Neuro‐adaptive fixed‐time trajectory tracking control for human‐in‐the‐loop teleoperation with mixed communication delays

Abstract

The fixed-time master–slave trajectory tracking control problem of the human-in-the-loop teleoperation systems with mixed communication delays (including time-varying delays and random delays), parametric uncertainties, and external disturbances is discussed in this study. Based on the non-singular terminal sliding mode control technique, a novel neuro-adaptive fixed-time control algorithm is designed to solve the above-mentioned problem. Moreover, to improve the steady-state performance of the presented control algorithm, the combination of the radial basis function neural networks, parametric adaptive laws and fixed-time control method is newly-designed and used to reduce the effects of parametric uncertainties and external disturbances. By employing the Lyapunov argument, the sufficient conditions on the control parameters for guaranteeing the fixed-time stability of the controlled teleoperation system are derived. Besides, the authors also present the upper bound of the settling time and prove that it is independent of the initial condition. Finally, several simulation examples are performed to verify the effectiveness of the theoretical results.