Intelligent Approaches to Real Time Level Control
Автор: Snejana Yordanova
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 10 vol.7, 2015 года.
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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.
Fuzzy logic level control, genetic algorithms, multi-objective optimization, real time, TSK plant modelling
Короткий адрес: https://sciup.org/15010756
IDR: 15010756
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