Adaptive global predefined-time control of robotic systems with output constraints via multiple multidimensional Taylor network

Abstract

Adaptive global predefined-time control is examined for the $n$-link robotic system, which involves output constraints. The primary challenge in designing the controller is not only to guarantee that the output constraints are never violated, but also to achieve global convergence of the tracking error within a predefined time. First, a barrier function is introduced to transform the output constrained system into an unconstrained system. Then, the command filtering technique is incorporated into the adaptive multiple multidimensional Taylor network (MMTN) control process. Furthermore, a compensation system is constructed to alleviate for errors arising from filtering. Notably, the designed multi-switching-based adaptive MMTN controller realizes the global stability of robotic systems. Finally, a two-link robotic system simulation is presented to demonstrate the feasibility of the proposed control strategy.