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Experimental system for the optimization of the parallel manipulator control

This paper presents the results of an experimental system design for the optimization of parallel manipulator control based on an optimal configuration. The experimental system is an open design for various different configurations and controllers to support parallel manipulator research and applications. | Journal of Computer Science and Cybernetics, V.31, N.2 (2015), 83–95 DOI: 10.15625/1813-9663/31/2/5869 EXPERIMENTAL SYSTEM FOR THE OPTIMIZATION OF THE PARALLEL MANIPULATOR CONTROL NGUYEN XUAN VINH1 , LE QUOC HA2 , NGUYEN NGOC LAM3 , LE HOAI QUOC4 , AND NGUYEN MINH THANH5 1 University of Science, Vietnam National University Ho Chi Minh City; nguyen.xuan.vinh@gmail.com 2 Vietnam Institute of Electronics, Informatics and Automation; lequochavn@yahoo.com 3 Vietnam Institute of Electronics, Informatics and Automation; lamnguyenngoc ne@yahoo.com.vn 4 Saigon Hi-tech Park; lhquoc.shtp@tphcm.gov.vn 5 Saigon Hi-tech Park; nmthanh.shtp@tphcm.gov.vn Abstract. This paper presents the results of an experimental system design for the optimization of parallel manipulator control based on an optimal configuration. The experimental system is an open design for various different configurations and controllers to support parallel manipulator research and applications. Traditional PID control and self-tuning fuzzy PID control algorithm are applied for motion control of parallel manipulator. The quality system standard will be analyzed and compared with simulation results. The system can be a useful tool for research and training. Keywords. Parallel manipulator, robot experimental system, robot controller, fuzzy theory, PID controller, self-tuning. 1. INTRODUCTION For recent years, parallel manipulators have been applied in several fields such as mechanical precision machining, assembly machinery, surgery equipment, astronomy, geodesy and moving simulators. . . [1–4]. As it is well known, high stiffness, high precision with high speed of movements, heavy load possibility and low inertia force are outstanding advantages of parallel robots. However, their drawbacks are limited workspace, complicated design and manufacture, high cost and the existence of singularities in their workspace [5–11]. Therefore, the study of optimization of design and control is important to minimize their noted