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考虑参数不确定性的无人车预设性能路径跟踪控制
作者姓名:王泰琪  肖润谋  王 畅  张新锋
摘    要:为保证无人车在参数不确定性影响下的路径跟踪具有预设控制精度,提出一种具有预设跟踪误差性能的路径跟踪输出反馈控制方法。根据横向预瞄偏差建立了路径跟踪二阶误差积分系统,在考虑轮胎侧偏刚度参数摄动及车辆横向速度未知的情况下,利用扩张状态方法建立了含有复合未知项的控制模型,再通过设计线性扩张状态观测器对系统未知状态和模型不确定项进行估计,并进一步证明了观测误差的一致有界收敛性。针对无人车路径跟踪瞬态和稳态性能无法满足预设精度的问题,结合观测器估计值提出了一种具有预设性能的路径跟踪输出反馈控制器,并根据Lyapunov理论对闭环系统稳定性进行了严格证明。Matlab/Simulink仿真结果表明,所设计的控制策略能保证车辆以预设控制性能跟踪上期望路径,进一步在硬件在环仿真试验台上进行验证,结果表明所设计方案能严格保证横向跟踪偏差位于安全边界之内并具有较强的鲁棒性。

关 键 词:无人车  路径跟踪  预设性能  模型不确定性

Prescribed Performance Path Following for Self-Driving Vehicles Considering Parametric Uncertainties
Authors:WANG Taiqi  XIAO Runmou  WANG Chang  ZHANG Xinfeng
Abstract:To ensure path tracking control precision in self-driving vehicles with uncertain parameters, the paper proposes an output-feedback control method with the prescribed control performance criteria. Firstly,by constructing the lateral offset error at the driver''s preview point, a second-order error integration system is established. Considering the unknown lateral velocity and perturbation in the tire cornering stiffness, a control model containing lumped unknown states is established by using the extended state method. The unknown states of the system are obtained by designing a linear extended state observer and the uniformly bounded convergence of the observation error is further proved. Then, to address the issue that the transient and steady-state performance of vehicles cannot meet the predefined accuracies, an output feedback path following controller with prescribed performance is proposed, incorporating observer estimations. The stability of the closed-loop system is rigorously proved based on the Lyapunov theory. Finally, Matlab/Simulink simulation results show that the designed control strategy effectively tracks the reference path with the desired accuracy. Moreover, the proposed control method is further verified via the hardware-in-the-loop experiment and the results show that the lateral tracking errors are consistently maintained within the predefined safety range with strong robustness.
Keywords:self-driving vehicles  path following  prescribed performance  model uncertainties
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