DocumentCode :
1221076
Title :
Intelligent feedforward control and payload estimation for a two-link robotic manipulator
Author :
Nho, Hyuk C. ; Meckl, Peter
Author_Institution :
Sch. of Mech. Eng., Purdue Univ., West Lafayette, IN, USA
Volume :
8
Issue :
2
fYear :
2003
fDate :
6/1/2003 12:00:00 AM
Firstpage :
277
Lastpage :
282
Abstract :
Conventional model-based computed torque control fails to produce a good trajectory tracking performance in the presence of payload uncertainty and modeling error. The challenge is to provide accurate dynamics information to the controller. A new control architecture that incorporates a neural-network, fuzzy logic and a simple proportional-derivative (PD) controller is proposed to control an articulated robot carrying a variable payload. An off-line trained feedforward (multilayer) neural network takes payload mass estimates from a fuzzy-logic mass estimator as one of the inputs to represent the inverse dynamics of the articulated robot. The effectiveness of the proposed architecture is demonstrated by experiment on a two-link planar manipulator with changing payload mass. Experimental results show that this control architecture achieves excellent tracking performance in the presence of payload uncertainty.
Keywords :
feedforward; flexible manipulators; fuzzy control; intelligent control; manipulator dynamics; neurocontrollers; two-term control; PD controller; feedforward; feedforward neural network; fuzzy control; intelligent control; inverse dynamics; model-based control; neurocontrol; payload estimation; two-link planar manipulator; Intelligent control; Intelligent robots; Manipulator dynamics; Multi-layer neural network; PD control; Payloads; Proportional control; Torque control; Trajectory; Uncertainty;
fLanguage :
English
Journal_Title :
Mechatronics, IEEE/ASME Transactions on
Publisher :
ieee
ISSN :
1083-4435
Type :
jour
DOI :
10.1109/TMECH.2003.812847
Filename :
1206484
Link To Document :
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