Efficiency Of Different Control Strategies In A Force-feedback Gripper
Free (open access)
213 - 222
O. B. Lőrinczi, T. Szalay & P. Aradi
This paper aims to introduce the development of a control system implemented for a force-feedback gripper mechanism, as well as the results of the experiments carried out on the device. The achievements shall be used in additional research related to medical purpose grippers, such as artificial hands. The aim of the current research is the improvement of the control system of artificial hands in order to assure the expected usability in the case of a simplified mechanical structure, and eventually to decrease the manufacturing cost of such devices to gain higher availability. First, the main units of the experimental device will be described. After the clarification of the basics, the applied control strategies shall be discussed in detail. From the basic PI/PID control, to adaptive fuzzy/neurofuzzy control, different methods are applied also on the simulation model and the experimental device itself. The main results of the research are the summary of differences between the particular control strategies. The properties of the controls, like speed, stability, accuracy and adaptivity are determined and a comparative analysis have been expounded. From the achieved results, the overall efficiency of the different control strategies can be determined, the type and properties of the optimal control can be described. Finally the aspects of further development will be discussed; on one hand, that means the design and production of a new, more complex mechanism; and on the other hand, the feedback of more state variables in order to gain more information for better function. Hopefully a complete five-finger gripper will be manufactured in the near future, and by the time it will be available, the results of this study can be utilized for its control system. Keywords: biomechatronics, sensor technologies, force-feedback grasping. Budapest University of Technology and Economics, Hungary
Keywords: biomechatronics, sensor technologies, force-feedback grasping.