摘要
为改善四轮驱动汽车行驶的稳定性,提出了一种基于改进粒子群算法优化模糊比例-积分-微分(PID)控制系统,并对优化后的控制系统输出效果进行仿真验证。建立四轮驱动的汽车车辆模型,推导了汽车运动学方程式。设计了模糊PID控制器,对传统粒子群算法进行改进,利用改进后的粒子群算法优化模糊PID控制器参数,使得模糊PID控制系统在汽车行驶稳定性方面发挥更佳,进一步提高汽车在转弯行驶过程中的稳定性。以四轮驱动汽车为例,利用Matlab软件对汽车横向位移误差、偏航角速度、左侧前轮转矩和右侧前轮转矩进行仿真,检验优化模糊PID控制系统输出效果。结果显示:汽车采用优化后的模糊PID控制系统,横向位移跟踪误差减小了8.1%,偏航角速度降低了22.2%。所提出的优化模糊PID控制系统,不仅提高了汽车行驶期望运动路径的跟踪精度,还改善了四轮驱动汽车转向行驶的稳定性。
To improve the stability of four-wheel drive vehicles,a fuzzy proportional integral derivative(PID)control system based on improved particle swarm optimization algorithm is proposed,and the output effect of the optimized control system is simulated and verified.Established a four-wheel drive vehicle model and derived the kinematic equations of the vehicle.A fuzzy PID controller has been designed to improve the traditional particle swarm optimization algorithm.The improved particle swarm optimization algorithm is used to optimize the parameters of the fuzzy PID controller,making the fuzzy PID control system perform better in terms of vehicle driving stability,further enhancing the stability of the vehicle during turning.Taking a four-wheel drive vehicle as an example,Matlab software is used to simulate the lateral displacement error,yaw rate,left front wheel torque,and right front wheel torque of the vehicle,and to verify the output effect of the optimized fuzzy PID control system.The results show that the optimized fuzzy PID control system reduces the lateral displacement tracking error by 8.1%and the yaw rate by 22.2%for the car.The proposed optimized fuzzy PID control system not only improves the tracking accuracy of the expected motion path of the vehicle during driving,but also improves the stability of the steering of four-wheel drive vehicles.
作者
杨巧曼
刘妮
YANG Qiaoman;LIU Ni(Shaanxi College of Communication Technology,Xi’an 710018,Shaanxi,China;School of Information Engineering,Xi’an University,Chang’an 710064,Shaanxi,China)
出处
《中国工程机械学报》
北大核心
2024年第6期744-749,共6页
Chinese Journal of Construction Machinery
基金
国家自然科学基金资助项目(61806023)。
关键词
四轮驱动
汽车
模糊PID控制
改进粒子群算法
优化
仿真
four-wheel drive
automobile
fuzzy PID control
improved particle swarm optimization algorithm
optimization
simulation
