This paper presents the application of a new and promising learning algorithm based on kernel methods, i.e., support vector machines (SVMs), for the control of injection moulding processes and plasticating extrusion. In particular, the main purpose of this work is to assess the effectiveness of the method when applied to such kinds of industrial processes, characterised by a large number of variables and strictly correlated by nonlinear relationships. First, we analyse the injection process by developing a simplified model, then we identify it by using a support vector machine. The reference of the control system is tracked through the design of a control block based on the structure of the SVM.
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