基于Kalman滤波器的智能车模型过弯路径优化控制

Cornering Way Optimizing Control of Intelligent Car Model Based on Kalman Filter

以非线性两自由度两轮直立智能车模型作为系统被控对象,设计一种基于卡尔曼滤波算法的过弯路径优化控制算法。运用卡尔曼滤波算法估计车辆行驶状态,根据相似理论Buckingham Pi定理,应用两轮直立智能模型车进行试验。试验结果表明:所设计的过弯路径优化控制算法能实现智能车以较合理的路径过弯,有效地减少过弯时间并提高过弯时的稳定性,验证了设计算法的有效性。

Take two-degree-freedom two-wheeled intelligent car model as the controlled object of the system, and design a cornering way optimal control algorithm based on the Kalman filter algorithm. The Kalman algorithm is applied to estimate the driving state information of the vehicle, and use the two-wheeled vertical intelligent car model to validate the effectiveness of this system according to the Buckingham Pi theorem. The results show that the cornering way optimizing control algorithm can realize intelligent vehicle to pass cornering way rationally, reduce the time effectively and improve the stability. It validate the effectiveness of design method.