基于优化动力学模型的路径跟踪控制研究OA北大核心CSTPCD

In response to the poor adaptability of conventional path tracking model predictive con-trollers under high-speed and large-curvature conditions,an adaptive prediction horizon control strate-gy was proposed based on optimized dynamic models.Firstly,to address the issues of insufficient ac-curacy of classical dynamics models under high lateral acceleration conditions,an optimized model in-cluding roll steer and compliance steer was established,achieving higher precision prediction of vehicle states.Secondly,to address the issues of fixed prediction horizon control under high-speed and large-curvature conditions,an adaptive prediction horizon strategy was proposed based on two-dimensional Gaussian function,achieving real-time adjustment of preview distances with low algorithm complexi-ty.Finally,the effectiveness of the controller on double-lane-change roads was verified throught Car-Sim/Simulink joint simulation.Results show that a reduction of 45.1％in lateral position peak errors and 72.4％in yaw angle peak errors indicate better adaptability of the designed controller to extreme conditions.