【摘要】 在智能汽车自适应跟车控制的实现中，提高控制精度和舒适性尤为重要。通过上层算法准确计算本车需求加速度，考虑安全性及舒适度，设计变时距跟车策略，基于响应快速鲁棒性较好的滑模变结构控制算法实现跟车巡航，并对滑模趋近率加以优化改进，以减小系统抖震。对于下层执行机构，进行实车实验，以此对比验证仿真中发动机逆模型和制动器逆模型的合理性，使其更符合真实响应状态。将以传统PID算法为跟车策略的实车实验与改进后的仿真跟车算法对比分析，通过Carsim车辆参数建模软件和MATLAB/Simulink联合仿真，节气门开度同制动主缸压力作为Carsim的输入信号实现对车辆的闭环控制。结果表明车辆控制的精确性和舒适性都显著提升，同时跟车距离更具安全性。更多还原

【Abstract】 It is very important to improve the control precision and comfort in the realization of adaptive tracking control of intelligent vehicle. In this paper, the demand acceleration of the vehicle was accurately calculated by the upper algorithm. Considering the comfort and safety to design the variable time distance following vehicle strategy, cruise was realized based on the sliding mode variable structure control algorithm which had fast response and good robustness, and the sliding mode approach rate was optimized and improved to reduce the system buffeting. For the lower actuator, a real car experiment was carried out to verify the rationality of the engine inverse model and the brake inverse model, so as to make it more consistent with the real response state. The actual vehicle experiment with the traditional PID algorithm as the following strategy was compared with the improved simulation following algorithm for verification. Through Carsim vehicle parameter modeling software and MATLAB/Simulink joint simulation, the throttle valve opening and brake master cylinder pressure were used as the input signals of Carsim to realize the closed-loop control of the vehicle. The results show that the accuracy and comfort of vehicle control are improved and the distance from the vehicle is safer.更多还原