Model predictive control approaches for centrifugal compression systems

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
2 Downloads (Pure)


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 languageEnglish
Title of host publication54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-4799-7885-4
ISBN (Print)978-1-4799-7884-7
Publication statusPublished - 15 Dec 2015
Event54th IEEE Conference on Decision and Control (CDC 2015) - "Osaka International Convention Center", Osaka, Japan
Duration: 15 Dec 201518 Dec 2015
Conference number: 54


Conference54th IEEE Conference on Decision and Control (CDC 2015)
Abbreviated titleCDC 2015
Internet address


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