Model predictive control for embedded applications

Panagiotis Vouzis; Leonidas G. Bleris; Mark Arnold; Mayuresh V. Kothare

Model predictive control for embedded applications

Panagiotis Vouzis, Leonidas G. Bleris, Mark Arnold, Mayuresh V. Kothare

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Model predictive control (MPC) refers to a family of control algorithms that compute a sequence of manipulated variables by solving an optimization problem, incorporating explicit knowledge of the plant model and incorporating feedback information. Applications that can readily benefit from embedded MPC chip range from automotive and avionics to microchemical systems, drug-delivery systems, and fuel cells. An overview of the platforms that have appeared in the literature for embedding MPC in applications with small physical size, such as fuel processors is presented. This is an abstract of a paper presented at the AIChE Annual Meeting (San Francisco, CA 11/12-17/2006).

Original language	English (US)
Title of host publication	AIChE Annual Meeting, Conference Proceedings
State	Published - 2006
Externally published	Yes
Event	2006 AIChE Annual Meeting - San Francisco, CA, United States Duration: Nov 12 2006 → Nov 17 2006

Other

Other	2006 AIChE Annual Meeting
Country/Territory	United States
City	San Francisco, CA
Period	11/12/06 → 11/17/06

ASJC Scopus subject areas

Biotechnology
General Chemical Engineering
Bioengineering
Safety, Risk, Reliability and Quality

Cite this

@inproceedings{3b6eca9353444212a491b5d39bdd07eb,

title = "Model predictive control for embedded applications",

abstract = "Model predictive control (MPC) refers to a family of control algorithms that compute a sequence of manipulated variables by solving an optimization problem, incorporating explicit knowledge of the plant model and incorporating feedback information. Applications that can readily benefit from embedded MPC chip range from automotive and avionics to microchemical systems, drug-delivery systems, and fuel cells. An overview of the platforms that have appeared in the literature for embedding MPC in applications with small physical size, such as fuel processors is presented. This is an abstract of a paper presented at the AIChE Annual Meeting (San Francisco, CA 11/12-17/2006).",

author = "Panagiotis Vouzis and Bleris, {Leonidas G.} and Mark Arnold and Kothare, {Mayuresh V.}",

year = "2006",

language = "English (US)",

isbn = "081691012X",

booktitle = "AIChE Annual Meeting, Conference Proceedings",

note = "2006 AIChE Annual Meeting ; Conference date: 12-11-2006 Through 17-11-2006",

}

TY - GEN

T1 - Model predictive control for embedded applications

AU - Vouzis, Panagiotis

AU - Bleris, Leonidas G.

AU - Arnold, Mark

AU - Kothare, Mayuresh V.

PY - 2006

Y1 - 2006

N2 - Model predictive control (MPC) refers to a family of control algorithms that compute a sequence of manipulated variables by solving an optimization problem, incorporating explicit knowledge of the plant model and incorporating feedback information. Applications that can readily benefit from embedded MPC chip range from automotive and avionics to microchemical systems, drug-delivery systems, and fuel cells. An overview of the platforms that have appeared in the literature for embedding MPC in applications with small physical size, such as fuel processors is presented. This is an abstract of a paper presented at the AIChE Annual Meeting (San Francisco, CA 11/12-17/2006).

AB - Model predictive control (MPC) refers to a family of control algorithms that compute a sequence of manipulated variables by solving an optimization problem, incorporating explicit knowledge of the plant model and incorporating feedback information. Applications that can readily benefit from embedded MPC chip range from automotive and avionics to microchemical systems, drug-delivery systems, and fuel cells. An overview of the platforms that have appeared in the literature for embedding MPC in applications with small physical size, such as fuel processors is presented. This is an abstract of a paper presented at the AIChE Annual Meeting (San Francisco, CA 11/12-17/2006).

UR - http://www.scopus.com/inward/record.url?scp=58049111509&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=58049111509&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:58049111509

SN - 081691012X

SN - 9780816910120

BT - AIChE Annual Meeting, Conference Proceedings

T2 - 2006 AIChE Annual Meeting

Y2 - 12 November 2006 through 17 November 2006

ER -

Model predictive control for embedded applications

Abstract

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ASJC Scopus subject areas

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