Finite-time composite prescribed performance synchronization control for double-lift spreaders of overhead cranes

This paper investigates the finite-time synchronization control issue for double-lift spreaders of overhead cranes subject to unknown disturbances and actuator saturation constraint, and proposes a composite predefined performance sliding mode control scheme. Firstly, predefined performance functions are utilized to construct performance constraints for both tracking error and synchronization error, ensuring that the system error can converge to predefined steady-state boundaries within a prescribed time. Meanwhile, an adaptive composite reaching law (ACRL) is designed based on the convergence dynamics of the system error and its approximation dynamics towards the prescribed performance functions, to reduce the peak of system error and suppress chattering. In addition, this paper employs the hyperbolic tangent function to replace the saturation function in constructing input saturation constraint, thereby limiting the output of the control system. The resulting control output limiting error, along with the unknown disturbances and unmodeled dynamics present in the system, is collectively treated as a lumped disturbance, which is estimated and compensated by the adaptive brain emotional learning observer. The adaptive brain emotion learning observer (ABELO) can adaptively adjust the learning rates according to the convergence dynamics of system error, thereby further improving the estimation accuracy and response speed of unknown dynamics and reducing the influence of residual unknown dynamics on the system. Finally, the stability of the closed-loop system is proven using Lyapunov stability theory. Also, the finite-time convergence of the system error with respect to the prescribed performance functions is confirmed. Simulation experiments are conducted to verify the effectiveness of the proposed synchronization control scheme.