Modelling of Level Process
Rhea Mariah Thomas1, Manimozhi M2, Chitra A3, J Vanishree4, Razia Sultana W5

1Rhea Mariah Thomas, School of Electrical Engineering, VIT, Vellore  
2Manimozhi M, School of Electrical Engineering, VIT, Vellore
3Chitra A, School of Electrical Engineering, VIT, Vellore
4J Vanishree, School of Electrical Engineering, VIT, Vellore

5Razia Sultana W, School of Electrical Engineering, VIT, Vellore

Manuscript received on 26 August 2019. | Revised Manuscript received on 09 September 2019. | Manuscript published on 30 September 2019. | PP: 1155-1161 | Volume-8 Issue-11, September 2019. | Retrieval Number: J90780881019/2019©BEIESP | DOI: 10.35940/ijitee.J9078.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Industries such as, textile, food processing, chemical and water treatment plants are part of our global development. The efficiency of processes used by them is always a matter of great importance. Efficiency can be greatly improved by obtaining an exact model of the process. This paper studies the two main classifications of model development – First-Principles Model and Empirical Model. First-Principles Model can be obtained with an understanding of the basic physics of the system. On the other hand, Empirical Models require only the input-output data and can thus factor in process non-linearity, disturbances and unexpected errors. This paper utilizes the System Identification Toolbox in MATLAB for empirical model development. Models are developed for a single tank system, a classic SISO problem and for the two interacting tank system. Both systems are studied with respect to three operating points, each from a local linear region. The obtained models are validated with the real-time setup. They are satisfactory in their closeness to the real time process and hence deemed fit for use in control algorithms and other process manipulations.
Keywords: System identification, level process, first principle model, real time validation.
Scope of the Article: