Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9iS1/107834
Year: 2016, Volume: 9, Issue: Special Issue 1, Pages: 1-5
Original Article
A. Sumalatha1* and A. Bhujanga Rao2
1 Department of Electronics and Instrumentation Engineering, VR Siddhartha Engineering College, Vijayawada - 520007, Andhra Pradesh,India; [email protected]
2 Department of Instrument Technology, Andhra University, Visakhapatnam - 530003, Andhra Pradesh,India; dr [email protected]
*Author for correspondence
Sumalatha
Department of Electronics and Instrumentation Engineering
Email:[email protected]
Objectives: Present work describes the development of a dynamic model of laboratory scale level process using System Identification toolkit from LabVIEW graphical programming language. Methods/Statistical analysis: The dynamic characteristics of industrial processes are affected when they are recognized with different operating conditions. It is always advantageous to have an efficient model to design and implement suitable control configuration to obtain better performance. The identification process has several stages. Findings: The first stage comprises design of experiment, conduction, collection of experimental data. Useful portion of the input output data is selected and preprocessed to eliminate any outliers. In the second stage the experimental data is prepared in to different datasets which are further used to estimate autoregressive exogenous (ARX) models. Application/Improvements: Estimated models are simulated in both direct and indirect methods and the results are compared to draw conclusions.
Keywords: ARX Model, Closed loop Step Response, Data Driven Modeling, Parametric System Identification, System Identification
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