DocumentCode :
3111559
Title :
Research on generic model control method for manipulator based on neural networks
Author :
Zhang, Mingjun ; Chu, Zhenzhong
Author_Institution :
State Key Lab. of Autonomous Underwater Vehicle, Harbin Eng. Univ., Harbin, China
fYear :
2012
fDate :
5-8 Aug. 2012
Firstpage :
371
Lastpage :
376
Abstract :
The trajectory tracking control problem based on generic model control method for manipulator is addressed in this paper. Aiming at the problem that the relative degree of the input and output of manipulator system is not equal to 1, the sliding mode switching function is established according to the trajectory tracking error, and a method using sliding mode switching function as system virtual output is presented for generic model control law design, so that the trajectory tracking error moves to the sliding mode switching surface and eventually tends to zero. Since it is difficult to establish the precise dynamics model for the manipulator, the adaptive identification method is put forward based on RBF neural networks, which introduces sliding mode switching item to compensate for the approximation error of neural networks and ensure the system stability. For the sliding mode switching item is easy to cause control system chattering, the sliding mode switching gain adjustment method based on the exponential function is proposed. Finally, the effectiveness of the proposed methods is verified by simulation results.
Keywords :
control system synthesis; manipulators; neurocontrollers; radial basis function networks; stability; trajectory control; variable structure systems; RBF neural networks; control system chattering; generic model control law design; generic model control method; manipulator system; neural networks; sliding mode switching function; sliding mode switching gain adjustment method; sliding mode switching surface; system stability; system virtual output; trajectory tracking control problem; trajectory tracking error; Joints; Manipulator dynamics; Neural networks; Switches; Trajectory; chattering; generic model control; manipulator; neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-1275-2
Type :
conf
DOI :
10.1109/ICMA.2012.6282872
Filename :
6282872
Link To Document :
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