空间连续型机器人自适应鲁棒容错控制

Aiming at the problem of concurrent faults of actuators in three-arm segments of a spatially continuous robot system, an adaptive robust fault-tolerant control algorithm is proposed. A non-singular fast terminal sliding mode controller is adopted, and the gain of the switching term of the controller is adjusted online by an adaptive RBF (Radial Basis Function) neural network, so that the controller still has high tracking accuracy and strong robustness under model parameter perturbations and external disturbances. Based on the Lyapunov stability theory, it is proved that this controller can ensure the asymptotic stability of the entire system. The simulation results verify the effectiveness of the algorithm in this paper.

针对空间连续型机器人系统三臂节执行器并发故障的问题,提出一种自适应鲁棒容错控制算法。采用非奇异快速终端滑模控制器,并通过自适应RBF(Radial Basis Function)神经网络在线调整控制器的切换项增益,使控制器在模型参数摄动和外部干扰下依旧具有较高的跟踪精度和较强的鲁棒性。基于Lyapunov稳定性理论,证明了该控制器可以保证整个系统的渐进稳定性。仿真结果验证了本文算法的有效性。