الفهرس 
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Abstract
Robot arm is very important in industrial applications, offices and hospitals. It helps to keep human away from dangerous tasks and also helps to save time and increase productions. Robot arm is generally used to move objects from point to another but if deflection happens the coordinates change so, the end effector will reach the wrong position. The robot arm or any robotic system will be useless without an efficient control system, because it controls the robot in such a way to execute the required goal. The used methods for the motion control of the robot arm depends on its mathematical model at large extent. Conventional proportional integration derivative (PID) controller or fractional order PID (FOPID) controller with inverse kinematics can be used to solve the problem of coordinates changing. PID controller is the most popular technique used in industrial application because of its simplicity of implementation and design. The fractional-order integral and the differential are however important in the control system design to add more degree of freedom to the controller. The FOPID controller is used to eliminate the error between the required and actual position of the robot end effector. Particle Swarm Optimization (PSO) algorithm is a new, modern, and robust optimization technique. It is commonly utilized to find out the global best solution in a complex search space. PSO is also widely used in adjusting parameters of controller and giving better responses. It is cheap, fast and more efficient than other optimization methods. In this thesis FOPID controller is used with inverse kinematics to reduce the error, solve the problem of coordinates changing and control the dynamic model of a 2-DOF robotic arm. A performance comparison between conventional PID and FOPID is done. Particle swarm optimization (PSO) technique is utilized to get the optimal parameters of PID and FOPID controllers. Modeling and simulation for PID and FOPID control system of 2-DOF robot arm is designed utilizing MATLAB/SIMULINK. The simulation result proved that FOPID is more flexible and more stable than PID controllers. FOPID controller also reduces errors more than PID controllers. The error response in both X and Z directions using PID controller is more than ten times the obtained error using FOPID controller.