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• W2395597603 abstract "The application of optimization-based control methods such as nonlinear model predictive control (NMPC) to real-world process models is still a major computational challenge. In this paper, we present a new numerical optimization scheme suited for NMPC. The SQP-type approach uses an inexact constraint Jacobian in its iterations and is based on adjoint derivatives, that can be computed very efficiently. In comparison to a similar real-time algorithm based on directional sensitivities and an exact constraint Jacobian, the computational complexity is significantly reduced. Both algorithms are applied to the model of a thermally coupled distillation column for disturbance rejection. The results provide a proof-of-principle for the proposed adjoint-based optimization approach." @default.
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• W2395597603 date "2008-01-01" @default.
• W2395597603 modified "2023-10-10" @default.
• W2395597603 title "An Adjoint-based Numerical Method for Fast Nonlinear Model Predictive Control" @default.
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• W2395597603 doi "https://doi.org/10.3182/20080706-5-kr-1001.00329" @default.
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