考虑测量噪声的车辆自适应巡航控制系统纵向跟车研究

提出一种具有自适应补偿能力的反馈校正模型预测控制器设计方法，该控制器由卡尔曼滤波器和模型预测控制器构成.建立ACC控制系统车间纵向跟车动力学模型，采用卡尔曼滤波器进行状态变量的估计，消除测量噪声的干扰；利用反馈校正机制改进跟车预测模型，以处理参数不完全确定和外部干扰对模型精度带来的影响，并采用向量松弛因子对硬约束进行软化处理，避免优化求解过程中出现无可行解的情况.将本文所设计的控制器转化为带约束的二次规划问题，利用MPC控制器滚动优化的特点，将控制量作用于被控对象，实现自适应巡航控制.实验结果表明:在存在测量噪声的情况下，本文提出的方法有效地提高了ACC系统的跟车安全性和乘坐舒适性，并且系统具备良好的抗干扰能力. 

Research on the Longitudinal Tracking of Adaptive Cruise Control System for Vehicles Considering of Measurement Noise

Aiming at adaptive cruise control (ACC) system with noise,a feedback correction model predictive controller (MPC) was proposed based on adaptive compensation method,composed of a Kalman filter and a model predictive controller.Firstly,a longitudinal tracking vehicle dynamics model of ACC control system was established,making use of a Kalman filter to estimate state variables and eliminate measurement noise.Then,the feedback correction mechanism was used to improve the prediction model for following vehicles to deal with the influence of uncertain parameters and external interference on model accuracy.And the softening vectors factors were used to deal with hard constraints,making the reasonable solutions be found in the optimization process.Finally,the controller proposed in this paper was transformed into a quadratic programming problem with constraints,taking the rolling optimization characteristics of the MPC to realize ACC.Experimental results show that the method proposed in this paper can effectively improve the safety and comfort of ACC system,providing a powerful anti-jamming ability.