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• W2043875902 abstract "Abstract The computation and application benefits of factorized RBF-based nonlinear model predictive control (NMPC) are presented. The NMPC algorithm derives its computational efficiency by factorizing the radial basis function (RBF) model response. A brief description of the factorized RBF-based NMPC algorithm is provided. Theoretical computation benefits are quantified for both SISO and MIMO formulations. Computation and application benefits of the algorithm are documented for a 4×4 MIMO subset of the Eastman Challenge problem. Results confirm computation requirements are reduced by more than an order of magnitude relative to application of traditional MPC using a non-factorized RBF model. The expected control performance benefits from using a nonlinear process model are also achieved." @default.
• W2043875902 created "2016-06-24" @default.
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• W2043875902 date "2002-09-01" @default.
• W2043875902 modified "2023-09-27" @default.
• W2043875902 title "Benefits of factorized RBF-based NMPC" @default.
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• W2043875902 doi "https://doi.org/10.1016/s0098-1354(02)00029-7" @default.
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