TY - JOUR
T1 - Neuro-adaptive control with application to robotic systems
AU - SONG, Y. D.
PY - 1997/6
Y1 - 1997/6
N2 - This article presents a highly model-independent neural network (NN)-based adaptive control method for a class of nonlinear dynamic systems. Two NN units are incorporated into the control scheme which are shown to be effective in attenuating NN reconstruction error and other lumped system uncertainties. Because the control scheme is based on the worst case behavior of the NNs, it exhibits a "fail-safe" feature, which enhances the reliability of the NN-based control scheme. Stable on-line weight-tuning algorithms are derived based on Lyapunov stability theory. The control method is extended to robotic systems and simulation on a three-joint robot is presented. © 1997 John Wiley & Sons. Inc.
AB - This article presents a highly model-independent neural network (NN)-based adaptive control method for a class of nonlinear dynamic systems. Two NN units are incorporated into the control scheme which are shown to be effective in attenuating NN reconstruction error and other lumped system uncertainties. Because the control scheme is based on the worst case behavior of the NNs, it exhibits a "fail-safe" feature, which enhances the reliability of the NN-based control scheme. Stable on-line weight-tuning algorithms are derived based on Lyapunov stability theory. The control method is extended to robotic systems and simulation on a three-joint robot is presented. © 1997 John Wiley & Sons. Inc.
UR - https://www.scopus.com/pages/publications/0031166158
U2 - 10.1002/(SICI)1097-4563(199706)14:6<433::AID-ROB5>3.0.CO;2-P
DO - 10.1002/(SICI)1097-4563(199706)14:6<433::AID-ROB5>3.0.CO;2-P
M3 - Journal Article (refereed)
AN - SCOPUS:0031166158
SN - 1556-4959
VL - 14
SP - 433
EP - 447
JO - Journal of Field Robotics
JF - Journal of Field Robotics
IS - 6
ER -