Background

Since there is a dynamic coupling effect between the space manipulator and the base, the motion of the space manipulator will inevitably lead to the elastic vibration of the base. Due to the thin air and extreme environment in the space, the elastic vibration of the base decays slowly and the actuator is prone to the failure of efficiency loss, which will severely decrease the tracking accuracy and stability of the space robot. In addition, considering the design tolerances, installation deviations and frictions, the inertial parameters of the system are uncertain, which will also affect the control effect of the actuator. This research is dedicated to achieving high-accuracy and high-stability control of the elastic space robot with actuator faults and uncertain dynamics.

Methods

According to the linear momentum conservation law, the Langrangian dynamics equation of the system is established. Based on the singular perturbation theory, the dynamic model is decomposed into a slow-varying subsystem denoting the trajectory tracking motions of the base attitude and the joints and a fast-varying one denoting the nonlinear vibration of the elastic base. A hybrid controller consisted of a decentralized neural network fault-tolerant controller of the slow-varying subsystem and a proportion differentiation (PD) feedback controller of the fast-varying subsystem is formulated.

Conclusions

The neural network fault-tolerant controller of the slow-varying subsystem can compensate the unknown actuator faults and uncertain dynamics and obtain H∞ convergence performance, while the PD feedback controller of the fast-varying subsystem can damp out the residual vibration of the elastic base. Simulation results confirm the feasibility and effectiveness of the hybrid control strategy.

中文翻译：

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具有执行器故障和不确定动力学的弹性基础空间机器人的分散容错控制和振动抑制

背景

由于空间机械手与基座之间存在动态耦合效应，空间机械手的运动必然会导致基座的弹性振动。由于空间内空气稀薄和极端环境，基座的弹性振动衰减缓慢，致动器容易出现效率损失故障，这将严重降低空间机器人的跟踪精度和稳定性。此外，考虑到设计公差、安装偏差和摩擦等因素，系统的惯性参数是不确定的，也会影响执行器的控制效果。本研究致力于实现致动器故障和动态不确定的弹性空间机器人的高精度、高稳定性控制。

方法

根据线性动量守恒定律，建立系统的朗格朗日动力学方程。基于奇异摄动理论，将动力学模型分解为表示基座姿态和关节轨迹跟踪运动的慢变子系统和表示弹性基座非线性振动的快变子系统。设计了一种混合控制器，由慢变子系统的分散式神经网络容错控制器和快变子系统的比例微分（PD）反馈控制器组成。

结论

慢变子系统的神经网络容错控制器可以补偿未知的执行器故障和不确定的动力学，获得H∞收敛性能，而快变子系统的PD反馈控制器可以抑制弹性底座的残余振动. 仿真结果证实了混合控制策略的可行性和有效性。