Abstract
We present a double-layered control algorithm to plan the local trajectory for automated trucks equipped with four hub motors. The main layer of the proposed control algorithm consists of a main layer nonlinear model predictive control (MLN-MPC) controller and a secondary layer nonlinear MPC (SLN-MPC) controller. The MLN-MPC controller is applied to plan a dynamically feasible trajectory, and the SLN-MPC controller is designed to limit the longitudinal slip of wheels within a stable zone to avoid the tire excessively slipping during traction. Overall, this is a closed-loop control system. Under the off-line co-simulation environments of AMESim, Simulink, dSPACE, and TruckSim, a dynamically feasible trajectory with collision avoidance operation can be generated using the proposed method, and the longitudinal wheel slip can be constrained within a stable zone so that the driving safety of the truck can be ensured under uncertain road surface conditions. In addition, the stability and robustness of the method are verified by adding a driver model to evaluate the application in the real world. Furthermore, simulation results show that there is lower computational cost compared with the conventional PID-based control method.
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Hong-chao WANG designed the research. Hong-chao WANG, Wei-wei ZHANG, Hao-tian CAO, and Xun-cheng WU designed the algorithms and processed the data. Hong-chao WANG, Wei-wei ZHANG, Qiao-ming GAO, and Su-yun LUO drafted the manuscript. Hong-chao WANG and Wei-wei ZHANG revised and finalized the paper.
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Hong-chao WANG, Wei-wei ZHANG, Xun-cheng WU, Hao-tian CAO, Qiao-ming GAO, and Su-yun LUO declare that they have no conflict of interest.
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Project supported by the National Fund for Fundamental Research, China (No. 282017Y-5303), the National Natural Science Foundation of China (Nos. 51805312 and 51675324), the Shanghai Sailing Program, China (No. 18YF1409400), the Training and Funding Program of Shanghai College Young Teachers, China (No. ZZGCD15102), the Scientific Research Project of Shanghai University of Engineering Science, China (No. 2016–19), the Shanghai University of Engineering Science Innovation Fund for Graduate Students, China (No. 18KY0610), and the Technology and Innovation Projects of Guangxi Province, China (No. 2017-393)
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Wang, Hc., Zhang, Ww., Wu, Xc. et al. A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions. Front Inform Technol Electron Eng 21, 1059–1073 (2020). https://doi.org/10.1631/FITEE.1900185
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DOI: https://doi.org/10.1631/FITEE.1900185