Conference Proceedings
Tracking improvement for stable robot control using neural networks
G Feng, M Palaniswami, ZX Han, CK Chak
IEEE International Conference on Neural Networks Conference Proceedings | Published : 1995
Abstract
This paper considers tracking control of robots in joint space. A new control algorithm is proposed based on the well known computed torque method and a compensating controller. The compensating controller is realized by using an switch-type structure and an RBF neural network. It is shown that stability of the closed loop system and better tracking performance can be established based on Lyapunov theory. Simulation results are also provided to support our analysis.