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Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

机译:基于Backstepping设计的近空高超声速飞行器再入姿态自适应滑模控制

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摘要

Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.
机译:结合滑模控制方法和径向基函数神经网络(RBFNN),提出了一种基于反演设计的鲁棒自适应控制方案,用于在参数变化和外部条件下对近空高超声速飞行器(NSHV)的再入姿态跟踪控制。干扰。在姿态角环中,通过自适应方法设计了鲁棒的自适应虚拟控制律,以估计复合不确定性的未知上限。在角速度环路中,设计了自适应滑模控制定律以抑制参数变化和外部干扰的影响。滑模控制的主要好处是对参数变化和外部干扰具有鲁棒性。为了进一步提高控制性能,引入了RBFNN,以分别近似估计姿态角环和角速度环中的复合不确定性。基于李雅普诺夫稳定性理论,跟踪误差被证明是渐近稳定的。仿真结果表明,所提出的控制系统具有令人满意的控制性能,并且对参数变化和外部干扰具有鲁棒性。

著录项

  • 来源
    《自动化学报:英文版》 |2015年第001期|P.94-101|共8页
  • 作者单位

    the Flight Control Research Center, Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University;

    the College of Information and Control, Nanjing University of Information Science & Technology;

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  • 正文语种 CHI
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