Behavior Study of a Combination of FLC and GA Controlling a Robot Arm Along a Desired Trajectory

Abstract

Behavior of a combination of a fuzzy logic controller (FLC) and genetic algorithms (GAs), when controlling a robot arm along a designed trajectory, is studied. In the investigated method, which henceforth will be referred to as GFLC, genetic algorithms, by modifying the consequences of the linguistic rules, train the FLC so that path tracking of the system is improved.
In this paper, the possibility of applying GFLC to a single arm robot is first discussed theoretically. Then, to investigate GFLC’s performance under some different conditions, a series of simulations on a model based on a single link manipulator are conducted. Finally, to study the practicality of this technique, GFLC is applied to a real single arm robot.