Comparison of Stochastic Identification Techniques for Dynamic Modelling of Plastics Extrusion Processes

Author:

Kochhar A. K.1,Parnaby J.1

Affiliation:

1. Schools of Mechanical and Manufacturing Systems Engineering, University of Bradford

Abstract

The important plastics extrusion process is briefly described and the difficulties of modelling the process from physical considerations are outlined. A number of stochastic process identification techniques, i.e. correlation, spectral analysis, generalized least squares, instrumental variable, correlation matching, maximum likelihood and Box-Jenkins algorithms are briefly reviewed. The results of experimental work carried out on a laboratory plastics extruder, using random perturbations in screw speed, are presented. From a comparison of the results of different identification methods, it is suggested that although correlation and spectral analysis techniques can help in improving the understanding of the process mechanisms, the type of models best suited for high level feed-forward computer control are of the Box-Jenkins and maximum likelihood structural forms.

Publisher

SAGE Publications

Subject

General Engineering

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Instrumentation and Control;Polymer Extrusion;2014

2. A Deterministic Approach to Process Noise Attenuation in a Communication Satellite Driven by White Noise Sequence;International Journal of Soft Computing;2010-02-01

3. A novel approach to dynamic modelling of polymer extrusion for improved process control;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering;2007-06-01

4. Dynamic analysis of on-line product quality attributes of a food extruder Análisis dinámico de los atributos de calidad de productos extrudados;Food Science and Technology International;1997-12

5. Towards Intelligent Process Control of Injection Moulding of Polymers;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;1995-10

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