Iterative learning-based adaptive disturbance rejection control method for the 3D overhead crane system with time-varying rope length

An iterative learning-based adaptive disturbance rejection control (ADRC) method is proposed to tackle control issues for three-dimensional (3D) overhead crane. The tracking differentiator (TD) and extended state observer (ESO) are employed to extract desired displacement and estimate system disturbances. A robust iterative learning control (ILC) law is constructed by integrating sliding mode control (SMC) with ILC. The stability of the closed-loop system is proved through Lyapunov stability theory, and simulations are conducted to verify the effectiveness and robustness of the proposed method.