TY - GEN
T1 - Neural network observer based optimal tracking control for multi-motor servomechanism with backlash
AU - Wang, Minlin
AU - Ren, Xuemei
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2016.
PY - 2016
Y1 - 2016
N2 - In this paper, a new neural network observer based optimal tracking control is presented to attenuate the effect of backlash and other uncertainty for the position tracking of multi-motor servomechanism (MMS). By adopting a continuously differentiable function instead of the non-differential dead-zone model of the backlash, the state space representation of MMS is set up by using a linear part of the differentiable function. Based on the state space representation, the optimal neural network (NN) observer is used to estimate the uncertainties and unmeasured states, which combines with the optimal state feedback to synthesis the actual control law. Finally, Lyapunov theory is utilized to certify that the tracking error, the observed error and neural network weights are all semi-globally uniformly ultimately bounded (SGUUB). Simulation results validate the effectiveness of this method.
AB - In this paper, a new neural network observer based optimal tracking control is presented to attenuate the effect of backlash and other uncertainty for the position tracking of multi-motor servomechanism (MMS). By adopting a continuously differentiable function instead of the non-differential dead-zone model of the backlash, the state space representation of MMS is set up by using a linear part of the differentiable function. Based on the state space representation, the optimal neural network (NN) observer is used to estimate the uncertainties and unmeasured states, which combines with the optimal state feedback to synthesis the actual control law. Finally, Lyapunov theory is utilized to certify that the tracking error, the observed error and neural network weights are all semi-globally uniformly ultimately bounded (SGUUB). Simulation results validate the effectiveness of this method.
KW - Backlash compensation
KW - Multi-motor servomechanism
KW - Neural network
KW - Optimal state feedback
KW - Uncertainty estimation
UR - https://www.scopus.com/pages/publications/84952644456
U2 - 10.1007/978-3-662-48365-7_46
DO - 10.1007/978-3-662-48365-7_46
M3 - Conference contribution
AN - SCOPUS:84952644456
SN - 9783662483633
T3 - Lecture Notes in Electrical Engineering
SP - 453
EP - 462
BT - Proceedings of the 2015 Chinese Intelligent Systems Conference
A2 - Jia, Yingmin
A2 - Li, Hongbo
A2 - Du, Junping
A2 - Zhang, Weicun
PB - Springer Verlag
T2 - Chinese Intelligent Systems Conference, 2015
Y2 - 1 January 2015
ER -