Abstract
A robust adaptive compensation scheme is presented for compensation of asymmetric deadzone, dynamic friction and uncertainty in the direct-drive robot manipulator. Simple estimation laws are derived to build observers for estimation of deadzone and friction based on the LuGre friction model. A model-free RWCMAC controller to mimic the ideal control law is employed to overcome some shortcomings of the traditional model-based adaptive controller, which requires information on the robots dynamics in advance. The Lyapunov stability analysis yields the adaptive laws of the RWCMAC network as well as observers of deadzone and friction. Furthermore, the stability and optimal convergence speed of the learning rates of the RWCMAC is also guaranteed by employing the fully informed particle swarm (FIPS) algorithm. Robust tracking performance of the proposed control schemes is verified by simulations of direct-drive robots with deadzone in joint input torque, joint dynamic friction and uncertainty.
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This paper was recommended for publication in revised form by Associate Editor Yang Shi
Seong-Ik Han received his B.S. and M.S. degrees in Mechanical Engineering from Busan National University, Korea, in 1987 and 1989, respectively, and the Ph.D. in Mechanical Design Engineering from Busan National University in 1995. From 1995 to 2009, he was an assistant professor of Electrical Automation of Suncheon First College, Korea. Now he is a research professor in the Dept. of Electrical Engineering, Pusan National University, Korea. His research interests include intelligent control, nonlinear control, robotic control, active noise and vibration control.
Kwon-Soon Lee received the B.S. degree from Chungnam National University, Daejeon in 1977, the M.S. in Electrical Engineering from Seoul National University, Seoul, Korea, in 1981, and the Ph.D. in Electrical and Computer Engineering from Oregon State University, USA, in 1990. Since 1994, he has been with the Dept. of Electrical Engineering, at Dong-A University, Busan, Korea, where he is currently a professor. His research interests include intelligent control theory, and application of immune algorithm.
Min-Gyu Park received the B. S degree in Automotive Engineering from Daegu University, Daegu, Korea in 2007, and the M.S. from the Department of Mechanical and Intelligent Systems Engineering at the Pusan National University, Busan, Korea in 2009. He is currently pursuing his Ph.D. in the Department of Mechanical and Intelligent Systems Engineering at the Pusan National University. His research interests include hydraulic control.
Jang-Myung Lee received the B.S. and the M.S. in Electronic Engineering from Seoul National University, Seoul, Korea, in 1980 and 1982, respectively, and a Ph.D. in Computer Engineering from the University of Southern California (USC), Los Angeles, in 1990. Since 1992, he has been a professor with the Intelligent Robot Laboratory, Pusan National University, Busan, Korea. His current research interests include intelligent robotic systems, ubiquitous ports, and intelligent sensors. Dr. Lee is currently the president of the Korean Robotics Society. He is also the head of National Robotics Research Center, SPENALO.
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Han, S.I., Lee, K.S., Park, M.G. et al. Robust adaptive deadzone and friction compensation of robot manipulator using RWCMAC network. J Mech Sci Technol 25, 1583–1594 (2011). https://doi.org/10.1007/s12206-011-0328-9
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DOI: https://doi.org/10.1007/s12206-011-0328-9