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Currently, SVM is an active field in artificial intelligent technology and has been applied to pattern recognition, regression and signal processing applications. It refers to kernel-based methods; follow the simple, but powerful idea of non-linearity mapping input data into high-dimensional feature space. The batch reactors are the important unit of many industries; mostly, it is used in chemical and pharmaceutical industries. In this paper, the support vector machine is employed to identify the batch reactor. The simulation results show that support vector machine provides a new and effective method for modelling a non-linear process and has promising application in industrial process. A non-linear control strategy for a batch reactor process with input-output form is proposed. This strategy is termed as internal model control (IMC). IMC is found to be well suited for a system when there is no significant rate of change of the set point.

GMC Design Based on SVM Model of Batch Reactor