车间运动学模型在智能车速度跟踪控制中的应用

Application of Vehicle Kinematics Model in Speed-tracking Control of Intelligent Vehicle

车辆纵向运动速度控制是智能车领域的关键技术之一,其控制精度和响应速度是智能车其他功能实现的基础。采用模型预测控制理论,研究实现速度跟踪控制算法:一是对车辆系统车间运动学模型进行改造,提出虚拟目标车辆概念;二是提出减少优化目标和改善预测时域的确定方法,降低控制算法的计算成本在实时控制周期之内。通过在不同车辆上的试验表明,所开发的算法满足了控制系统的实时性要求和控制精度要求,并可实现控制算法的无缝移植。

Vehicle longitudinal speed control is one of the key technologies in the field of intelligent vehicle, and its control precision and response speed is the basis of other technologies. The paper studies the speed-tracking control algorithm with model predictive control theory： firstly, it proposes the concept of virtual target vehicle by improving vehicle system kine- matics model; secondly, it proposes a method to decrease optimal target and improve prediction horizon, which can reduce the computational expense of control algorithm to real-time control cycle. After testing on different vehicles, it proves that this algorithm can meet the real-time and accuracy requirements, and it can also realize the low-cost transplantation of con- trol algorithm.