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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
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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| Summary: | 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. |
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| ISSN: | 1000-128X |