Model predictive control approaches for centrifugal compression systems

G. Torrisi; S. Grammatico; M. Morari; R. Smith

doi:10.1109/CDC.2015.7402893

Model predictive control approaches for centrifugal compression systems

G. Torrisi, S. Grammatico, M. Morari, R. Smith

Control Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

3 Citations (Scopus)

2 Downloads (Pure)

Abstract

Model Predictive Control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics. We consider the torque provided by an external drive and a recycle valve as control actuators for the system. Closed-loop stability in the presence of control constraints is studied via the contractive control Lyapunov function method. We solve the nonlinear MPC problem to assess a performance benchmark, and then design a Sequential Quadratic Programming (SQP) MPC approach which is computationally affordable. We show in several numerical simulations based on a realistic centrifugal compressor case study that the SQP MPC technique outperforms the classic linearized MPC and performs similarly to the nonlinear MPC approach.

Original language	English
Title of host publication	54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	4320-4325
Number of pages	6
ISBN (Electronic)	978-1-4799-7885-4
ISBN (Print)	978-1-4799-7884-7
DOIs	https://doi.org/10.1109/CDC.2015.7402893
Publication status	Published - 15 Dec 2015
Event	54th IEEE Conference on Decision and Control (CDC 2015) - "Osaka International Convention Center", Osaka, Japan Duration: 15 Dec 2015 → 18 Dec 2015 Conference number: 54 http://www.cdc2015.ctrl.titech.ac.jp/

Conference

Conference	54th IEEE Conference on Decision and Control (CDC 2015)
Abbreviated title	CDC 2015
Country/Territory	Japan
City	Osaka
Period	15/12/15 → 18/12/15
Internet address	http://www.cdc2015.ctrl.titech.ac.jp/

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10.1109/CDC.2015.7402893

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title = "Model predictive control approaches for centrifugal compression systems",

abstract = "Model Predictive Control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics. We consider the torque provided by an external drive and a recycle valve as control actuators for the system. Closed-loop stability in the presence of control constraints is studied via the contractive control Lyapunov function method. We solve the nonlinear MPC problem to assess a performance benchmark, and then design a Sequential Quadratic Programming (SQP) MPC approach which is computationally affordable. We show in several numerical simulations based on a realistic centrifugal compressor case study that the SQP MPC technique outperforms the classic linearized MPC and performs similarly to the nonlinear MPC approach.",

author = "G. Torrisi and S. Grammatico and M. Morari and R. Smith",

year = "2015",

month = dec,

day = "15",

doi = "10.1109/CDC.2015.7402893",

language = "English",

isbn = "978-1-4799-7884-7",

pages = "4320--4325",

booktitle = "54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "54th IEEE Conference on Decision and Control (CDC 2015), CDC 2015 ; Conference date: 15-12-2015 Through 18-12-2015",

url = "http://www.cdc2015.ctrl.titech.ac.jp/",

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Torrisi, G, Grammatico, S, Morari, M & Smith, R 2015, Model predictive control approaches for centrifugal compression systems. in 54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan. Institute of Electrical and Electronics Engineers, Piscataway, pp. 4320-4325, 54th IEEE Conference on Decision and Control (CDC 2015), Osaka, Japan, 15/12/15. https://doi.org/10.1109/CDC.2015.7402893

Model predictive control approaches for centrifugal compression systems. / Torrisi, G.; Grammatico, S.; Morari, M. et al.

54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan. Piscataway : Institute of Electrical and Electronics Engineers, 2015. p. 4320-4325.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Model predictive control approaches for centrifugal compression systems

AU - Torrisi, G.

AU - Grammatico, S.

AU - Morari, M.

AU - Smith, R.

N1 - Conference code: 54

PY - 2015/12/15

Y1 - 2015/12/15

N2 - Model Predictive Control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics. We consider the torque provided by an external drive and a recycle valve as control actuators for the system. Closed-loop stability in the presence of control constraints is studied via the contractive control Lyapunov function method. We solve the nonlinear MPC problem to assess a performance benchmark, and then design a Sequential Quadratic Programming (SQP) MPC approach which is computationally affordable. We show in several numerical simulations based on a realistic centrifugal compressor case study that the SQP MPC technique outperforms the classic linearized MPC and performs similarly to the nonlinear MPC approach.

AB - Model Predictive Control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics. We consider the torque provided by an external drive and a recycle valve as control actuators for the system. Closed-loop stability in the presence of control constraints is studied via the contractive control Lyapunov function method. We solve the nonlinear MPC problem to assess a performance benchmark, and then design a Sequential Quadratic Programming (SQP) MPC approach which is computationally affordable. We show in several numerical simulations based on a realistic centrifugal compressor case study that the SQP MPC technique outperforms the classic linearized MPC and performs similarly to the nonlinear MPC approach.

U2 - 10.1109/CDC.2015.7402893

DO - 10.1109/CDC.2015.7402893

M3 - Conference contribution

SN - 978-1-4799-7884-7

SP - 4320

EP - 4325

BT - 54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 54th IEEE Conference on Decision and Control (CDC 2015)

Y2 - 15 December 2015 through 18 December 2015

ER -

Model predictive control approaches for centrifugal compression systems

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