DocumentCode :
1863893
Title :
Trajectory control of flexible plate using neural network
Author :
Arai, Fumihito ; Rong, Lili ; Fukuda, Toshio
Author_Institution :
Dept. of Mechano-Inf. & Syst., Nagoya Univ., Japan
fYear :
1993
fDate :
2-6 May 1993
Firstpage :
155
Abstract :
Modeling and control problems for a three-joint robot handling a flexible plate in the vertical plane under gravity are treated. The dynamical model is obtained using Hamilton´s principle, and the ordinary differential equations are obtained using modal analysis. Given the tip position, an iterative algorithm for solving the inverse kinematics is presented. The control torque is obtained using the feedback error learning method and the desired trajectory of the static bending deflection curve. Four three-layer neural networks are used to reduce the joint-angle feedback errors and bending vibration. Simulation results are given
Keywords :
distributed parameter systems; inverse problems; iterative methods; kinematics; large-scale systems; neural nets; robots; Hamilton´s principle; bending vibration; control torque; feedback error learning method; flexible plate; inverse kinematics; iterative algorithm; joint-angle feedback errors; neural network; ordinary differential equations; static bending deflection curve; three-joint robot; three-layer neural networks; trajectory control; Differential equations; Error correction; Gravity; Iterative algorithms; Kinematics; Modal analysis; Neural networks; Neurofeedback; Robots; Torque control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
Type :
conf
DOI :
10.1109/ROBOT.1993.291976
Filename :
291976
Link To Document :
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