Assessment of control techniques for the dynamic optimization of (semi-)batch reactors

This work investigates how batch reactors can be optimized to increase the yield of a desired product coupling two appealing techniques for process control and optimization: the nonlinear model predictive control (NMPC) and the dynamic real-time optimization (D-RTO). The overall optimization problem is formulated and applied to calculate the optimal operating parameters of a selected case study and the numerical results are compared to the traditional control/optimization techniques. It has been demonstrated in our previous work (Pahija et al. (2013). Selecting the best control methodology to improve the efficiency of discontinuous reactors. Computer Aided Chemical Engineering, 32,805-810) that the control strategy can significantly affect optimization results and that the appropriate selection of the control methodology is crucial to obtain the real operational optimum (with some percent of improved yield). In this context, coupling NMPC and D-RTO seems to be the ideal way to improve the process yield. The results presented in this work have been obtained by using gPROMS (R) and MS C++ with algorithms of BzzMath library. (c) 2014 Elsevier Ltd. All rights reserved.