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Multi-model adaptive pictorial information digitizer (PID) control of braking process of motor train unit

A braking process, EMU technology, applied in the direction of adaptive control, general control system, control/regulation system, etc.

Inactive Publication Date: 2013-05-08
EAST CHINA JIAOTONG UNIVERSITY
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Problems solved by technology

However, this method is based on the mechanism model of the braking process of high-speed trains, assuming that the basic resistance is constant, ignoring the fact that the resistance changes with the change of speed

Method used

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  • Multi-model adaptive pictorial information digitizer (PID) control of braking process of motor train unit
  • Multi-model adaptive pictorial information digitizer (PID) control of braking process of motor train unit
  • Multi-model adaptive pictorial information digitizer (PID) control of braking process of motor train unit

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Embodiment Construction

[0105] The implementation of the present invention selects the CRH380AL type EMU as the experimental verification object, and its main parameter characteristics are shown in Table 3. Collect 417 sets of speed and running distance data of the EMU during the braking process of a certain line section, and use 278 sets of data as modeling data samples, and the remaining 139 sets of data as test data.

[0106] Table 3 Main parameter characteristics

[0107]

[0108] First, according to the collected 1200 sets of modeling sample data, the optimal model number of the model can be determined to be 5 by subtractive clustering, and the model parameters are identified by the recursive least squares method. In order to verify the effectiveness of the model, the remaining 139 sets of operating data were used to test the established model, and then the multi-model switching strategy was used to select the model closest to the actual data at each sampling time. The results of multi-model ...

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Abstract

Disclosed is a fuzzy adaptive pictorial information digitizer (PID) control method of a motor train unit based on multi-model switch. According to the method, a data driving modeling method is proposed according to collected running process data of the motor train unit and field experience knowledge, the number of braking models is determined by means of subtraction cluster, and then a plurality of partial linear models describing a braking process of the motor train unit are established. The partial linear models adopt the recursive least-squares method to identify model parameters. At each sampling moment, an optimal partial model is selected based on the multi-model switch strategy, and the fuzzy adaptive PID control algorithm is adopted to control the braking process of the motor train unit, and therefore safe, punctual and effective running of the motor train unit is achieved. The multi-model adaptive PID control of the braking process of the motor train unit is simple, practical, capable of achieve multi-purpose control of the braking process of the motor train unit, and suitable for on-line monitoring and automatic control of the braking process of the motor training unit.

Description

technical field [0001] The invention relates to a modeling and control method for the braking process of an EMU, and belongs to the technical field of monitoring and automatic control of the braking process of an EMU. Background technique [0002] Railway transportation plays an extremely critical role in the social and economic development of our country. The high-speed passenger train is one of the important components to improve the railway transportation capacity, and the EMU has become an important means of transportation for the development of my country's high-speed railway. The braking process of the EMU has nonlinear characteristics. With the continuous increase of the initial braking speed and the improvement of passenger requirements, higher requirements are put forward for the safe and reliable braking of the EMU. How to establish an effective braking process for the EMU? The model and the determination of the correct control strategy have important practical si...

Claims

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Application Information

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IPC IPC(8): G05B13/04
Inventor 杨辉严瑾张坤鹏李中奇刘杰民
Owner EAST CHINA JIAOTONG UNIVERSITY
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