Title :
A neurocontroller for robot manipulators
Author :
Derbal, Y. ; Bayoumi, M.M.
Author_Institution :
Dept. of Electr. Eng., Queen´´s Univ., Kingston, Ont., Canada
Abstract :
Feedforward neural networks have been proven to be capable of approximating nonlinear mappings on compact sets. This property has been used in the design of a large number of robot controllers. The overwhelming majority of these NN based robot controllers lack any substantial stability analysis. We propose a neurocontroller where: the unmodelled dynamics are considered; and the closed loop system is L∞ stable provided that certain m assumptions are satisfied
Keywords :
closed loop systems; feedforward neural nets; manipulators; neurocontrollers; robust control; closed loop system; compact sets; feedforward neural networks; neurocontroller; nonlinear mappings; robot controllers; robot manipulators; stability analysis; unmodelled dynamics; Actuators; Closed loop systems; Equations; Feedforward neural networks; Manipulators; Neural networks; Neurocontrollers; Robot control; Stability analysis; Vectors;
Conference_Titel :
Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
Conference_Location :
Le Touquet
Print_ISBN :
0-7803-0911-1
DOI :
10.1109/ICSMC.1993.390688
