Lecturer's Publications

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Evolutionary Optimization Scheme for Exothermic Process Control System
(2011) Tan, M.K.; Chin, Y.K.; Tham, H.J; Teo, K.T.K.
The primary aim in batch process is to enhance the process operation in order to achieve high quality and purity product while minimizing the production of undesired byproduct. During the process, a large amount of heat is released rapidly when the reactants are mixed together due to exothermic behavior. This causes the reaction to become unstable and consequently the quality and purity of the final product will be affected. Therefore, it is important to have a control scheme which is able to balance the needs of process safety with the product quality and purity. This paper proposes genetic algorithm (GA) as an approach to control the process temperature by changing the coolant temperature because GA does not require the exact process dynamics in advance, which normally in practical, the process dynamics are poorly known in practical. GA is able to evolve itself to obtain an optimum solution to change the coolant temperature. The simulation studies show that the GA will be a good candidate to optimize the process and minimize the temperature overshoot throughout the reaction process. Furthermore, GA is able to evolve itself to obtain an optimum solution to change the coolant temperature.