智能车运动轨迹跟踪算法的研究

针对智能车运动过程中轨迹跟踪精度差的问题,提出了一种基于反演控制算法的智能车运动轨迹跟踪算法。首先,建立智能车的运动学模型;误差模型和动态模型。然后,根据反演控制算法,设计出合理的分部虚拟控制量,并结合李雅普诺夫稳定性分析,设计智能车运轨迹跟踪控制律;最后,在Simulink上进行智能车轨迹跟踪控制的仿真实验。实验结果表明,设计的智能车运动轨迹跟踪算法相比于迭代学习算法或者李雅普诺夫直接法,具有更好的实时性且跟踪精度好,且满足不同车速环境下智能车稳定性的需求。

Tracking algorithm of intelligent vehicle movement trajectory

Aim at the difference in trajectory tracking accuracy during the movement of smart cars. An intelligent vehicle trajectory tracking algorithm based on inversion control algorithm is proposed. First, establish the kinematics model of the smart car, error model and dynamic model. Then, according to the inversion algorithm, design a reasonable amount of virtual control of the branch, combined with Lyapunov stability analysis, the intelligent vehicle trajectory tracking control law is designed. Finally, the simulation experiment of intelligent vehicle trajectory tracking control is carried out on Simulink. The experimental results show that the designed smart car motion trajectory tracking algorithm has better real-time performance and better tracking accuracy in the above learning algorithm or Lyapunov direct method. And meet the needs of the stability of smart cars under different speed environments.