期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 45, 期 3, 页码 521-532出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2014.2329931
关键词
Dual-arm coordination; humanoid robot; motion/force; neural network; unknown output nonlinearity
类别
资金
- National Natural Science Foundation of China [60974047, U1134004]
- Natural Science Foundation of Guangdong Province [S2012010008967]
- Science Fund for Distinguished Young Scholars, Zhujiang New Star [S20120011437]
- Ministry of Education of New Century Excellent Talent [NCET-12-0637]
- 973 Program of China [2011CB013104]
- Doctoral Fund of Ministry of Education of China [20124420130001]
- University of Macau Multiyear Research Grants
To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.
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