Train automatic driving track planning and tracking integrated control method and device

Abstract

The invention relates to a train automatic driving trajectory planning and tracking integrated control method, which comprises the following steps of: A, analyzing the stress condition of a train and the response process of coupler force and acceleration between parking spaces to a control command, and establishing a kinematics differential equation set model based on a multi-mass-point model; b, controlled train objects are grouped, and a double-closed-loop controller structure composed of a planning ring with an outer ring being model prediction control and a tracking ring with an inner ring being sliding mode control is constructed; c, establishing a quadratic form planning model considering multiple indexes such as tracking errors, coupler force and control smoothness, and solving the quadratic form planning model; and D, smoothing a model prediction solving result by using a tracking differentiator, and outputting the smoothed model prediction solving result to a sliding-mode control tracking ring for train speed and acceleration tracking. Compared with the prior art, the method has the advantages that tracking control is easy, and the ATO driving quality is improved.

Description

technical field [0001] The invention relates to a rail transit train signal control system, in particular to an integrated control method and device for train automatic driving trajectory planning and tracking. Background technique [0002] At present, the automatic train operation (ATO) technology is mostly used in the field of urban rail transit, and the controlled trains are fixed-arranged power-distributed EMU trains. For the power-concentrated trains pulled by locomotives, there is currently no practical application for passenger and cargo transportation operations. [0003] Different from the power-distributed EMU trains with fixed marshalling, the power-concentrated trains pulled by locomotives need to consider the coupler force between cars during the control process, and the response of train acceleration to control commands is slow, which has strong nonlinearity and large The characteristics of inertia and large time lag. If it is similar to the subway ATO system...

AI Technical Summary

Problems solved by technology

At the same time, due to the fact that there are many variable parameters in the train formation, traction quality, and number of locomotives during the operation of the power-concentrated train towed by locomotives, it is difficult to deal with the above variable factors if the reference speed curve is stored in an offline preset method. Lack of flexibility and real-time

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