Abstract
This paper presents the application of machine learning schemes, namely SVM and GA, for realization of non linear control schemes and optimization of Batch reactor. Batch reactor is an essential unit operation in almost all batch- processing industries such as chemical and pharmaceuticals. In this approach, the temperature profile of the batch reactor is optimized using Genetic Algorithm (GA) with a view to maximize the desired product and minimize the waste product as a multi -objective function. Generic Model Control is implemented by using SVM Estimator, and it includes the non-linear model of a process to determine the control action. SVM estimator will predict the current value of the heat release makes the control performance to be more robust. The robustness performance of GMC has been experienced. Other non linear control schemes, such as Direct Inverse Control and Internal Model Control, are also implemented.
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