A comparison between three methods applied to parallel robot control namely: Computed torque controller, sliding mode control and sliding mode control using neural networks is presented in this paper. The simulation results show that PD control method is only accurate when model parameters are precisely identified. | Journal of Computer Science and Cybernetics, , (2015), 71–81 DOI: A COMPARISON STUDY OF SOME CONTROL METHODS FOR DELTA SPATIAL PARALLEL ROBOT NGUYEN VAN KHANG1,a , NGUYEN QUANG HOANG1,b , NGUYEN DUC SANG1 , and NGUYEN DINH DUNG2 1 Department of Applied Mechanics, School of Mechanical Engineering, Hanoi University of Science and Technology a ; b 2 Phuong Dong University Abstract. A comparison between three methods applied to parallel robot control namely: computed torque controller, sliding mode control and sliding mode control using neural networks is presented in this paper. The simulation results show that PD control method is only accurate when model parameters are precisely identified. In case of uncertain parameters, sliding mode and neural network sliding mode control methods are applied instead. Three controllers are implemented in Matlab for simulation. The results show that the control quality is improved by using the neural network sliding mode control method in comparison with two others. Keywords. Delta parallel robot, computed-torque control, sliding mode control, neural network control. 1. INTRODUCTION Today, parallel robotic manipulators are used widely in industrial applications owing to light compact structure, high stiffness and accuracy. Delta robot is one of the most successful parallel robots, with thousands of versions created around the world for several applications such as in food factories and medical field. Invented by Reymond Clavel in the early ’80s, this parallel robot uses the parallelogram structure to create three translational degrees of freedom by three revolute actuators. In most applications, the robot must move rapidly from one position to another position or follow a desired trajectory in three dimensional spaces with high precision. In order to perform this task, recently, several control methods have been investigated such as .
