Improved nonlinear active disturbance rejection control based on hierarchical expected improvement for high-speed elevator horizontal vibration suppression

In this paper, an improved NADR control method based on hierarchical expected improvement (HEI) optimization is studied to suppress the horizontal vibration of high-speed elevator car under complex coupled disturbances to improve high-speed elevator ride comfort. First, a nonlinear 8-DOF dynamic model for the horizontal vibration of the high-speed elevator car is constructed. Then, a 4-level parallel NADR main control system based on the fal-function is designed to observe the total disturbance in real time, which can be quickly compensated by fuzzy sliding mode control. Meanwhile, the adaptive law is used to adjust fuzzy rules and sliding mode switching term coefficients to ensure the stability and adaptability of the control system. To address the problem of multiple bandwidth parameters and high sensitivity of the observer in the NADR control system, the comprehensive RMS experimental data fusion model based on hierarchical Gaussian process is constructed. With the goal of achieving the optimal value of comprehensive RMS, a hierarchical expectation improvement search strategy that balances exploratory and developmental aspects is studied to improve the optimization accuracy of bandwidth parameters. Finally, the results show that the proposed method can reduce the horizontal vibration acceleration and tilt angle acceleration of the car system by more than 68%.