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Model Predictive Control approaches for Centrifugal Compression Systems


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

Conference on Decision and Control (CDC), Osaka, Japan, pp. 4320 - 4325

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 approach. 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.


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% Autogenerated BibTeX entry
@InProceedings { TorEtal:2015:IFA_5221,
    author={G. Torrisi and S. Grammatico and M. Morari and R. S. Smith},
    title={{Model Predictive Control approaches for Centrifugal
	  Compression Systems}},
    booktitle={Conference on Decision and Control (CDC)},
    pages={4320 -- 4325},
    address={Osaka, Japan},
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