FUZZY LOGIC CONTROL IN ROBOT MANIPULATORS: A COMPARATIVE ANALYSIS WITH BOOLEAN LOGIC
Abstract
Robot manipulators encounter significant control challenges stemming from nonlinear dynamics, parametric uncertainties, and external disturbances. While Boolean logic-based controllers operate through precise binary thresholds, fuzzy logic control utilizes linguistic rules and graded membership to emulate human decision-making. This paper examines both control paradigms, detailing theoretical foundations and practical implementation for a 2-DOF manipulator. Quantitative comparisons reveal fuzzy logic’s superior adaptability in trajectory tracking and disturbance rejection, while Boolean methods maintain advantages in computational efficiency. The study concludes with controlled selection guidelines based on application-specific requirements.