Subway train speed automatic control method based on second-order ADRC algorithm

Abstract

The invention provides a subway train speed automatic control method based on a second-order ADRC algorithm. The method comprises the following steps of: arranging a transition process from the running target speed of the train through a tracking differentiator, extracting a differential signal and then acquiring a tracking speed and a tracking acceleration, acquiring an observation disturbance, an observation speed and an observation acceleration after the actual running speed of the train passes through an extended state observer to estimate the state of an object and the uncertain disturbance effect, and processing the tracking speed error and the tracking acceleration error through a nonlinear feedback link to obtain an output quantity, and subtracting the product of the observation disturbance and the reciprocal of the system gain from the output quantity to obtain a system control quantity. the system control quantity is converted to a control force of a mathematical model of thetrain, and the control force is outputted to the mathematical model of the train. According to the method, the speed tracking error is corrected by combining the advantages of the ADRC algorithm, sothat the speed tracking error is reduced, the train is controlled more accurately, and the train can run more stably.

Description

technical field [0001] The invention relates to the technical field of urban rail transit control, in particular to an automatic control method for subway train speed based on a second-order ADRC (active disturbance rejection control) algorithm. Background technique [0002] With the continuous increase of the urbanization rate in our country, the population of modern metropolises is becoming more and more dense, and the urban traffic problems are becoming more and more severe. It is an urgent need to build a high-efficiency, high-density and high-reliability urban rail transit system. In order to meet these requirements, ATO (automatic train operation, train automatic driving) is essential. The use of excellent train driving control algorithms can effectively improve driving safety, improve efficiency, increase density, increase passenger comfort, reduce driver human control uncertainty, and reduce driver labor intensity. Proportion integration differentiation (PID) contro...

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Problems solved by technology

[0003] However, there are large randomness in the operation parameters and various disturbances during the operation of the subway train, and the train controller based on the PID algorithm cannot adapt to this disturbance well, so that in the actual control of the train, the train driving strategy often appears frequent Adjustment, too many acceleration and deceleration switching times and serious overshooting problems make it difficult for the train to run smoothly and reduce the comfort of passengers

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