Predefined-Time Robust Kinematic Control of Redundant Manipulators

In this article, a predefined-time robust kinematic control (PTRKC) scheme is proposed, which can effectively solve the kinematic uncertainty and noise problems. The convergence time of the system is independent of the initial state and control gain, and the manipulator can complete adjustment within the predefined time. To this end, a nonsingularity sliding variable is first designed and treated as an equality criterion. Meanwhile, the predefined time convergence property of the controller in reaching and sliding stages is rigorously proved based on the Lyapunov theory. Additionally, a dedicated recurrent neural network is also developed to address the PTRKC scheme. Finally, the performance of the proposed scheme is supported by the trajectory tracking experiment.