Disturbance observer-based dynamic fuzzy sliding-mode control strategy for horizontal vibration of high-speed elevator car system

To effectively suppress the horizontal vibration of high-speed elevator cars caused by uncertainties such as unevenness of guide rails and piston wind in the shaft, a disturbance observer-based dynamic fuzzy sliding-mode control strategy is proposed, which is a combination of a dynamic fuzzy sliding-mode controller and an optimal nonlinear disturbance observer. First, a horizontal vibration dynamics model of the semi-active high-speed elevator car system is established, and the external disturbance of the airflow obtained by the dynamic grid technique and the uneven excitation of the guide rail are jointly applied as inputs to the dynamical model. Then, an active fuzzy sliding-mode controller is established, approximating the local optimum of the sliding mode surface parameters using a differential evolutionary algorithm, and the sliding mode surface is fuzzified to estimate the switching gain dynamically; next, a disturbance observer is designed by the response of the semi-active car system dynamics model to monitor and estimate the unpredictable state and compensate for the effect of external disturbances on the car system. The stability analysis shows that making the system's dynamic response converge at the origin is a Lyapunov stable process. In addition, real elevator experiments are conducted to analyze the horizontal vibration characteristics of the car system and verify the model. Finally, considering the limitations of actuators in real conditions, the simulation experiments are carried out under random excitation and pulse excitation respectively, and their results show that the proposed control strategy reduces the root mean square value of vibration acceleration by more than 70% and the output active control force is more stable, indicating that the proposed control strategy can effectively suppress the horizontal vibration of high-speed elevators.