Genetic Algorithm Based Multivariable Control for Exothermic Batch Process

Exothermic process is highly nonlinear and complex process. Large amount of heat will be released during the chemical reaction. As a result of the exothermic behaviour, the reaction may become unstable and consequently poses safety concern to the plant if the reactor temperature exceeds the cooling capacity. In the industrial point of view, heating is needed in order to speed up the reaction rate so that it can reduce the overall process reaction time. Hence, this paper proposes genetic algorithm (GA) to control the reaction temperature as well as to balance the production needs with the safety specification. GA exploits probabilistic search method to optimise the specific objective function based on evolutionary principle. Simulation assessment of the GA has been carried out using a benchmark exothermic batch process model. The results show that GA is a good candidate in controlling the reactor temperature.