Performance study of Kinematic Control of 6 DOF Robot Arm Using Fuzzy Logic Control

Abstract

There are many fields for the applications of robot manipulators to execute the given tasks such as material handling, painting, welding, pick-and-place operations, undersea explorations, space manipulation, hazardous field, etc. The important role of industrial robot manipulators is to substitute labor power by doing the repetitive, dangerous and mundane tasks in different type of application area. The robotic systems design and their control methods are difficult to make zero error for complex activity like, welding electronics, inspection and medical tasks. Those tasks need high accuracy and precisions especially on medical fields like surgical operations. To achieve the desired task the position and orientation (pose) of end effector or tool must be controlled to be complete the execution of the specific task. The above stated goal to have the sound knowledge of modeling of the robot arm and to solve the control problems. The kinematic modeling is the first task to study the position and orientation of the end effector numericaly performed and see the kinematic analysis using Matlab toolbox. Then the independent joint controlling will apply for each joint actuators. The main objective of thesis concerned about Performance study of Kinematic Control of 6 DOF Robot Arm Using Fuzzy Logic Control. From existing robots type I select KUKA KR 16-2 manipulator robot as case study. The study performed using theoretical analysis including forward and inverse kinematic mathematical modeling approach of the robot based on transformation matrix , the kinematic modeling implemented by robot toolbox that work under MATLAB program, the forward and inverse kinematic simulation done by robot toolbox with MATLAB/SIMULINK environment. Then the simulation show as the pose of end effector of the robot. Design of the robot controller using fuzzy logic controller (FLC) method and the result were compared with the proportional integral derivative controller (PID) use as benchmark then the discussion will done based on the result output in terms time of response. FLC gives as better results than PID controller in terms of time response of the settling time minimum and no overshot, but PID is better result gives fast rising time than FLC