Comparison of Tuning Methods of PID Controllers of Two Conical Tank System of Interacting Type
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Conical tank, interacting system, non-linear, PID, controller, performance and genetic algorithmResumé
The rapid increasing complexity of modern control systems has accentuated the idea ofapplying new modern approaches in order to solve design problems for various controlengineering applications. This paper deals with the tuning of PID controllers for complexnonlinear process of two interacting Conical Tank Systems. Conical tanks play vital rolein leaching extractions in pharmaceutical and chemical industries, as well as in foodprocessing industry. It is a kind of multiple-use equipment, designed for boiling andextraction working procedure. Level control of a conical tank is a tedious processbecause of its non-linear characteristics hence proportional-Integral-Derivative (PID)control schemes have been widely used to overcome the issue by applying differentcontrolling techniques. A PID controller is otherwise called as three term-control whichhas three constant parameters and it takes the present error, accumulation of past errorsand prediction of future errors into account based upon the current rate of change oferror, respectively. The proposed control strategy includes the tuning of PID controllerusing Ziegler-Nicholos (Z-N) method and intelligent techniques like Genetic Algorithm(GA). The scope of this paper is to compare the different conventional tuning methods forsingle input single output (SISO) systems such as Z-N, Tyreus-Luben (T-L), InternalModel Control (IMC) and GA to predict the most efficient controller. The factors forcomparison include time domain specifications and performance of the controller. Theperformance of the controller for different tuning rules has been investigated in aMATLAB simulation Platform in which Genetic Algorithm outperformed well whencompared to all other controllers in terms of time domain specification and performanceindex.Keywords: Conical tank, interacting system, non-linear, PID, controller, performance and genetic algorithmDownloads
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