TY - GEN
T1 - Intelligent control of space robot system using RBF neural network
AU - Kumar, Naveen
AU - Panwar, Vikas
N1 - Publisher Copyright:
© 2015 Institute of Control, Robotics and Systems - ICROS.
PY - 2015/12/23
Y1 - 2015/12/23
N2 - In this paper, an intelligent controller is proposed for a space robot system with an attitude controlled base without joint acceleration measurements. The controller consists of computed torque type part, RBF neural network and an adaptive controller. The controller achieves the required tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the space robot system dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally numerical simulation studies are performed to evaluate the controller performance.
AB - In this paper, an intelligent controller is proposed for a space robot system with an attitude controlled base without joint acceleration measurements. The controller consists of computed torque type part, RBF neural network and an adaptive controller. The controller achieves the required tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the space robot system dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally numerical simulation studies are performed to evaluate the controller performance.
UR - https://www.scopus.com/pages/publications/84966263921
UR - https://www.scopus.com/pages/publications/84966263921#tab=citedBy
U2 - 10.1109/ICCAS.2015.7364900
DO - 10.1109/ICCAS.2015.7364900
M3 - Conference contribution
AN - SCOPUS:84966263921
T3 - ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
SP - 167
EP - 172
BT - ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Control, Automation and Systems, ICCAS 2015
Y2 - 13 October 2015 through 16 October 2015
ER -