An iterative GP-based NMPC learning scheme for batch processes achieves 83% tracking error reduction after 4 iterations and 17-fold product mass increase by iteration 8 in simulations, matching full-model NMPC performance.
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Iterative Model-Learning Scheme via Gaussian Processes for Nonlinear Model Predictive Control of (Semi-)Batch Processes
An iterative GP-based NMPC learning scheme for batch processes achieves 83% tracking error reduction after 4 iterations and 17-fold product mass increase by iteration 8 in simulations, matching full-model NMPC performance.