Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains
The locomotive autonomous operation system is characterized by its inherent nonlinear and time-varying nature. Operating trains encounter a diverse range of track conditions, which necessitates not only predictive control but also the dynamic adjustment of controller parameters to adapt to these var...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Control and Information Technology
2024-08-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.005 |
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| _version_ | 1849224677907496960 |
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| author | YI Jie JIANG Fan LUO Yuan ZHANG Zhengfang BAI Jinlei ZHONG Puhua |
| author_facet | YI Jie JIANG Fan LUO Yuan ZHANG Zhengfang BAI Jinlei ZHONG Puhua |
| author_sort | YI Jie |
| collection | DOAJ |
| description | The locomotive autonomous operation system is characterized by its inherent nonlinear and time-varying nature. Operating trains encounter a diverse range of track conditions, which necessitates not only predictive control but also the dynamic adjustment of controller parameters to adapt to these varying conditions. To address these challenges, this paper presents a fuzzy adaptive model predictive control (FAMPC) approach specifically for heavy-haul trains. Based on the establishment of a nonlinear multi-mass model for heavy-haul trains, a model predictive control system framework was constructed, to incorporate optimization processes that consider multiple objectives and operational constraints. This model aims to predict and dynamically adjust the operational states of trains. To mitigate the inadaptability associated with fixed controller parameters in response to changing track conditions, this paper integrates fuzzy control with model predictive control methods, to facilitate the adaptive optimization control for trains running on different railways, by enabling the adaptive tuning of weight coefficients within their model predictive controllers. Simulation results revealed the good control performance of the integrated controller configuration, highlighting its ability to ensure the stable train operation while achieving accurate train control within speed errors of ±1 km/h. |
| format | Article |
| id | doaj-art-c6829e75b1d54d4389d29e746ab4043e |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2024-08-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-c6829e75b1d54d4389d29e746ab4043e2025-08-25T06:57:16ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272024-08-01364368496716Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul TrainsYI JieJIANG FanLUO YuanZHANG ZhengfangBAI JinleiZHONG PuhuaThe locomotive autonomous operation system is characterized by its inherent nonlinear and time-varying nature. Operating trains encounter a diverse range of track conditions, which necessitates not only predictive control but also the dynamic adjustment of controller parameters to adapt to these varying conditions. To address these challenges, this paper presents a fuzzy adaptive model predictive control (FAMPC) approach specifically for heavy-haul trains. Based on the establishment of a nonlinear multi-mass model for heavy-haul trains, a model predictive control system framework was constructed, to incorporate optimization processes that consider multiple objectives and operational constraints. This model aims to predict and dynamically adjust the operational states of trains. To mitigate the inadaptability associated with fixed controller parameters in response to changing track conditions, this paper integrates fuzzy control with model predictive control methods, to facilitate the adaptive optimization control for trains running on different railways, by enabling the adaptive tuning of weight coefficients within their model predictive controllers. Simulation results revealed the good control performance of the integrated controller configuration, highlighting its ability to ensure the stable train operation while achieving accurate train control within speed errors of ±1 km/h.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.005heavy-haul trainlocomotive automatic operationadaptive model predictive controlfuzzy control |
| spellingShingle | YI Jie JIANG Fan LUO Yuan ZHANG Zhengfang BAI Jinlei ZHONG Puhua Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains Kongzhi Yu Xinxi Jishu heavy-haul train locomotive automatic operation adaptive model predictive control fuzzy control |
| title | Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains |
| title_full | Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains |
| title_fullStr | Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains |
| title_full_unstemmed | Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains |
| title_short | Research on Fuzzy Adaptive Model Predictive Control Methodology for Heavy-Haul Trains |
| title_sort | research on fuzzy adaptive model predictive control methodology for heavy haul trains |
| topic | heavy-haul train locomotive automatic operation adaptive model predictive control fuzzy control |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.005 |
| work_keys_str_mv | AT yijie researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains AT jiangfan researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains AT luoyuan researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains AT zhangzhengfang researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains AT baijinlei researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains AT zhongpuhua researchonfuzzyadaptivemodelpredictivecontrolmethodologyforheavyhaultrains |