Abstract
This paper discusses the design of a model-based multivariable nonlinear model predictive control (NMPC) formulation for the control of a multi-zone multi-feed LDPE autoclave reactor. Unscented Kalman filtering (UKF) state estimation was employed for online estimation of the plant states and disturbances. In addition to structural plant-model mismatch and noisy process measurements, the closed-loop performance of the UKF based NMPC scheme was investigated under parametric uncertainty in the kinetic rate constants. The closed-loop NMPC performance was also assessed for polymer grade changes, and for disturbance rejection at both open-loop stable and unstable operating regions.
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