In order to optimize industrial production, the parallel three degrees of freedom (3-DOF) Delta robot has been studied and improved during the time. This study continues to present two methods to improve the quality of the PID controller using fuzzy logic and genetic algorithm, applying to 3-DOF Delta robot. The Fuzzy-PID controllers for the Delta robot are designed using errors and changes of errors between references and system responses and combined with initial parameters to find the optimal values of PID controllers. While the GA-PID controllers are optimally designed to satisfy IAE objective functions based on the starting values of PID controllers determined by the Ziegler-Nichols method. Simulation and comparison results indicate that the combination of fuzzy logic and genetic algorithm with traditional PID controllers are suitable for the improvement of Delta robot tracking control. The proposed controllers are also applied in experiments on the real Delta robot model. Experimental results also indicate that the Fuzzy-PID and GA-PID controllers can control the Delta robot for tracking several trajectories.