Title :
Trajectory following control of robotic manipulators using neural networks
Author :
M.K. Ciliz;C. Isik
Author_Institution :
Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
fDate :
6/12/1905 12:00:00 AM
Abstract :
A novel learning control architecture utilizing nonlinear computational properties of neural networks is presented. The nonlinear dynamics of the manipulator is assumed to be unknown, and the control scheme efficiently learns the required feedforward torques for a specified trajectory after a repeated number of trials. Simulation tests give promising results for real-time implementation of the algorithm.
Keywords :
"Robot control","Neural networks","Manipulator dynamics","Equations","Torque control","Trajectory","Computer networks","Adaptive control","Parametric statistics","Neurofeedback"
Conference_Titel :
Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
Print_ISBN :
0-8186-2108-7
DOI :
10.1109/ISIC.1990.128509
