AUTHORS: Khaled Mustafa, Abdulgani Albagoul, Mustafa Saad

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ABSTRACT: Most of the industrial processes are multivariable in nature. The multivariable system consists of many manipulated and controlled variables and thereby it is very difficult in controller design because of changes in process dynamics and interactions between process variables. A quantitative approach such as relative gain array is used in the analysis of the interactions between manipulated and controlled variables, and thus provides a best pairing to generate a control scheme. In this paper, the coupled tank control system has two inputs, which are the inlet flow rate to the tanks and two outputs, which are the liquid level height inside the tanks. PID controller has been commonly used in industrial automation. PID controllers are designed and simulated for the best loop pairings of manipulated and controlled variables. In this work, a MIMO system is converted to multivariable SISO system in the separation process for the coupled tank. In the consideration of nonlinearity, the fuzzy adaptive PID controller is introduced to obtain an excellent control performance. The PID parameters are then fed in an on-line manner from the fuzzy logic algorithm. That depends on the fuzzy inference rules, which are established between the PID parameters and the error and change in error. Simulation studies are then conducted based on the developed model using MATLAB Simulink. Based on the integral time absolute error index the best performance of the system is decided. Finally, the fuzzy adaptive PID controller is more robust than classical PID controller.

KEYWORDS: coupled tank system, modeling, multivariable, interaction, ITAE, MATLAB, fuzzy adaptive.

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