Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm
This paper presented an improved sliding mode extremum seeking control (SMESC) algorithm with time-varying parameters, as a solution to steady-state oscillation and slow convergence speed of the traditional SMESC algorithm in tracking the optimal adhesion point of freight trains. In order to weaken...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2023-01-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.014 |
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| _version_ | 1850142718634754048 |
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| author | CHENG Xiang TANG Runzhong HUANG Gang HUANG Yishan |
| author_facet | CHENG Xiang TANG Runzhong HUANG Gang HUANG Yishan |
| author_sort | CHENG Xiang |
| collection | DOAJ |
| description | This paper presented an improved sliding mode extremum seeking control (SMESC) algorithm with time-varying parameters, as a solution to steady-state oscillation and slow convergence speed of the traditional SMESC algorithm in tracking the optimal adhesion point of freight trains. In order to weaken the steady-state oscillation and speed up the convergence speed of SMESC, the mathematical relationship between the gain parameter and steady-state amplitude in SMESC and the correlation between the slope of auxiliary function and convergence were analyzed and optimized. The time-varying slope of auxiliary function was designed to improve the convergence speed of SMESC, and a dynamic gain parameter based on observation error was designed to reduce steady-state oscillation, and the convergence was analyzed. A resistance parameters estimation method based on particle swarm algorithm (PSO) was proposed to deal with the absence of running resistance due to inaccessibility for measurement. At last, the SMESC-based adhesion control law was designed, and the effectiveness and practicability of the proposed method were verified by comparing with the traditional SMESC algorithm. |
| format | Article |
| id | doaj-art-8293c4880dbe4e388de199e780d1083a |
| institution | OA Journals |
| issn | 1000-128X |
| language | zho |
| publishDate | 2023-01-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-8293c4880dbe4e388de199e780d1083a2025-08-20T02:28:58ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2023-01-0110411235729817Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithmCHENG XiangTANG RunzhongHUANG GangHUANG YishanThis paper presented an improved sliding mode extremum seeking control (SMESC) algorithm with time-varying parameters, as a solution to steady-state oscillation and slow convergence speed of the traditional SMESC algorithm in tracking the optimal adhesion point of freight trains. In order to weaken the steady-state oscillation and speed up the convergence speed of SMESC, the mathematical relationship between the gain parameter and steady-state amplitude in SMESC and the correlation between the slope of auxiliary function and convergence were analyzed and optimized. The time-varying slope of auxiliary function was designed to improve the convergence speed of SMESC, and a dynamic gain parameter based on observation error was designed to reduce steady-state oscillation, and the convergence was analyzed. A resistance parameters estimation method based on particle swarm algorithm (PSO) was proposed to deal with the absence of running resistance due to inaccessibility for measurement. At last, the SMESC-based adhesion control law was designed, and the effectiveness and practicability of the proposed method were verified by comparing with the traditional SMESC algorithm.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.014adhesion controlextremum seekingobserversteady-state oscillation |
| spellingShingle | CHENG Xiang TANG Runzhong HUANG Gang HUANG Yishan Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm 机车电传动 adhesion control extremum seeking observer steady-state oscillation |
| title | Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| title_full | Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| title_fullStr | Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| title_full_unstemmed | Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| title_short | Adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| title_sort | adhesion control research for freight trains based on an improved sliding mode extremum seeking algorithm |
| topic | adhesion control extremum seeking observer steady-state oscillation |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.01.014 |
| work_keys_str_mv | AT chengxiang adhesioncontrolresearchforfreighttrainsbasedonanimprovedslidingmodeextremumseekingalgorithm AT tangrunzhong adhesioncontrolresearchforfreighttrainsbasedonanimprovedslidingmodeextremumseekingalgorithm AT huanggang adhesioncontrolresearchforfreighttrainsbasedonanimprovedslidingmodeextremumseekingalgorithm AT huangyishan adhesioncontrolresearchforfreighttrainsbasedonanimprovedslidingmodeextremumseekingalgorithm |