- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | LI Zikang, DAI Chunhui, HUANG Cuicui, LONG Zhiqiang. Active Disturbance Rejection Speed Control for Maglev Trains Based on Multiple Population Genetic Algorithm[J]. Journal of Southwest Jiaotong University, 2025, 60(4): 912-920. doi: 10.3969/j.issn.0258-2724.20240113
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To realize precise speed control of maglev trains in complex disturbance environments, an active disturbance rejection control (ADRC) method with self-tuning parameters was proposed. Firstly, the longitudinal dynamic model of maglev trains was established by force analysis to describe the nonlinear hysteresis characteristics of maglev trains during operation. Secondly, the unknown parameters of the model and external disturbances were regarded as the extended state, and a third-order extended state observer was designed to observe the extended state in real time. In addition, the convergence condition of the observer was analyzed based on the Lyapunov stability theorem. Then, to solve the problem of many control parameters and difficult parameter adjustment in traditional ADRC, the multiple population genetic algorithm (MPGA) was introduced to realize adaptive optimization and adjustment of parameters. Finally, the simulation experiment was carried out based on the data collected from the real operation environment of maglev trains, and the simulation results show that compared with traditional ADRC, the speed control accuracy is increased by 22.7% and the tracking stability is improved by 25.6% by means of MPGA-ADRC method, which indicates that the proposed method can effectively improve the stability and ride comfort of maglev trains.
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Figures(11) / Tables(3)
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