Abstarct: In this thesis, designing an optimal controller is presented by employing intelligent evolutionary algorithms to the position control of robotic arms baxsed on voltage control strategy. As a case study, a robust control law baxsed on voltage control strategy is proposed and applied to the position control of a two-lixnk robotic arm in the presence of uncertainty. An advantage of the proposed control scheme is the repeatability of the closed loop system, which makes the use of optimization algorithms possible. Then Coefficients of the controller are calculated optimally to attain the control goals. The cost-function of optimization is evaluated using the mean square error index. Three optimization algorithms namely particle swarm optimization, firefly algorithm, and bat algorithm are compared in terms of accuracy and speed of convergence. The proposed control law is free from robot dynamics due to the use of voltage control strategy. Robustness and stability of the proposed control system are achieved through optimization algorithms.