TY - GEN
T1 - Improved Q-Learning Control for Optimal Tracking of Underwater Vehicle Manipulator System
AU - Huang, Yanbin
AU - Tian, Xin
AU - Hameed Shah, Umer
AU - Wang, Hongdu
AU - Hou, Dongdong
AU - Li, Ming
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In this work, an improved Q learning control algorithm base on an extended state observer (ESO) is designed for an underwater vehicle manipulator system (UVMS). The UVMS is modeled as a nonlinear system with model uncertainties and external disturbances. In this paper, extended state observer (ESO) is constructed to evaluate the model uncertainties and external disturbances. In addition, an augmented system is constructed based on UVMS and reference signal. Furthermore, an improved Q learning control method is proposed to solve online the augmented algebraic Riccati equation (ARE) in the absence of the knowledge of the augmented system parameters. Finally, extensive numerical simulation results show that the effectiveness of the proposed optimal tracking control method for UVMS.
AB - In this work, an improved Q learning control algorithm base on an extended state observer (ESO) is designed for an underwater vehicle manipulator system (UVMS). The UVMS is modeled as a nonlinear system with model uncertainties and external disturbances. In this paper, extended state observer (ESO) is constructed to evaluate the model uncertainties and external disturbances. In addition, an augmented system is constructed based on UVMS and reference signal. Furthermore, an improved Q learning control method is proposed to solve online the augmented algebraic Riccati equation (ARE) in the absence of the knowledge of the augmented system parameters. Finally, extensive numerical simulation results show that the effectiveness of the proposed optimal tracking control method for UVMS.
KW - Q learning
KW - extended state observer (ESO)
KW - optimal tracking control
KW - underwater vehicle manipulator system (UVMS)
UR - https://www.scopus.com/pages/publications/85185221010
U2 - 10.1109/NTCI60157.2023.10403725
DO - 10.1109/NTCI60157.2023.10403725
M3 - Conference contribution
AN - SCOPUS:85185221010
T3 - Proceedings of 2023 International Conference on New Trends in Computational Intelligence, NTCI 2023
SP - 127
EP - 131
BT - Proceedings of 2023 International Conference on New Trends in Computational Intelligence, NTCI 2023
A2 - Wang, Jian
A2 - Polycarpou, Marios M.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on New Trends in Computational Intelligence, NTCI 2023
Y2 - 3 November 2023 through 5 November 2023
ER -