Intelligent Approaches to Real Time Level Control

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Snejana Yordanova 1,*

1. Technical University of Sofia, Faculty of Automation, Sofia 1000, Bulgaria

* Corresponding author.


Received: 7 Feb. 2015 / Revised: 4 May 2015 / Accepted: 11 Jul. 2015 / Published: 8 Sep. 2015

Index Terms

Fuzzy logic level control, genetic algorithms, multi-objective optimization, real time, TSK plant modelling


Liquid level control is important for ensuring energy and material balance in many installations but it also difficult as the plant is nonlinear, inertial and with model uncertainties. Fuzzy logic controllers (FLCs) are successfully applied to ensure system stability and robustness by simple means and a model-free design. This paper suggests a procedure for off-line tuning of the many FLC parameters based on optimization of a suggested multi-objective function defined on several system performance indices using genetic algorithms (GAs). First, a model-free FLC is empirically tuned, then applied for real time control of the plant and the necessary data recorded and used to GA parameter optimize a TSK plant model of an accepted structure. The validated on different set of experimental data model is employed in FLC closed loop system simulation experiments to evaluate the fitness function in the GA optimization of the FLC pre-processing and post-processing parameters. The procedure is applied for the real time PI/PID FLC level control in a laboratory-scale tank system. The improvement of the system performance indices due to the GA optimization is estimated in level real time control.

Cite This Paper

Snejana Yordanova,"Intelligent Approaches to Real Time Level Control", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.10, pp.19-27, 2015. DOI:10.5815/ijisa.2015.10.03


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