DESIGN AND ANALYSIS OF RULE-BASED FUZZY LOGIC CONTROLLER FOR PERFORMANCE ENHANCEMENT OF THE SUGARCANE INDUSTRY

Abstract

In the beginning, Zadeh's 1965 research on fuzzy sets inspired fuzzy logic (FL). FL continues to be comprehended through the estimation, ambiguity, partial reality, and inaccuracy. The integration of system intelligence will be accomplished through soft computing techniques. The study focuses on the widespread FL applications in manufacturing processes and standard computerization approaches. The sugar processing facility with the highest percentage of success in extracting the juice took first place among them. Because of the more significant seasonal component, regularity must be preserved to improve system performance. As a result, the proposed methodology successfully limits the volume or range of the Donnelly channel using the three inputs for the fuzzy controller. However, due to nonlinearities, the amount of cane fibre passing through the sugar mill's carrier fluctuates, which affects the mill's effectiveness. Additionally, the algorithm's use of three fuzzy input controllers to increase cane volume in the Donnelly chute during cane juice extraction results in a critical motor speed for the rake carrier ascribed to the range and quantity of cane on the carrier with the rolling rate. The toolbox function of FL in MATLAB® was used to create the simulation results for the 3-input.