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- W3045597989 abstract "This article considers the dynamic optimization and control of startup operations for a portable, modular, reconfigurable system for the on-demand, continuous-flow synthesis of pharmaceuticals. The offline dynamic optimization employs piecewise constant or affine discretizations of the control inputs for a high-order nonlinear differential-algebraic equation first-principles model. The dynamic optimization is implemented using a direct sequential approach anTd the nonlinear program is solved using adaptive mesh methods. The startup objective is designed to minimize waste while maximizing production rate. The optimized setpoint trajectories are followed by using fast model predictive control whose online computational cost is not a function of the high state dimension of the process model. Providing an optimal time-varying setpoint trajectory to the fast model predictive control algorithm results in significant improvement in the closed-loop performance during startup, and the overall approach is shown to be robust to a realistic and large level of model uncertainty." @default.
- W3045597989 created "2020-08-03" @default.
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- W3045597989 date "2020-07-01" @default.
- W3045597989 modified "2023-10-16" @default.
- W3045597989 title "Fast Model Predictive Control of Startup of a Compact Modular Reconfigurable System for Continuous-Flow Pharmaceutical Manufacturing" @default.
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- W3045597989 doi "https://doi.org/10.23919/acc45564.2020.9147331" @default.
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