Thermal runaways in batch processes can lead to significant issues for safety and performance during normal operation in industry. This is usually circumvented by running such processes at lower temperatures than necessary, hence losing the opportunity to intensify production and therefore reduce reaction time. The detection of the thermal stability of batch systems can potentially be embedded in an advanced control scheme, therefore improving the performance by being able to intensify the process, achieving higher yields while keeping a stable operation. The derivation of stability criterion K for high-order reactions is presented in this work, resulting in better control when embedded in Model Predictive Control (MPC) schemes than standard nonlinear MPC schemes, based on the work in Kähm and Vassiliadis (2018). The non-trivial extension of stability criterion K for multi-component reactions with application to MPC systems is discussed in detail. The logic and verification of the form of the resultant Damköhler number in particular is discussed and demonstrated with case studies. A comparison of various MPC schemes is presented, showcasing that the implementation using criterion K results in intensified processes kept stable at all times, whilst reducing computational cost with regards to standard nonlinear MPC schemes. Furthermore, reaction times are reduced by at least twofold with respect to processes run at constant temperatures.
Thermal runaways in exothermic batch reactions are a major economic, health and safety risk in industry. In literature most stability criteria for such behaviour are not reliable for nonlinear non-steady state systems. In this work, Lyapunov exponents are shown to predict the instability of highly nonlinear batch processes reliably and are hence incorporated in standard MPC schemes, leading to the intensication of such processes. The computational time is of major importance for systems controlled by MPC. The optimal tuning of the initial perturbation and the time frame reduces the computational time when embedded in MPC schemes for the control of complex batch reactions. The optimal tuning of the initial perturbation and time horizon, dening Lyapunov exponents, has not been carried out in literature so far and is here derived through sensitivity analyses. The computational time required for this control scheme is analysed for the intensication of complex reaction schemes.
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