Stabilization conditions for model predictive control of constrained PWA systems

M. Lazar; W.P.M.H. Heemels; S. Weiland; A. Bemporad

doi:10.1109/CDC.2004.1429508

Stabilization conditions for model predictive control of constrained PWA systems

M. Lazar, W.P.M.H. Heemels, S. Weiland, A. Bemporad

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

30 Citaten (Scopus)

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Model Predictive Control (MPC) has recently been applied to several relevant classes of hybrid systems with promising results. These developments generated an increasing interest towards issues such as stability and computational problems that arise in hybrid MPC. Stability aspects have been addressed only marginally. In this paper we present an extension of the terminal cost and constraint set method for guaranteeing stability in MPC to the class of constrained piecewise affine systems. Semidefinite programming is used to calculate the employed terminal weight matrix that ensures stability for quadratic cost based MPC. A procedure for computing a robust positively invariant set for piecewise linear systems is also developed. The implementation of the proposed method is illustrated by an example.

Originele taal-2	Engels
Titel	43rd IEEE Conference on Decision and Control (CDC)
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	4595-4600
Aantal pagina's	6
ISBN van geprinte versie	0-7803-8682-5
DOI's	https://doi.org/10.1109/CDC.2004.1429508
Status	Gepubliceerd - 1 dec. 2004
Evenement	43rd IEEE Conference on Decision and Control (CDC 2004) - "Atlantis", Nassau, Bahama's Duur: 14 dec. 2004 → 17 dec. 2004 Congresnummer: 43 http://cdc2004.ieeecss.org/

Congres

Congres	43rd IEEE Conference on Decision and Control (CDC 2004)
Verkorte titel	CDC 2004
Land/Regio	Bahama's
Stad	Nassau
Periode	14/12/04 → 17/12/04
Ander	IEEE Conference on Decision and Control
Internet adres	http://cdc2004.ieeecss.org/

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title = "Stabilization conditions for model predictive control of constrained PWA systems",

abstract = "Model Predictive Control (MPC) has recently been applied to several relevant classes of hybrid systems with promising results. These developments generated an increasing interest towards issues such as stability and computational problems that arise in hybrid MPC. Stability aspects have been addressed only marginally. In this paper we present an extension of the terminal cost and constraint set method for guaranteeing stability in MPC to the class of constrained piecewise affine systems. Semidefinite programming is used to calculate the employed terminal weight matrix that ensures stability for quadratic cost based MPC. A procedure for computing a robust positively invariant set for piecewise linear systems is also developed. The implementation of the proposed method is illustrated by an example.",

keywords = "Linear matrix inequalities, Model predictive control, Piecewise affine systems, Positively invariant sets, Stability",

author = "M. Lazar and W.P.M.H. Heemels and S. Weiland and A. Bemporad",

year = "2004",

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doi = "10.1109/CDC.2004.1429508",

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note = "43rd IEEE Conference on Decision and Control (CDC 2004), CDC 2004 ; Conference date: 14-12-2004 Through 17-12-2004",

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Lazar, M , Heemels, WPMH , Weiland, S & Bemporad, A 2004, Stabilization conditions for model predictive control of constrained PWA systems. in 43rd IEEE Conference on Decision and Control (CDC). Institute of Electrical and Electronics Engineers, Piscataway, blz. 4595-4600, 43rd IEEE Conference on Decision and Control (CDC 2004), Nassau, Bahama's, 14/12/04. https://doi.org/10.1109/CDC.2004.1429508

Stabilization conditions for model predictive control of constrained PWA systems. / Lazar, M.; Heemels, W.P.M.H.; Weiland, S. et al.
43rd IEEE Conference on Decision and Control (CDC). Piscataway: Institute of Electrical and Electronics Engineers, 2004. blz. 4595-4600.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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T1 - Stabilization conditions for model predictive control of constrained PWA systems

AU - Lazar, M.

AU - Heemels, W.P.M.H.

AU - Weiland, S.

AU - Bemporad, A.

N1 - Conference code: 43

PY - 2004/12/1

Y1 - 2004/12/1

N2 - Model Predictive Control (MPC) has recently been applied to several relevant classes of hybrid systems with promising results. These developments generated an increasing interest towards issues such as stability and computational problems that arise in hybrid MPC. Stability aspects have been addressed only marginally. In this paper we present an extension of the terminal cost and constraint set method for guaranteeing stability in MPC to the class of constrained piecewise affine systems. Semidefinite programming is used to calculate the employed terminal weight matrix that ensures stability for quadratic cost based MPC. A procedure for computing a robust positively invariant set for piecewise linear systems is also developed. The implementation of the proposed method is illustrated by an example.

AB - Model Predictive Control (MPC) has recently been applied to several relevant classes of hybrid systems with promising results. These developments generated an increasing interest towards issues such as stability and computational problems that arise in hybrid MPC. Stability aspects have been addressed only marginally. In this paper we present an extension of the terminal cost and constraint set method for guaranteeing stability in MPC to the class of constrained piecewise affine systems. Semidefinite programming is used to calculate the employed terminal weight matrix that ensures stability for quadratic cost based MPC. A procedure for computing a robust positively invariant set for piecewise linear systems is also developed. The implementation of the proposed method is illustrated by an example.

KW - Linear matrix inequalities

KW - Model predictive control

KW - Piecewise affine systems

KW - Positively invariant sets

KW - Stability

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BT - 43rd IEEE Conference on Decision and Control (CDC)

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Stabilization conditions for model predictive control of constrained PWA systems

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