Robotics is the branch of rapidly developing technology that studies with the design, construction, manufacture and application of robots. The Selective Compliance Assembly Robot Arm is one of the most popular industrial robots because of its high precision, high speed, simplicity, and ease of installation. In this thesis, an optimal super-twisting sliding mode control for high speed pick and place industrial robot (SCARA) is designed and simulated, to derive the manipulator trajectories along the desired position, very precisely with a fast convergence. Euler-Lagrange approach has been applied to get the complete dynamic model of a manipulator and for each joints articulating joint torque to accelerate with direct current motors actuator, the stability of a system analyzed by using Lyapunov method. As before, several researchers are proposed on a SCARA robot based on sliding mode control technique to solve the position control problem. Furthermore, selection of designed parameters, sliding mode control has chattering effect. In this thesis the chattering effect is minimized by higher-order sliding mode control (super-twisting sliding mode control) techniques and particle swarm optimization is used to tune the control parameters of super-twisting sliding mode control. Also a comparative analysis of a standard super-twisting sliding mode control, particle swarm optimization based sliding mode control and the proposed controller in terms of dynamic performance and robustness characteristics is also proposed. Finally, this thesis shows that the proposed controller realize a good dynamic performance of the selective compliance assembly robotic arm with a minimum tracking error (3.1 xe −6 rad for first joint, 4.7 xe −6 rad for second joint, 2.1 xe −6 rad for third joint and 5.8 xe −6 rad for fourth joint). Key words: Particle Swarm Optimization, Pick and Place, SCARA Robot, Superslide model twisting Slide Mode Contro