摘要
随着智能小车技术的发展,对智能小车控制器的研究也有了更多的现实意义。针对智能小车轨迹跟踪问题,提出一种多维泰勒网优化控制器。首先,为智能小车构建数学模型,并据此设计多维泰勒网优化控制器;然后,将多维泰勒网优化控制器的仿真结果与反步法控制及PID控制器进行比较,三种控制器均采用粒子群优化算法训练至最优。最终得出结论,相比较于PID控制器和反步法控制,多维泰勒网优化控制器能取得更快的响应速度和更好的控制效果。
In this paper,a multi-dimensional Taylor network optimal controller is proposed to solve the problem of vehicle trajectory tracking.Firstly,a mathematical model is built for the intelligent vehicle,and a multi-dimensional Taylor network optimal controller is designed based on this model.Then,the simulation results of multi-dimensional Taylor network optimal control are compared with those of controller based on back-stepping and PID controller.The parameters of controllers of all the three kinds are trained to the best by particle swarm optimization algorithm.Finally,compared with PID control and control based on back-stepping,multi-dimensional Taylor network optimal controller can achieve faster response speed and better control effect.
出处
《工业控制计算机》
2020年第6期116-118,共3页
Industrial Control Computer
基金
上海航天科技创新基金(SAST2019-020)资助。
关键词
智能小车
多维泰勒网
轨迹跟踪
Intelligent vehicle
multi-dimensional Taylor network
trajectory tracking
