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Lateral Control of Autonomous Light Truck Based on Improved LPV Model
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Fuwu Yan1, 2, 3, Bowen Xiang1, 2, 3, Jie Hu1, 2, 3, Ruipeng Chen1, 2, 3, Zhihao Zhang1, 2, 3, Haoyan Liu1, 2, 3, Chongzhi Gao4
Automotive Engineering | 2024, 46(8) : 1403 - 1413
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Automotive Engineering | 2024, 46(8): 1403-1413
Lateral Control of Autonomous Light Truck Based on Improved LPV Model
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Fuwu Yan1, 2, 3, Bowen Xiang1, 2, 3, Jie Hu1, 2, 3, Ruipeng Chen1, 2, 3, Zhihao Zhang1, 2, 3, Haoyan Liu1, 2, 3, Chongzhi Gao4
Affiliations
  • 1. Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering,Wuhan 430070
  • 2. Wuhan University of Technology,Hubei Key Laboratory of Modern Auto Parts Technology,Wuhan 430070
  • 3. Wuhan University of Technology,Auto Parts Technology Hubei Collaborative Innovation Center,Wuhan 430070
  • 4. Commercial Product R&D Institute,Dongfeng Automobile Co. ,Ltd. ,Wuhan 430000
Published: 2024-08-25 doi: 10.19562/j.chinasae.qcgc.2024.08.007
Outline
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For the characteristic of significant load variation in urban logistics autonomous light trucks and to meet the needs of low computational load and high stability, a path-tracking control method based on Linear Parameter-Varying Model Predictive Control (LPV-MPC) is proposed in this paper. Firstly, a linear parameter-varying model is constructed, and nonlinear mapping rules between the model and scheduling variables - speed and load - are established, to improve driving stability and mitigating system sensitivity to parameter fluctuations. Then, for the rolling optimization stage, a trajectory reconstruction method is designed to reconcile disparities between the discrete trajectory points provided by the planning layer and the demand of the control module's prediction layer. A smooth trajectory sequence tailored to the temporal scale of the prediction layer is constructed to effectively decrease the deviation between predicted and actual states. In addition, a multi-point state deviation prediction method is used instead of the traditional single-point prediction, fully leveraging reference trajectory information for improved tracking accuracy. Finally, the effectiveness of the proposed control strategy is verified through combined simulation and empirical vehicle tests.

autonomous light truck  /  path tracking  /  LPV-MPC  /  trajectory reconstruction
Fuwu Yan, Bowen Xiang, Jie Hu, Ruipeng Chen, Zhihao Zhang, Haoyan Liu, Chongzhi Gao. Lateral Control of Autonomous Light Truck Based on Improved LPV Model[J]. Automotive Engineering, 2024 , 46 (8) : 1403 -1413 . DOI: 10.19562/j.chinasae.qcgc.2024.08.007
Year 2024 volume 46 Issue 8
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Article Info
doi: 10.19562/j.chinasae.qcgc.2024.08.007
  • Receive Date:2024-01-29
  • Online Date:2025-07-29
  • Published:2024-08-25
Article Data
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History
  • Received:2024-01-29
  • Revised:2024-03-24
Funding
Affiliations
    1. Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering,Wuhan 430070
    2. Wuhan University of Technology,Hubei Key Laboratory of Modern Auto Parts Technology,Wuhan 430070
    3. Wuhan University of Technology,Auto Parts Technology Hubei Collaborative Innovation Center,Wuhan 430070
    4. Commercial Product R&D Institute,Dongfeng Automobile Co. ,Ltd. ,Wuhan 430000
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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