ATO Controller for High-speed Train Based on Model-Free Adaptive Control
In view of the problems of dynamic model mismatch of traditional controller and potential safety hazards of driver operation when the high-speed train operated in a changeable and complex environment, a high speed train automatic driving controller design scheme based on model-free adaptive control...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2021-07-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.04.019 |
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| _version_ | 1849313238931472384 |
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| author | Ri LIU Tong SUN Yiwei ZHANG Mengjiao LI Junying CHU Sheng ZHANG |
| author_facet | Ri LIU Tong SUN Yiwei ZHANG Mengjiao LI Junying CHU Sheng ZHANG |
| author_sort | Ri LIU |
| collection | DOAJ |
| description | In view of the problems of dynamic model mismatch of traditional controller and potential safety hazards of driver operation when the high-speed train operated in a changeable and complex environment, a high speed train automatic driving controller design scheme based on model-free adaptive control (MFAC) was proposed. Firstly, a full-format dynamic data train model to transfer the nonlinear characteristics of the train to the pseudo gradient was constructed; Secondly, according to the full-format dynamic data train model,the model-free adaptive control law and the train control principle were designed, and with the pseudo gradient estimated through the train operation data, the ATO controller was constructed; Finally, "Lanzhouxi-Xining" EMU operating data was used for simulation. The result shows that: speed tracking error under the action of the MFAC controller is 0.254 km/h, and the train acceleration impact rate is mainly distributed in [0, 0.1), accounting for about 83.8% of the total step length. By compared with fuzzy adaptive PID (proportion-integral-derivative)in terms of speed tracking, displacement tracking, and comfort, the performance of the proposed controller is proved better. |
| format | Article |
| id | doaj-art-88ccceb8dda74f548bfccd5756fc02c3 |
| institution | Kabale University |
| issn | 1000-128X |
| language | zho |
| publishDate | 2021-07-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-88ccceb8dda74f548bfccd5756fc02c32025-08-20T03:52:51ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2021-07-0111912520903976ATO Controller for High-speed Train Based on Model-Free Adaptive ControlRi LIUTong SUNYiwei ZHANGMengjiao LIJunying CHUSheng ZHANGIn view of the problems of dynamic model mismatch of traditional controller and potential safety hazards of driver operation when the high-speed train operated in a changeable and complex environment, a high speed train automatic driving controller design scheme based on model-free adaptive control (MFAC) was proposed. Firstly, a full-format dynamic data train model to transfer the nonlinear characteristics of the train to the pseudo gradient was constructed; Secondly, according to the full-format dynamic data train model,the model-free adaptive control law and the train control principle were designed, and with the pseudo gradient estimated through the train operation data, the ATO controller was constructed; Finally, "Lanzhouxi-Xining" EMU operating data was used for simulation. The result shows that: speed tracking error under the action of the MFAC controller is 0.254 km/h, and the train acceleration impact rate is mainly distributed in [0, 0.1), accounting for about 83.8% of the total step length. By compared with fuzzy adaptive PID (proportion-integral-derivative)in terms of speed tracking, displacement tracking, and comfort, the performance of the proposed controller is proved better.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.04.019high speed trainmodel-free adaptiveautomatic train operationfull-format dynamic linearizationsimulation |
| spellingShingle | Ri LIU Tong SUN Yiwei ZHANG Mengjiao LI Junying CHU Sheng ZHANG ATO Controller for High-speed Train Based on Model-Free Adaptive Control 机车电传动 high speed train model-free adaptive automatic train operation full-format dynamic linearization simulation |
| title | ATO Controller for High-speed Train Based on Model-Free Adaptive Control |
| title_full | ATO Controller for High-speed Train Based on Model-Free Adaptive Control |
| title_fullStr | ATO Controller for High-speed Train Based on Model-Free Adaptive Control |
| title_full_unstemmed | ATO Controller for High-speed Train Based on Model-Free Adaptive Control |
| title_short | ATO Controller for High-speed Train Based on Model-Free Adaptive Control |
| title_sort | ato controller for high speed train based on model free adaptive control |
| topic | high speed train model-free adaptive automatic train operation full-format dynamic linearization simulation |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.04.019 |
| work_keys_str_mv | AT riliu atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol AT tongsun atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol AT yiweizhang atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol AT mengjiaoli atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol AT junyingchu atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol AT shengzhang atocontrollerforhighspeedtrainbasedonmodelfreeadaptivecontrol |