Optimal Fuzzy Logic Control for Temperature Control Based on Social Spider Optimization

Abstract

Fuzzy Logic Controller (FLC) is useful for many applications like industrial, home, military and medical applications, so one of main application is temperature control of A proposed controller combines the advantages of controller structure and fuzzy inference for air heater temperature control applications. The input variables of the PDFLC-SSO are error and change of error, while its output is the control signal. PDFLC-SSO has seven membership functions. These functions are triangular shaped. Centroid method (CM) is selected for the defuzzification process. The universe of discourse range is used from (-1 to 1) for each input and output. Temperature heater model was utilized to test the controller; the gain factors was tuned using trial and error method and SSO algorithm to reach the optimum response with minimum settling time, minimum peak overshoot and minimum Integral Time Absolute Error (ITAE). Carried out simulations showed an average improvement in measurements using ITAE. ITAE is 7.46% for a constant set-value using PDFLC-SSO, while it is 9.55 for a constant set-value using PDFLC.