduling variable is not available, we argue and show that good practical performance can be obtained by a scheduling prediction strategy.
AB - In this paper, we propose a method for model predictive control of linear parameter-varying (LPV) systems described in an input-output (IO) representation and subject to input- and output constraints. By assuming exact knowledge of the future trajectory of the scheduling variable, the on-line computations reduce to the solution of a nominal predictive control problem. An incremental non-minimal state-space representation is used as a prediction model, giving a controller with integral action suitable for tracking piecewise-constant reference signals. Closed-loop asymptotic stability is guaranteed by a terminal cost and terminal set constraint, and the computation of an ellipsoidal terminal set is discussed. Numerical examples demonstrate the properties of the proposed approach. When exact future knowledge of the scheduling variable is not available, we argue and show that good practical performance can be obtained by a scheduling prediction strategy.
U2 - 10.1109/ISIC.2016.7579987
DO - 10.1109/ISIC.2016.7579987
M3 - Conference contribution
SP - 354
EP - 359
BT - Proceedings of the 2016 IEEE International Symposium on Intelligent Control (ISIC), 20-22 september 2016, Buenos Aires, Argentina
PB - Institute of Electrical and Electronics Engineers
CY - Piscataway
ER -