In this paper, propose a new method of easily recognizing and regenerating robot motions used for robot motion control to perform the task of painting furniture and welding parts in small scale industries. | TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K6- 2015 Accurate motion regeneration technique with robust control approach Dac-Chi Dang Young-Bok Kim Pukyong National University, Busan, Korea (Manuscript Received on July 15, 2015, Manuscript Revised August 30, 2015) ABSTRACT In this paper, the authors propose a new method of easily recognizing and regenerating robot motions used for robot motion control to perform the task of painting furniture and welding parts in small scale industries. The method is based on the process of accurate modeling, control design and experimental evaluation. In this study, the models and controllers for all joints of 3DOF robot system are obtained individually. The Robust control controller is designed to cope with uncertainties, especially the effects of the added inertia moment. In the experiment, the robust control method is compared with the existing PID control method, and the results indicate that the proposed designing method is more efficient than the traditional method. Keywords: Recognition; Regeneration; Robot; Motion control; robust control; Trajectory tracking. 1. INTRODUCTION In recent decades, advanced robot technology has been widely applied in painting and welding processes due to its benefits such as improvement in quality of products, improvement of working environment and safety, reduction in the number of workers in hazardous environment. The work performed by the industrial robot is simple and repetitive and taught by the operator. In the automobile assembly line, for instance, the robot welds or tightens repeatedly the assigned point all the time. In order to control robot regenerate exactly target routes, many control strategies have been proposed. Some approaches such as PID control [1], sliding mode control [2] and adaptive control [3] have been used. However, these approaches require a precise model or need to identify on-line model. It is unavoidable to make heavy computation time. Moreover, the .
