TY - GEN
T1 - Reinforcement Learning based Optimal Tracking Control for Hypersonic Flight Vehicle
T2 - 20th IEEE International Conference on Industrial Informatics, INDIN 2022
AU - Hu, Xiaoxiang
AU - Dong, Kejun
AU - Yang, Teng
AU - Xiao, Bing
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The tracking control of hypersonic flight vehicle (HFV) is discussed in this paper, and the nonlinear model of HFV is assumed to be completely unknown. This problem is surely challenging because of the missing prior knowledge, but is more closer to reality since the exact mode of HFV is difficult to be obtained. A reinforcement learning (RL) based optimal controller is proposed for the tracking control of HFV. A model based RL algorithm is firstly proposed and then, based on this algorithm, a model free algorithm is constructed. For relaxing the environmental conditions, neural network (NN) is adopted for the approximation of Critic and Actor, and then a Greedy Policy based updated learning law for NN is derived. The presented RL based control strategy is carried on the nonlinear model of HFV to show its effectiveness.
AB - The tracking control of hypersonic flight vehicle (HFV) is discussed in this paper, and the nonlinear model of HFV is assumed to be completely unknown. This problem is surely challenging because of the missing prior knowledge, but is more closer to reality since the exact mode of HFV is difficult to be obtained. A reinforcement learning (RL) based optimal controller is proposed for the tracking control of HFV. A model based RL algorithm is firstly proposed and then, based on this algorithm, a model free algorithm is constructed. For relaxing the environmental conditions, neural network (NN) is adopted for the approximation of Critic and Actor, and then a Greedy Policy based updated learning law for NN is derived. The presented RL based control strategy is carried on the nonlinear model of HFV to show its effectiveness.
KW - Hypersonic flight vehicles (HFV)
KW - Model free
KW - reinforcement learning(RL)
UR - http://www.scopus.com/inward/record.url?scp=85145770052&partnerID=8YFLogxK
U2 - 10.1109/INDIN51773.2022.9976071
DO - 10.1109/INDIN51773.2022.9976071
M3 - 会议稿件
AN - SCOPUS:85145770052
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 711
EP - 717
BT - 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 July 2022 through 28 July 2022
ER -