Prescribed-Time-Based Anti-Disturbance Tracking Control of Manipulators Under Multiple Constraints

Manipulators have a wide range of applications in industrial automation. However, their nonlinear characteristics, time-varying properties, and external disturbances present significant challenges in accurately tracking their trajectories. This paper proposes an integrated control strategy based on prescribed-time convergence control, output constraint control, prescribed performance control (PPC), and an extended state observer (ESO)-based anti-disturbance control method. The prescribed-time convergence control guarantees that the system will reach a steady state at a specified time, while the output constraint control ensures that the Vm will move within a predefined physical range. The PPC meets the rigorous requirements of error convergence during trajectory tracking by regulating the error dynamics, while the ESO is employed to estimate unknown disturbances and enhance the system’s resilience to interference. The simulation outcomes demonstrate that the proposed control methodology exhibits notable advantages in terms of a rapid response, precision tracking, and anti-disturbance capabilities.