Adaptive prescribed settling time periodic event-triggered control for uncertain robotic manipulators with state constraints

Abstract

In this paper, an adaptive prescribed settling time periodic event-triggered control (APST-PETC) is investigated for uncertain robotic manipulators with state constraints. In order to economize network bandwidth occupancy and reduce computational burden, a periodic event-triggered control (PETC) strategy is proposed to reduce the update frequency of the control signal and avoid unnecessary continuous monitoring. Besides, considering that the maneuverable space of the actual robotic manipulators is often limited, the barrier Lyapunov function (BLF) is applied to deal with the influence of the constraint characteristics on the robotic manipulators. Further, based on the one-to-one nonlinear mapping function of the system tracking error, an adaptive prescribed settling time control (APSTC) is designed to ensure that the system tracking error reaches the predetermined precision residual set within the prescribed settling time. Finally, theoretical analysis and comparative experiments are given to verify its feasibility.