基于线性二次型最优控制的自适应巡航控制算法研究
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摘要
以提高自适应巡航控制系统在全速域的控制精度为目标,提出了一种采用变权重系数的线性二次型最优控制算法。根据采集的车辆速度建立模糊控制器,动态选取线性二次型调节器(LQR)中的权重系数,从而得出全速域范围最优的目标加速度。通过仿真实验发现,改进的最优控制算法跟随距离的平均绝对误差,相较于传统的LQR算法降低了42. 95%,相较于常用的模糊控制算法降低了33. 97%。结果表明:改进的LQR算法能够有效提高自适应巡航控制系统的精度,保证跟随的安全性。
In order to improve the control accuracy of the adaptive cruise control system in the whole speed range,a linear quadratic optimal control algorithm with variable weight coefficients is proposed. The fuzzy controller is established according to the collected vehicle speed,and the weight coefficient in the linear quadratic regulator( LQR) is dynamically selected to obtain the optimal target acceleration in the full speed range. Through simulation experiments,the mean absolute error of the improved optimal control algorithm is 42. 95% lower than that of the traditional LQR algorithm and 33. 97% lower than that of the fuzzy control algorithm in the full-speed range. The results show that the improved LQR algorithm can effectively improve the accuracy of the adaptive cruise control system and ensure the safety of the following.
In order to improve the control accuracy of the adaptive cruise control system in the whole speed range,a linear quadratic optimal control algorithm with variable weight coefficients is proposed. The fuzzy controller is established according to the collected vehicle speed,and the weight coefficient in the linear quadratic regulator( LQR) is dynamically selected to obtain the optimal target acceleration in the full speed range. Through simulation experiments,the mean absolute error of the improved optimal control algorithm is 42. 95% lower than that of the traditional LQR algorithm and 33. 97% lower than that of the fuzzy control algorithm in the full-speed range. The results show that the improved LQR algorithm can effectively improve the accuracy of the adaptive cruise control system and ensure the safety of the following.
引文
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[2]王志洪,邵毅明.汽车自适应巡航控制算法的仿真研究[J].计算机工程与设计,2014,35(2):604-608.
[3]沈晨,秦训鹏,刘昌业,等.基于滑移率变化模型的ABS汽车制动距离计算[J].武汉理工大学学报(信息与管理工程版),2015,37(6):865-869.
[4] MOON S,YI K. Human driving data-based design of a vehicle adaptive cruise control algorithm[J]. Vehicle System Dynamics,2008,46(8):661-690.
[5] WU X,QIN G,YU H,et al. Using improved chaotic ant swarm to tune PID controller on cooperative adaptive cruise control[J]. Optik-International Journal for Light and Electron Optics,2016,127(6):3445-3450.
[6]王斌,王仁广,何玮,等.汽车ACC系统可变输出论域模糊控制算法[J].计算机应用研究,2010,27(2):465-467.
[7]刘红梅.基于模糊控制的自适应巡航控制系统研究[D].西安:长安大学,2018.
[8]章军辉,李庆,陈大鹏.车辆多模式多目标自适应巡航控制[J].电子科技大学学报,2018,47(3):368-375.
[9]张亮修,吴光强,郭晓晓.车辆自适应巡航控制系统的建模与分层控制[J].汽车工程,2018,40(5):547-553.
[10]甘志梅.基于激光雷达的Stop&Go巡航控制技术研究[D].上海:上海交通大学,2009.
[11] YI K,HONG J,KWON Y D. A vehicle control algorithm for stop-and-go cruise control[J]. Proceedings of the Institution of Mechanical Engineers(Part D):Journal of Automobile Engineering,2001,215(10):1099-1115.
[12]许伦辉,黄颖.基于不同安全车距策略的自适应巡航控制稳定性研究[J].科学技术与工程,2016,16(29):132-140.