Modeling and Intelligent Control of Two-Tank Interacting Level Process
L. ThillaiRani1, N. Deepa2, S. Arulselvi3
1L.Thillai Rani, Department of Electronics and Instrumentation Engineering, Annamalai University, Annamalai Nagar, Chidambaram-608002, (Tamil Nadu), India.
2N. Deepa, Department of Electronics and Instrumentation Engineering, Annamalai University, Annamalai Nagar, Chidambaram-608002, (Tamil Nadu), India.
3Dr. S. Arulselvi, Department of Electronics and Instrumentation Engineering,Annamalai University, Annamalai Nagar, Chidambaram-608002,(Tamil Nadu), India.
Manuscript received on 20 March 2014 | Revised Manuscript received on 25 March 2014 | Manuscript published on 30 March 2014 | PP: 30-36 | Volume-3 Issue-1, March 2014 | Retrieval Number: A0983033114/2014©BEIESP
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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: The control of liquid level in tanks and flow between tanks is a basic problem in the process industries. In vital industries such as petro-chemical industries, paper industries, water treatment industries have the interacting tanks which the processes of chemical or mixing treatment takes place in the process tanks. Hence, the level of fluid in the tanks and interaction between tanks must be controlled. It is essential for control system engineers to understand how interacting tanks control system works and how the level control problem is solved. The problem of level control in interacting tank processes are system dynamics and interacting characteristics. In interacting process dynamics of tank1 affects the dynamics of tank2 and vice versa because flow rate depends on the difference between the liquid levels. In this work, a real-time two-tank interacting level process is taken-up for study. The mathematical model of a two-tank interacting process is derived. The hydraulic resistances (R1 and R2) are obtained using Experimental data. The servo and regulatory responses are obtained with PI controller. To improve the performance of the closed loop a Fuzzy Logic Controller (FLC) is designed and implemented for a two-tank interacting process. The servo and regulatory responses are obtained with FLC. The performances of Fuzzy Logic Controller are compared with PI controller in simulation. The performance measures are tabulated. It is observed from the results that the FLC out performs with no overshoot, faster settling time, better set-point tracking and thereby producing minimum integral square error(ISE).
Keywords: Two-tank interacting process, PI Controller and FLC
Scope of the Article: Signal and Image Processing