Re-evaluation on fuzzy logic controlled system by optimizing the membership functions

Abstract

Heat exchange among two fluids at different temperatures is achieved by temperature gradient. Heat exchange process modelling and control is complex because of its non-linearity, large inertia, and time variability. Its control effect is often not satisfactory because of these disadvantages which are difficult to overcome. Therefore, it is very important to identify an effective and accurate temperature control scheme for heat exchange system. A fuzzy logic control (FLC) system can be used for controlling this process. FLC system works with fuzzy set theories which are characterized via membership functions (MFs) i.e. fuzzy sets are constructed by their MFs. Their simulation studies can be performed with different shapes such as triangular, trapezoidal, Gaussian, etc. There are different responses to different shapes of MFs of a fuzzy inference system. The membership function must have its values in the range [0,1], which is the only constraint it must satisfy. This paper evaluates the detailed design method of a fuzzy logic control (FLC) system. The study considers the plant function of a heat exchange system and presents the controller response of this system using various membership functions. The study also details out comparison of three different types of membership functions in a fuzzy logic controller. The plant model [2] is used as a test base to confirm the efficacy of this design technique, with modeling and simulations performed using MATLAB Simulink software. Through the results of the simulation, the study, justifies the control strategy which has a significant robustness, quicker response, and better temperature control of the plant system.