Adaptive Control of Robotic Manipulators With Unified Motion Constraints

Mingming Li, Yanan Li, Shuzhi Sam Ge, Tong Heng Lee
2017 IEEE Transactions on Systems, Man & Cybernetics. Systems  
In this paper, we present an adaptive control of robotic manipulators with parametric uncertainties and motion constraints. Position and velocity constraints are considered and they are unified and converted into the constraint of the nominal input. An adaptive neural network control is developed to achieve trajectory tracking, while the problems of motion constraints are addressed by considering the saturation effect of the nominal input. The uniform boundedness of all closed-loop signals is
more » ... rified through Lyapunov analysis. Simulation and experiment results on a 2 DOF robotic manipulator demonstrate the effectiveness of the proposed method. Index Terms-robotic manipulator; adaptive control; unified motion constraints; input saturation; neural network approximation Mingming Li Mingming Li received the B.Eng. degree in communication engineering from Sun Yatsen University, Guangzhou, China, in 2013. He is currently pursuing his Ph.D. degree with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His current research interests include adaptive control, associative memories and artificial intelligence. Yanan Li (M'14) received the B.Eng degree in control science and engineering and the M.Eng degree in control and mechatronics engineering, from the Harbin Institute of Technology, China, in 2006 and 2009, respectively, and the Ph.D. degree from the NUS Graduate
doi:10.1109/tsmc.2016.2608969 fatcat:vodozxicc5a53kmeu3ra5ulir4