姿态受控柔性臂空间机器人的自适应神经网络容错控制及残振抑制

Adaptive neural network fault-tolerant control and residual vibration suppression for flexible-arm space robot with attitude-controlled base

针对执行器发生部分失效故障的漂浮基姿态受控柔性臂空间机器人系统,研究了执行器故障的容错控制及柔性臂杆残余振动的主动抑制。结合假设模态法、线动量守恒定理和第二类拉格朗日方程建立了系统的动力学微分方程。基于奇异摄动理论将系统分解为一个表征载体姿态与关节轨迹跟踪的慢变子系统和一个表征柔性臂杆残余振动的快变子系统;据此设计了由慢变子系统的自适应神经网络容错控制器与快变子系统的线性二次型最优调节器组成的复合控制器;其中,慢变子系统的容错控制器使得系统对执行器故障不敏感,保证了跟踪误差的渐进收敛;快变子系统的最优调节器可以有效地抑制柔性臂杆引起的残余振动,减少能量损耗。对比数值仿真校验了理论推导的正确性与复合控制策略的可行性。

Aiming at the space robot system of floating-based attitude-controlled flexible arm with partial actuator failure,the fault-tolerant control of actuator fault and the active suppression of residual vibration of flexible arm were studied.The dynamic differential equation of the system was established by combining the assumed mode method,the conservation theorem of linear momentum and the Lagrangian equation of the second kind.Based on the singular perturbation theory,the system was decomposed into a slow-varying subsystem representing the attitude of the base and joint trajectory tracking and a fast-varying subsystem representing the residual vibration of the flexible arm.Based on this,a compound controller was designed,which is composed of an adaptive neural network fault-tolerant controller of the slow-varying subsystem and a linear quadratic optimal regulator of the fast-varying subsystem.The fault-tolerant controller of the slow-varying subsystem makes the system insensitive to actuator faults and ensures the asymptotic convergence of the tracking error;the optimal regulator of the fast-varying subsystem can effectively restrain the residual vibration caused by the flexible arm and reduce the energy loss.The correctness of the theoretical derivation and the feasibility of the compound control strategy are verified by numerical simulation.