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.

SVM Performance Assessment for the Control of Injection Moulding Processes and Plasticating Extrusion / Anguita, Davide; Tagliafico, Luca; Boni, Andrea. - ELETTRONICO. - (2002), pp. 1-40.

SVM Performance Assessment for the Control of Injection Moulding Processes and Plasticating Extrusion

Boni, Andrea
2002-01-01

Abstract

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.
2002
Trento, Italia
Università degli Studi di Trento. DEPARTMENT OF INFORMATION AND COMMUNICATION TECHNOLOGY
SVM Performance Assessment for the Control of Injection Moulding Processes and Plasticating Extrusion / Anguita, Davide; Tagliafico, Luca; Boni, Andrea. - ELETTRONICO. - (2002), pp. 1-40.
Anguita, Davide; Tagliafico, Luca; Boni, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/358348
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