OGCVL integrates symbolic and numerical techniques to learn effective nonlinear controlled variables for scalable self-optimizing control in chemical processes.
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Pith papers citing it
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math.OC 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A vectorized reformulation of global self-optimizing control makes structural causality constraints linear for batch processes and enables a shortcut method that yields simple, repetitive combination matrices for near-optimal control, shown on a fed-batch reactor.
A desensitized optimal guidance algorithm using direct collocation and mesh remapping yields tighter trajectory envelopes and smaller terminal errors under parameter uncertainties compared to standard methods.
citing papers explorer
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Generalized Global Self-Optimizing Control for Chemical Processes: Part II Objective-Guided Controlled Variable Learning Approach
OGCVL integrates symbolic and numerical techniques to learn effective nonlinear controlled variables for scalable self-optimizing control in chemical processes.
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Global self-optimizing control of batch processes
A vectorized reformulation of global self-optimizing control makes structural causality constraints linear for batch processes and enables a shortcut method that yields simple, repetitive combination matrices for near-optimal control, shown on a fed-batch reactor.
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Computational Method for Desensitized Optimal Guidance Using Direct Collocation
A desensitized optimal guidance algorithm using direct collocation and mesh remapping yields tighter trajectory envelopes and smaller terminal errors under parameter uncertainties compared to standard methods.