Robot control based on Coriolis and centrifugal terms fuzzification

摘要

A new method for on-line tuning the gains of a decentralized PD controller with gravity compensation using fuzzy logic is proposed. The design of the controller is based on the fuzzy description of the robot configuration. The fuzzy inference system keeps track and takes decisions based on the robot configuration and joint velocities to adjust the derivative and proportional gains. The rules governing the controller are derived by studying the effects of the Coriolis and centrifugal terms on the robot dynamic behavior. The gravitational terms are computed using a fizzy inference system for each joint This FIS is trained with data taken from the simulated robot. The designed fuzzy-PD controller is compared with a centralized PD control law with gravity compensation and it is found that the fuzzy-PD controller is more robust in facing dynamic uncertainties. A two DOF robotic arm is used to demonstrate the performance of the proposed method for designing a robot controller.