Model predictive approaches for active surge control in centrifugal compressors

G. Torrisi, S. Grammatico, A. Cortinovis, M. Mercangoz, M. Morari, R.S. Smith

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)

Abstract

Model predictive control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics, to address process and antisurge control for reaching the desired pressure ratio and surge distance. We consider a contractive nonlinear MPC formulation that ensures asymptotic stability of the closed-loop system by imposing the decrease of a quadratic Lyapunov function via an additional constraint. We discuss recursive feasibility and estimate the region of attraction via numerical methods. We also consider alternative MPC formulations, including offset-free linear and nonlinear MPC to handle the effects of disturbances and unmodeled dynamics. The computational efficiency of an approximation based on sequential quadratic programming (SQP), that yields a closed-loop performance comparable to the full nonlinear MPC is also discussed. All of the controllers considered are tested in simulations that emulate a realistic test bench and their computational time is assessed on an industrial Programmable Logic Controller (PLC). Their performance is compared with standard industrial control in nominal and perturbed cases replicating the typical and critical disturbances and model mismatches. The numerical results show that the SQP and nonlinear MPC methods outperform the other controllers in the considered scenarios, based on closed-loop performance metrics for the surge margin, the reference tracking accuracy, and the system actuation, without significantly increasing the computational time.

Original languageEnglish
Article number7833116
Pages (from-to)1947-1960
Number of pages14
JournalIEEE Transactions on Control Systems Technology
Volume25
Issue number6
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • Compressors
  • drives
  • industrial control
  • predictive control
  • stability analysis

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