Adaptive Dynamic Threshold Event‐Triggered Fixed‐Time Control for Multiple Uncertain Robotic Manipulators With Position Constraints

ABSTRACT In this paper, an adaptive dynamic threshold event‐triggered fixed‐time control is proposed for multiple uncertain robotic manipulators with position constraints on the basis of a dynamic gain function. First, a novel dynamic threshold fixed‐time prescribed performance control (DFTPPC) strategy that mixes a time‐varying function with fixed‐time prescribed performance control, which allows the error to be reduced again, is designed. On this basis, the barrier Lyapunov function (BLF) is designed in combination with the hyperbolic tangent function to obtain the system state constraints. Second, the dynamic gain function (DGF) is designed to improve the sensitivity of the error in the feedback control and the anti‐interference ability of the system. Third, a dynamic event‐triggered mechanism (DETM) is designed by incorporating a time‐varying scaling function and an exponentially decreasing term to not only reduce communication resources but also achieve stronger robustness. Finally, an analysis of the theory and comparative simulation experiments verifies that the proposed strategy is feasible.