This paper deals with the development of a dynamic real-time optimization (D-RTO) methodology and its experimental use in optimal operation of a batch reactor where polymer grafting reactions take place. It combines a constrained dynamic optimization method with a moving horizon state estimator within closed-loop control. The objective is to determine the online reactor temperature profile that minimizes the batch final time while meeting terminal constraints on the overall conversion rate and grafting efficiency. The methodology is first implemented in open-loop control in order to set up the experimental procedure and at the same time to assess the model accuracy. It is then implemented in closed-loop control, and the resulting computed and measured optimal profiles of temperature, monomer conversion rate, and grafting efficiency exhibit very good agreement and show also that the terminal constraints are satisfied.

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