Employing economic model predictive control for improving efficiency of the batch reactor carrying out decomposition of the Di-Cumyl-Peroxide

Batch reactors are used to produce agro-herbicides, often operating under metastable conditions. Exothermic reactions within these reactors can rapidly release large amounts of chemical energy, increasing the reaction rate and risking a runaway excursion. To prevent excessive heat dissipation, the reactor must operate within a lower mesophilic temperature range. The decomposition of dicumyl-peroxide is a notable example of a runaway reaction, characterized by multi-order thermo-kinetics with an Arrhenius temperature dependency. This decomposition rate is highly sensitive to factors such as Damkohler’s number, exothermic enthalpy, oxygen presence, substrate concentration, and initial temperature variations. Many kinetic parameters are not directly measurable in real-time applications. (i) An economic stage cost is derived and integrated into a model-predictive-control (MPC) law to regulate coolant flow and manage exothermic heat dissipation, mitigating unmeasured disturbances and faults. (ii) For estimating unmeasured reactor states and uncertainties, a cubature Kalman filter with a singular-value-decomposition approach has been utilized. (iii) Event-triggered scheduling combined with cubature Kalman filter, reduced communication resource usage. : The economics MPC controller tested on the dicumyl-peroxide system is compared with a standard nonlinear MPC rule, considering factors like cooling period, decomposition rate, and observer accuracy which ensures the effectiveness of the proposed algorithm. [Display omitted] •Temperature control of a hazardous decomposition reaction has been carried out.•To avoid cumbersome iterative steps, an event-driven observer is utilized.•CKF incorporated with SVD method observes unmeasured uncertainties, actuator fault.•A trade-off is laid out between the transmission rate and the prediction accuracy.•An EMPC is integrated with the event-driven observer to optimize batch operations.•Field-oriented control of batch reactor with DCP decomposition is explored.•Stability analysis of the closed-loop system is proved via the Lyapunov theorem.