Abstarct: The advantages of parallel robots have increased their usage in the industry as well as increasing their attention in scientific studies. In this study, first, the dynamic and kinematic modeling of a parallel robot called the delta robot and its motion control is investigated. Due to the existence of parallel kinematics, the inverse kinematics equation is extracted as closed loop equations. In this study, to obtain the dynamic equations of the delta robot lagrange method is used which is one of the most practical ways to obtain robot dynamics equations. In order to control the position of the robot to track the desired path, two control strategies, adaptive and sliding mode controller are considered to control the robot. Adaptive controller is designed to compensate the uncertainties baxsed on their estimation and sliding mode control due to compensate the parametric uncertainties and load disturbance. The results show that the proposed sliding mode controller has better performance than the adaptive controller. Also, to improve the sliding mode controller performance, a swarm optimization method is used to find optimal values of controlling coefficients. The simulation results show that the error is reduced as well as reduction of the control inputs by the optimal sliding mode controller rather than the sliding mode control without optimization.