Design of a Genetic based Optimized Fuzzy Logic Controller for Enhanced Trajectory Tracking Accuracy of a 3P Robot
Afshin Kouhkord, Armin Ghanbarzadeh, Parastoo Ebrahimi, Esmaeil Najafi
Abstract
Robot positioning precision is critical in industrial automation. This research attempts to analyze three distinct approaches for controlling a 3P robot. The designed controllers are position PID (P-PID), position and velocity PID (PV-PID) and genetic algorithm optimized fuzzy logic controller (GA-FLC). In this regard, the mentioned system is initially described, then a position PID controller is applied to the system. In the next step, an attempt has been made to reduce the system error by adding a PID on the velocity to the previous controller as a feed forward term. Then the fuzzy logic controller (FLC) is expressed in which the input variables are the position and velocity error signals and the output is the required force desired path. Ultimately by means of genetic algorithms optimized fuzzy membership functions are achieved. The proposed method outperforms its conventional counterpart and enhances robot precision for applications that require high positioning accuracy, such as riveting, drilling, and precise assembly. The robot modeling and control design were simulated using MATLAB and Simulink software, with the obtained numerical results serving as the criterion for evaluation.