Abstract
In this paper, a nonlinear receding-horizon observer is proposed for state reconstruction in batch terpolymerization reactors. It is shown that when constrained receding-horizon estimation is used together with a dedicated crossing singularity heuristic, state reconstruction is possible even in presence of measurement noise and up-to 10% error on the r.h.s of the ODE's describing the system's dynamics. The efficiency and the real-time implementability of the overall scheme is shown through illustrative scenarios including both simulation and experimental validation.
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