Fuzzy Adaptive Predefined Time Control With Global Prescribed Performance for Robotic Manipulator Under Unknown Disturbance

Abstract

The assurance of faster transient response rate, higher steady-state tracking accuracy, and global adaptability are crucial for enhancing the efficiency and robustness of manipulators during operation. This article explores a novel fuzzy adaptive predefined-time controller based on global prescribed performance for robotic systems with unknown dynamics and bounded disturbances. First, a predefined time error transformation function (PTETF) is developed and combined with a barrier function based on constant value constraints for control design, which not only significantly simplifies the derivation process of the proposed predefined time prescribed performance control (PTPPC), but also equips it with the ability of global constraints on the trajectory tracking error. Then, we utilize the fuzzy logic system (FLS) with a single-parameter update mechanism to compensate for the dynamic uncertainty of manipulators, thereby reducing computational complexity and cost. In addition, a fixed time disturbance observer (FxTDOB) is introduced to alleviate the effect of nonparametric disturbances on the tracking performance. Further, by integrating the predefined time theory with Lyapunov method to ensure that all state signals of the controlled system converge in a predefined time. Finally, numerical simulations and practical experiments are carried out to demonstrate the effectiveness of the proposed framework.