Research on Estimation Method of Rail Vehicle Information Under Noise Interference
Precise and reliable rail vehicle status and route information serve as critical input signals for the active control system of rail vehicles and are also essential for fault detection in rail vehicles.To address the challenge of acquiring the necessary information for active control of rail vehicles,a novel method for estimating vehicle status and unknown inputs for independently wheeled vehicles under the influence of noise disturbances is proposed.Firstly,to mitigate the impact of measurement noise disturbances,the system's measurement outputs are reconstructed and a novel reduced-order observer is devised.Subsequently,based on the estimated state information from the previous step,the unknown inputs are reconstructed,specifically estimating the route curvature.The rail vehicle model is then built in MATLAB/SIMULINK,and real-world signal simulations are performed by introducing noise disturbances into the signals.Finally,the estimation method is validated through simulations by comparing the estimated rail vehicle states and route curvature information under different types and levels of noise with the actual states.The results demonstrate that even in the presence of measurable/random noise disturbances,the proposed estimation method performs well in estimating rail vehicle status and route curvature information.Compared to other information estimation techniques,this method requires only the measurement of the left and right wheel speeds,which necessitates fewer sensors that are already widely installed,making it valuable for active control of rail vehicles.
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