Title :
Control of dynamic grasping systems using neural network approximation
Author :
Guo, Gongliang ; Gruver, William A. ; Jin, Kai
Author_Institution :
Coll. of Eng., Kentucky Univ., Lexington, KY, USA
Abstract :
A control algorithm for dynamic grasping systems using neural network approximation (NNA) is proposed. The kinematic and dynamic equations of the grasping system are derived. Based on these equations, a method for generalized computed torque control is developed. From computations of this control scheme, four elemental operation functions that are realized by elemental NNA functions are induced. All of the control computations in the grasping system are accomplished using neural network approximation. The PD control of a two-jointed finger mechanism is studied as an example of the application of the algorithm. Results using the NNA functions are compared
Keywords :
neural nets; robots; PD control; dynamic equations; dynamic grasping systems; generalized computed torque control; kinematic equations; neural network approximation; two-jointed finger mechanism; two-term control; Approximation algorithms; Computer networks; Control systems; Equations; Fingers; Heuristic algorithms; Kinematics; Neural networks; PD control; Torque control;
Conference_Titel :
Intelligent Control, 1991., Proceedings of the 1991 IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-0106-4
DOI :
10.1109/ISIC.1991.187357
