Adaptive fractional-order non-singular terminal sliding mode control based on fuzzy wavelet neural networks for omnidirectional mobile robot manipulator

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.