摘要
选择双电机线控转向(steer-by-wire,SBW)系统作为研究对象,针对负载扰动、参数摄动以及双电机耦合等因素导致的双电机SBW系统跟踪与同步性能差的问题,提出一种基于自抗扰控制与滑模交叉耦合控制的双电机协调驱动控制策略。分析了双电机SBW系统的结构和工作机理,建立了该系统动力学模型。设计了一个二阶自抗扰控制器用于电机位置控制,整合电机控制的位置、速度环,解决传统电机位置控制中速度参数不可调节的问题。为了进一步提高二阶自抗扰控制器在系统状态变化时的控制效果,利用模糊神经网络算法动态优化控制器参数,增强控制系统的自适应能力。同时,基于交叉耦合控制思想,采用滑模控制算法设计了滑模速度协调控制器解决双电机系统的不同步问题。最后,基于Carsim-Simulink联合仿真平台进行了仿真分析,证明了所提控制策略的有效性。
We take the dual-motor steering-by-wire(SBW)system as our research object and propose a dual-motor coordinated drive control strategy to address the poor tracking and synchronization in the dual-motor SBW system caused by load disturbance,parameter perturbation and dual-motor coupling.The strategy integrates automatic disturbance rejection control and sliding mode cross-coupling control.First,the structure and working mechanism of the dual-motor SBW system are analyzed,and its dynamic model is then built.Next,a second-order automatic disturbance rejection controller is designed to control the motor position.It integrates the position and speed loop of the motor control,solving the problem of non-adjustable speed parameters in traditional control methods.To improve the control performance of the second-order automatic disturbance rejection controller when system state changes,the fuzzy neural network algorithm dynamically optimizes the controller parameters,enhancing the adaptive ability of the control system.Moreover,a sliding mode speed coordination controller is designed based on the concept of cross coupling control,using the sliding mode control algorithm to address the asynchronous problem in the dual-motor system.Finally,the effectiveness of our proposed control strategy is verified through simulation analysis on the Carsim-Simulink joint simulation platform.
作者
刘军
王怡凡
顾洪钢
杨紫燕
LIU Jun;WANG Yifan;GU Honggang;YANG Ziyan(School of Automobile and Traffic Engineering,Jiangsu University,Zhenjiang 212013,China)
出处
《重庆理工大学学报(自然科学)》
北大核心
2025年第1期19-26,共8页
Journal of Chongqing University of Technology:Natural Science
关键词
线控转向
自抗扰控制
模糊神经网络
滑模控制
交叉耦合控制
steer-by-wire
active disturbance rejection control
fuzzy neural network
sliding mode control
cross-coupling control
