caa a22 4500 445361395 CHVBK 20180317142916.0 cr unu---uuuuu 170323e20110901xx s 000 0 eng 10.1007/s11071-010-9902-4 doi (NATIONALLICENCE)springer-10.1007/s11071-010-9902-4 Neural network based robust hybrid control for robotic system: an H ∞ approach [Elektronische Daten] [Jinzhu Peng, Jie Wang, Yaonan Wang] A novel robust hybrid tracking control for robotic system is proposed. This hybrid control scheme combines computed torque control (CTC) with neural network, variable structure control (VSC) and nonlinear H ∞ control methods. It is assumed that the nominal system of robotic system is completely known, which is controlled by using CTC method. Neural network is designed to approximate parameter uncertainties, VSC is used to eliminate the effect of approximation error, and H ∞ control is employed to achieve a desired robust tracking performance. Based on Lyapunov stability theorem, it can be guaranteed that all signals in closed loop are bounded and a specified H ∞ tracking performance is achieved by employing the proposed robust hybrid control. The validity of the control scheme is shown by computer simulation of a two-link robotic manipulator. Springer Science+Business Media B.V., 2010 Robotic system nationallicence Computed torque control nationallicence Neural network nationallicence Variable structure control nationallicence H ∞ control nationallicence Lyapunov stability nationallicence Peng Jinzhu School of Electrical Engineering, Zhengzhou University, 450001, Zhengzhou, Henan, China aut Wang Jie School of Electrical Engineering, Zhengzhou University, 450001, Zhengzhou, Henan, China aut Wang Yaonan College of Electrical and Information Engineering, Hunan University, 410082, Changsha, Hunan, China aut Nonlinear Dynamics Springer Netherlands 65/4(2011-09-01), 421-431 0924-090X 65:4<421 2011 65 11071 https://doi.org/10.1007/s11071-010-9902-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11071-010-9902-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Peng Jinzhu School of Electrical Engineering, Zhengzhou University, 450001, Zhengzhou, Henan, China aut NATIONALLICENCE 700 1- Wang Jie School of Electrical Engineering, Zhengzhou University, 450001, Zhengzhou, Henan, China aut NATIONALLICENCE 700 1- Wang Yaonan College of Electrical and Information Engineering, Hunan University, 410082, Changsha, Hunan, China aut NATIONALLICENCE 773 0- Nonlinear Dynamics Springer Netherlands 65/4(2011-09-01), 421-431 0924-090X 65:4<421 2011 65 11071 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer