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A feasibility study of elementary reinforcement learning-based process control
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Optimality assessment with optimality recovery for multi-modal process operations
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State estimation and model-based fault detection in a submerged arc furnace
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Investigating the performance of time-constrained clustering of multi-modal chemical process data
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Nonlinear adaptation of established linear and predictive control laws through safe reinforcement learning
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Constrained multi-objective Bayesian optimization of simulated moving bed chromatography
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On-line Final Quality Prediction for Multiphase Batch Processes with Uneven Durations
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