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Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller
[Full Text]
AUTHOR(S)
Omur Can Ozguney, Recep Burkan
KEYWORDS
Fuzzy Logic Control, Lyapunov Stability, Adaptive Control, Robotics.
ABSTRACT
The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore, adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose, adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory, stability of the uncertain system is guaranteed. In this study, robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.
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