Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

被引:0
|
作者
Wenxue Chen
Yudong Hu
Changsheng Gao
Ruoming An
机构
[1] School of Astronautics
[2] Harbin Institute of Technology
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TJ765 [制导与控制];
学科分类号
081105 ;
摘要
This paper investigates interception missiles’ trajectory tracking guidance problem under wind field and external disturbances in the boost phase. Indeed, the velocity control in such trajectory tracking guidance systems of missiles is challenging. As our contribution, the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy. The global prescribed performance function, which guarantees the tracking error within the set range and the global convergence of the tracking guidance system, is first proposed based on the traditional PPF. Then, a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities. Meanwhile, an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem. A back propagation neural network(BPNN) extended state observer(BPNNESO) is employed in the inner loop to identify disturbances. The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors, convergence times, and overshoots.
引用
收藏
页码:412 / 429
页数:18
相关论文
共 50 条
  • [41] Sliding mode control of AUV trajectory tracking in the presence of disturbance
    Jalalnezhad, Mostafa
    Fazeli, Sadegh
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING, 2023,
  • [42] Neural Network Control of Underactuated Surface Vehicles With Prescribed Trajectory Tracking Performance
    Zhang, Jin-Xi
    Yang, Tao
    Chai, Tianyou
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (06) : 8026 - 8039
  • [43] Adaptive neural network sliding mode tracking control with prescribed performance for an underwater glider under input saturation
    Zhang, Xu
    Yao, Baoheng
    Lian, Lian
    Mao, Zhihua
    OCEAN ENGINEERING, 2024, 307
  • [44] Trajectory Tracking Control of Remotely Operated Vehicles via a Fast-Sliding Mode Controller with a Fixed-Time Disturbance Observer
    Zhou, Huadong
    Mu, Xiangyang
    APPLIED SCIENCES-BASEL, 2024, 14 (06):
  • [45] Disturbance-Observer-Based Terminal Sliding Mode Control for Linear Traction System With Prescribed Performance
    Ding, Bo
    Xu, Dezhi
    Jiang, Bin
    Shi, Peng
    Yang, Weilin
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2021, 7 (02) : 649 - 658
  • [46] Integral Sliding Mode Control Using a Disturbance Observer for Vehicle Platoons
    Wang, Jianmei
    Luo, Xiaoyuan
    Wang, Li
    Zuo, Zhiqiang
    Guan, Xinping
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (08) : 6639 - 6648
  • [47] Integral Adaptive Sliding Mode Control for Vehicle Platoon with Disturbance Observer
    Yang, Xin
    Liu, Cheng-Lin
    2024 3RD CONFERENCE ON FULLY ACTUATED SYSTEM THEORY AND APPLICATIONS, FASTA 2024, 2024, : 365 - 370
  • [48] Performance-guaranteed fractional-order sliding mode control for underactuated autonomous underwater vehicle trajectory tracking with a disturbance observer
    Rong, Shaowei
    Wang, Huigang
    Li, Huiping
    Sun, Weitao
    Gu, Qingyue
    Lei, Juan
    OCEAN ENGINEERING, 2022, 263
  • [49] Indirect neural-based finite-time integral sliding mode control for trajectory tracking guidance of Mars entry vehicle
    Yao, Qijia
    Jahanshahi, Hadi
    Moroz, Irene
    Bekiros, Stelios
    Alassafi, Madini O.
    ADVANCES IN SPACE RESEARCH, 2023, 71 (09) : 3723 - 3733
  • [50] Performance-guaranteed fractional-order sliding mode control for underactuated autonomous underwater vehicle trajectory tracking with a disturbance observer
    Rong, Shaowei
    Wang, Huigang
    Li, Huiping
    Sun, Weitao
    Gu, Qingyue
    Lei, Juan
    Ocean Engineering, 2022, 263