基于模糊LQR的智能汽车路径跟踪控制

Path Tracking Control of Intelligent Vehicles Based on Fuzzy LQR

为保证智能汽车在不同车速下路径跟踪的精确性与稳定性,本文中设计了一种带有预瞄PID转角补偿的模糊线性二次型调节器(LQR)以进行路径跟踪控制。首先,基于路径跟踪误差模型设计了LQR控制器,并采用预瞄PID方法进行转角补偿,消除稳态误差,提高跟踪精度。接着,针对固定权重系数的控制器对于不同车速适应性较差的问题,提出了一种基于车速的权重系数模糊调节策略。最后,通过实车试验,验证了控制器在实车环境中的控制性能。结果表明,设计的控制器具有较高的跟踪精度,且在不同车速下均能保持良好的精确性与稳定性。

In order to ensure the accuracy and stability of the path tracking of intelligent vehicles under different speeds, a fuzzy linear quadratic regulator(LQR) with rotation angle compensation using preview PID for path tracking control is designed in this paper. Firstly, the LQR controller is designed based on the path tracking error model, and the preview PID algorithm is used to compensate the rotation angle,eliminate the steady-state error and enhance the tracking accuracy. Then, aiming at the problem of poor adaptability to different speeds of the controller with fixed weighting factors, a speed-based fuzzy adjustment strategy of weighting factors is proposed. Finally, a real vehicle test is conducted to verify the control performance of the controller in real world environment. The results show that the controller designed has high tracking accuracy, and can maintain good accuracy and stability under different vehicle speeds.