考虑预设性能约束的飞行器自适应神经网络姿态控制器

doi:10.12382/bgxb.2025.0401

摘要/Abstract

摘要：

针对存在模型不确定性的高速飞行器刚体动力学，考虑执行机构故障情况下的姿态预设性能控制问题，提出了一种基于自适应故障失效估计策略和有限时间预设性能控制的姿态控制器。采用动态有限时间预设性能控制和时变障碍Lyapunov控制技术，保证了姿态跟踪误差的瞬态性能及稳态的有限时间收敛；同时，采用径向基函数自适应神经网络对模型不确定性进行估计。引入指令滤波器，避免了对复杂虚拟控制量的直接求导。通过设计自适应算法，对模型逼近误差、外部扰动以及滤波器估计误差的上界进行估计和补偿。针对执行机构的故障失效问题，设计了自适应复合容错控制策略，有效补偿了执行机构失效的影响。基于Lyapunov理论，验证了闭环系统的半全局一致有界性。通过数值仿真实验，验证了所设计姿态控制器的有效性。

关键词: 高速飞行器姿态控制, 预设性能, 时变障碍Lyapunov, 模型不确定性, 自适应神经网络, 容错控制

Abstract:

In the presence of model uncertainties for the rigid body dynamics of high-speed vehicle ，and considering actuator faults，an attitude control strategy based on an adaptive fault estimation approach and an attitude controller for finite-time prescribed performance control are proposed by considering the attitude preset performance control under the condition of actuator failure.By employing the dynamic finite-time prescribed performance control and time-varying barrier Lyapunov control techniques，both the transient attitude tracking error performance and the finite-time convergence of steady-state errors are ensured.Moreover，a radial basis function neural network is used to estimate the model uncertainties.In addition，a command filter is introduced to avoid the direct differentiation of complex virtual control quantities.An adaptive algorithm is also designed to estimate and compensate for the upper bounds of model approximation errors，external disturbances，and command filter estimation errors.To address actuator faults，an adaptive composite fault-tolerant control strategy is proposed to effectively compensate for the impact of actuator fault.The semi-global uniform boundedness of the closed-loop system is verified based on Lyapunov theory.Finally，the effectiveness of the proposed attitude controller is verified through numerical simulation.

Key words: high-speed vehicle attitude control, prescribed performance control, time-varying barrier Lyapunov function, model uncertainty, adaptive neural network, fault-tolerance control

王伟, 刘佳琪, 林时尧, 朱泽军, 纪毅. 考虑预设性能约束的飞行器自适应神经网络姿态控制器[J]. 兵工学报, 2025, 46(S1): 250401-.

WANG Wei, LIU Jiaqi, LIN Shiyao, ZHU Zejun, JI Yi. Adaptive Neural Network-based Flight Vehicle Attitude Controller with Prescribed Performance Constraint[J]. Acta Armamentarii, 2025, 46(S1): 250401-.

图/表 6

图1 动态有限时间预设性能函数

Fig.1 The scheme of dynamic finite-time prescribed performance function

表1 HSV参数

Table 1 Parameters of high speed vehicle

变量	数值	变量	数值	变量	数值
S	0.42m²	J_z	5600kg·m²	${m}_{x}^{{\delta }_{x}}$	2.12
L	0.68m	${m}_{z}^{\alpha }$	-28.61	${c}_{y}^{\alpha }$	57.16
m	1200kg	${m}_{z}^{{\delta }_{z}}$	-27.92	${c}_{y}^{\beta }$	0.08
V	1000m/s	${m}_{y}^{\beta }$	-27.31	${c}_{y}^{{\delta }_{z}}$	5.74
ρ	1.1558kg/m³	${m}_{y}^{{\delta }_{y}}$	-26.57	${c}_{z}^{\alpha }$	-56.31
J_x	100kg·m²	${m}_{x}^{\alpha }$	0.46	${c}_{z}^{\beta }$	-5.62
J_y	5700kg·m²	${m}_{x}^{\beta }$	-0.37	${c}_{z}^{{\delta }_{z}}$	0.098

图2 角度跟踪实验仿真结果

Fig.2 Simulated results of attitude control performance test

图3 容错性能验证实验结果

Fig.3 Experimental results of fault-tolerant performance

图4 无故障与故障条件下能量消耗对比

Fig.4 Comparison of energy consumptions under fault-free and fault conditions

图5 对比实验

Fig.5 Comparison simulated results

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