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Model Predictive approaches for Active Surge Control in Centrifugal Compressors


G. Torrisi, S. Grammatico, Andrea Cortinovis, Mehmet Mercangoez, M. Morari, R. S. Smith

IEEE Transactions on Control Systems Technology, (in press)

Model Predictive Control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics, to address process and anti-surge 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) is also discussed, that yields a closed-loop performance comparable to the full nonlinear MPC. All of the controllers considered are tested in simulations that emulate a realistic test bench and their computational time is assessed on an industrial PLC. Their performance is compared to 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.


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% Autogenerated BibTeX entry
@Article { TorEtal:2016:IFA_5512,
    author={G. Torrisi and S. Grammatico and Andrea Cortinovis and Mehmet
	  Mercangoez and M. Morari and R. S. Smith},
    title={{Model Predictive approaches for Active Surge Control in
	  Centrifugal Compressors}},
    journal={IEEE Transactions on Control Systems Technology},
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