End-point parametrization and guaranteed stability for a model predictive control scheme

Siep Weiland; Antonie Arij Stoorvogel; Andrei A. Tiagounov

doi:10.1109/.2001.980972

End-point parametrization and guaranteed stability for a model predictive control scheme

Siep Weiland, Antonie Arij Stoorvogel, Andrei A. Tiagounov

Research output: Contribution to conference › Paper › Academic › peer-review

4 Citations (Scopus)

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Abstract

In this paper we consider the closed-loop asymptotic stability of the model predictive control scheme which involves the minimization of a quadratic criterion with a varying weight on the end-point state. In particular, we investigate the stability properties of the (MPC-) controlled system as function of the end-point penalty and provide a useful parametrization of the class of end-point penalties for which stability of the controlled system can be guaranteed. The results are successfully applied for the implementation of an MPC controller of a binary distillation process

Original language	Undefined
Pages	4832-4837
Number of pages	6
DOIs	https://doi.org/10.1109/.2001.980972
Publication status	Published - Dec 2001
Event	40th IEEE Conference on Decision and Control, CDC 2001 - Hyatt Regency Grand Cypress, Orlando, United States Duration: 4 Dec 2001 → 7 Dec 2001

Conference

Conference	40th IEEE Conference on Decision and Control, CDC 2001
Abbreviated title	CDC
Country/Territory	United States
City	Orlando
Period	4/12/01 → 7/12/01

Keywords

IR-69041
EWI-16645

Access to Document

10.1109/.2001.980972

Cite this

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title = "End-point parametrization and guaranteed stability for a model predictive control scheme",

abstract = "In this paper we consider the closed-loop asymptotic stability of the model predictive control scheme which involves the minimization of a quadratic criterion with a varying weight on the end-point state. In particular, we investigate the stability properties of the (MPC-) controlled system as function of the end-point penalty and provide a useful parametrization of the class of end-point penalties for which stability of the controlled system can be guaranteed. The results are successfully applied for the implementation of an MPC controller of a binary distillation process",

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AB - In this paper we consider the closed-loop asymptotic stability of the model predictive control scheme which involves the minimization of a quadratic criterion with a varying weight on the end-point state. In particular, we investigate the stability properties of the (MPC-) controlled system as function of the end-point penalty and provide a useful parametrization of the class of end-point penalties for which stability of the controlled system can be guaranteed. The results are successfully applied for the implementation of an MPC controller of a binary distillation process

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