DocumentCode :
3325669
Title :
Constrained motion control of flexible manipulators based on a dynamic neural network
Author :
Tian, Lianfang ; Wang, Jun ; Mao, Zongyuan
Author_Institution :
Dept. of Mech. Eng., California Univ., Riverside, CA, USA
Volume :
2
fYear :
2002
fDate :
11-14 Dec. 2002
Firstpage :
678
Abstract :
In this paper, a neural network approach is proposed for the motion control of a constrained flexible manipulator system, whereby both the contact force and the position of the end-effector contacting with a surface are controlled. The dynamic equations, vibration of the flexible link and constrained force are derived. The developed control scheme can adaptively estimate the dynamics of the manipulator by utilizing a dynamic recurrent neural network (DRNN) to approximate the underlying dynamics. Local stability of the system is discussed. The results confirm that the designed controller performs remarkably well.
Keywords :
flexible manipulators; motion control; neurocontrollers; recurrent neural nets; controller design; dynamic recurrent neural network; flexible link; flexible manipulator system; flexible manipulators; motion control; neural network; recurrent neural network; Automatic control; Control systems; Equations; Force control; Manipulator dynamics; Motion control; Motion planning; Neural networks; Stability; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2002. IEEE ICIT '02. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7657-9
Type :
conf
DOI :
10.1109/ICIT.2002.1189246
Filename :
1189246
Link To Document :
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