This paper studies a novel adaptive fractional-order non-singular terminal sliding mode (FO-NTSM) control strategy for omnidirectional mobile robot manipulator (OMRM) with unknown parameters and external disturbances. Firstly, we adopt the fuzzy wavelet neural networks (FWNNs) to estimate the dynamic uncertainty of the OMRM because it has superior function approximation capability. Secondly, we design the adaptive NTSM controller to attenuate external disturbances by virtue of adjusting the weights of the FWNNs online. Moreover, we obtain a fractional-order (FO) control criterion, which speed up the convergence of the algorithm. In addition, we prove the globally robust stability of the OMRM control system through a designed Lyapunov function. Finally, simulation and experiment researches indicate the feasible and validity of the presented method.

本文研究了一种新的自适应分数阶非奇异终端滑模（FO-NTSM）控制策略，用于具有未知参数和外部干扰的全向移动机器人机械臂（OMRM）。首先，我们采用模糊小波神经网络（FWNNs）来估计 OMRM 的动态不确定性，因为它具有优越的函数逼近能力。其次，我们设计了自适应 NTSM 控制器，通过在线调整 FWNN 的权重来衰减外部干扰。此外，我们获得了分数阶（FO）控制准则，加快了算法的收敛速度。此外，我们通过设计的 Lyapunov 函数证明了 OMRM 控制系统的全局鲁棒稳定性。最后，仿真和实验研究表明了所提方法的可行性和有效性。