PROCESS CONTROL SYSTEM IDENTIFICATION

• Main Author: CHE HAS, CHE MUHAIZILAWATI
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2004
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/7572/1/2004%20-%20PROCESS%20CONTROL%20SYSTEM%20IDENTIFICATION.pdf; http://utpedia.utp.edu.my/7572/

System Identification is an art of dealing with a problem of generating workable model of dynamic response based on the observed dataset from the actual system. The modelling process is based on the observed input and output data of a system. The objective of this project is to design and implement System Identification for Liquid System Pilot Plant in UTP by applying both the conventional System Identification technique known as empirical modeling and the intelligent techniques, a computer based method named System Identification Toolbox. Then, the comparison study between intelligent techniques and conventional modelling technique is conducted for a better performance determination. System Identification procedure involves the construction of a model from actual data and the model validation process. The construction of a model engages with three basic entities that are data record, model structure and determination of the best model. By following the System I dentification procedure, the four steps taken in accomplishing this project were: (1) experimental design, (2) modelling via empirical modelling, (3) simulation of System Identification via MATLAB-Simulink and (4) investigate performance Comparison between empirical modelling and model predictor using System Identification Toolbox. Empirical modelling is a simple graphical and calculation technique. A linear transfer function that is obtained from this method is adequate for the project implementations. The second method is intelligent method which is carried out with the aid of MATLAB software. All the selected best models are capable to reproduce the observed data with minimum predicted error. At the end of the project, based on some comparison and analysis, the author concludes that an intelligent technique gives a better performance compared to the conventional technique. n