Observer-based optimal control method combination with event-triggered strategy for hypersonic morphing vehicle

被引:9
作者
Bao, Cunyu [1 ]
Wang, Peng [1 ]
He, Ruizhi [1 ]
Tang, Guojian [1 ]
机构
[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Peoples R China
基金
中国国家自然科学基金;
关键词
Hypersonic morphing vehicle; Event-triggered; Adaptive dynamic programming; Fuzzy disturbance observer; SLIDING MODE CONTROL; DISTURBANCE OBSERVER; TRACKING CONTROL; SYSTEMS; STABILIZATION; FEEDBACK;
D O I
10.1016/j.ast.2023.108219
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
A morphing-attitude coupling control method based on event-triggered adaptive dynamic programming (ETADP) and a finite-time fuzzy disturbance observer (FTFDO) is proposed for a class of hypersonic morphing vehicle (HMV). Firstly, an attitude-morphing coupled dynamic model is established, and the morphing variable is treated as the state for integrated control with attitude. The control law is updated by an event-triggered mechanism, which is designed in two parts: feedforward control and feedback control. Based on the proposed FTFDO, the matched and mismatched uncertainties are estimated and compensated in finite time to solve the feedforward control input. Based on an adaptive dynamic programming algorithm, Critic-Actor dual networks are constructed to implement policy iteration for an approximate optimal feedback control policy by offline training with exploration. The Critic-Actor dual networks then adopt the ETADP algorithm to tune the weight of the networks online when triggering criteria for policy improvement are met. Event-triggered conditions are developed such that the feedforward control and feedback control are both updated by aperiodic sampling, reducing the number of controller updates required. Zeno behavior is avoided by determining the minimum sampling interval time. The stability of the closed-loop system is demonstrated theoretically. Simulation results verify the control efficiency and robustness of the proposed method.(c) 2023 Elsevier Masson SAS. All rights reserved.
引用
收藏
页数:21
相关论文
共 37 条
  • [11] Design and aerodynamic performance analysis of a variable-sweep-wing morphing waverider
    Dai, Pei
    Yan, Binbin
    Huang, Wei
    Zhen, Yifei
    Wang, Mingang
    Liu, Shuangxi
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2020, 98 (98)
  • [12] Event-triggered-based adaptive dynamic programming for distributed formation control of multi-UAV
    Dou, Liqian
    Cai, Siyuan
    Zhang, Xiuyun
    Su, Xiaotong
    Zhang, Ruilong
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2022, 359 (08): : 3671 - 3691
  • [13] Greene M.L., 2022, AIAA SCITECH 2022 FO
  • [14] Online policy iteration ADP-based attitude-tracking control for hypersonic vehicles
    Han, Xiao
    Zheng, Zongzhun
    Liu, Lei
    Wang, Bo
    Cheng, Zhongtao
    Fan, Huijin
    Wang, Yongji
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2020, 106
  • [15] Robust Adaptive Dynamic Programming and Feedback Stabilization of Nonlinear Systems
    Jiang, Yu
    Jiang, Zhong-Ping
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (05) : 882 - 893
  • [16] Khalil H., 2002, NONLINEAR SYSTEMS, V3
  • [17] Reinforcement learning solution for HJB equation arising in constrained optimal control problem
    Luo, Biao
    Wu, Huai-Ning
    Huang, Tingwen
    Liu, Derong
    [J]. NEURAL NETWORKS, 2015, 71 : 150 - 158
  • [18] Adaptive model-free fault-tolerant control based on integral reinforcement learning for a highly flexible aircraft with actuator faults
    Ma, Jianjun
    Peng, Chi
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2021, 119
  • [19] Intelligent data-driven aerodynamic analysis and optimization of morphing configurations
    Magalhaes Junior, Jose M.
    Halila, Gustavo L. O.
    Kim, Yoobin
    Khamvilai, Thanakorn
    Vamvoudakis, Kyriakos G.
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2022, 121
  • [20] Fuzzy Disturbance Observer-Based Adaptive Sliding Mode Control for Reusable Launch Vehicles With Aeroservoelastic Characteristic
    Mao, Qi
    Dou, Liqian
    Yang, Zhenshu
    Tian, Bailing
    Zong, Qun
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (02) : 1214 - 1223