Research on adaptive explicit distributed model predictive control strategy for horizontal vibration of high-speed elevator multi-agent car system

To solve the horizontal vibration problem of high-speed elevators caused by unevenness of guide rails and excitation of guide rail joints, considering the uncertainty of high-speed elevator parameters and multivariable coupling, an adaptive explicit distributed model predictive control strategy based on a multi-agent car system of high-speed elevators is proposed. First, the coupling constraints of high-speed elevator car are analyzed, and the horizontal vibration model of multi-agent car system is established. Second, the topology relationship of car multi-agent communication based on graph theory is analyzed, and the optimal control law of agent distribution model prediction is realized offline by multi-parameter programming technology. Meanwhile, by introducing a correction term with parameter estimation error, the uncertain parameter terms of the multi-agent car system can be estimated online. Design an adaptive explicit distributed model predictive control strategy for multi-agent car systems by combining offline collaborative distributed optimization with online uncertain parameter adaptive estimation. Finally, the time-domain and frequency-domain responses of high-speed elevator multi-agent car systems under two typical guide excitations are analyzed by simulation calculation and compared with the numerical results under passive control, adaptive control, and model predictive control. The results show that after the proposed control strategy is adopted, the mean horizontal vibration acceleration of the car system decreases by more than 48.4%, which further verifies the effectiveness of the proposed control strategy.