高地隙自走式车辆主动前轮转向稳定性控制的研究  

Study on the stability controlof active front wheel steering of self-propelled high clearance sprayer

作　　者：杨松林 冯静安[1] 宋宝[2] YANG Songlin;FENG Jing’an;SONG Bao(School of Mechanical and Electrical Engineering,Shihezi University,Shihezi,Xinjiang 832003,China;School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan,Hubei 430074,China)

机构地区：[1]石河子大学机械电气工程学院,新疆石河子832003 [2]华中科技大学机械科学与工程学院,湖北武汉430074

出　　处：《石河子大学学报（自然科学版）》2022年第6期684-690,共7页Journal of Shihezi University(Natural Science)

基　　金：国家自然科学基金项目(61663042);石河子大学高层次人才科研启动项目(RCZK2018C07)。

摘　　要：针对高地隙自走式车辆动力系统非线性以及多耦合的问题,本文提出基于BP神经网络的自抗扰主动前轮转向控制策略,建立了高地隙车辆非线性七自由度操纵稳定性动力学模型及其参考模型;设计了质心侧偏角自抗扰控制器以及横摆角速度自抗扰控制器,对整车行驶过程中质心侧偏角和横摆角速度之间的耦合特性以及非线性因素进行在线估计和抑制;添加BP神经网络模块对控制器参数进行在线寻优,提高控制器精度和鲁棒性;最后,基于MATLAB/Simulink仿真了高地隙车辆在不同路面环境转向工况下的响应。研究结果表明:基于BP神经网络的自抗扰主动前轮转向控制器BPADRC对比无控制,质心侧偏角峰值降低约6%,横摆角速度峰值降低约7%;对比普通的自抗扰控制器ADRC,控制精度更高,鲁棒性更好。Aiming at the non-linear and multi-coupling problems of self-propelled high clearance clearance self-propelled vehicle power system, this paper proposes an active disturbance rejection active front-wheel steering control strategy based on BP neural network.The nonlinear seven-degree-of-freedom handling stability dynamics model of the high ground clearance sprayer and its reference model are established;the side slip angle auto disturbance rejection controller and the yaw rate auto disturbance rejection controller are designed to control the center of mass of the vehicle during driving.The coupling characteristics between the slip angle and the yaw rate and the nonlinear factors are estimated and suppressed online;the BP neural network module is added to optimize the controller parameters online to improve the accuracy and robustness of the controller.Finally, based on MATLAB/Simulink, the response of high gap self-travelling vehicle in different steering conditions is simulated.The results show that the peak values of side slip angle and yaw rate of the active front wheel steering active disturbance rejection controller based on BP neural network are reduced by 6% and 7% respectively compared with no control.Compared with the common active disturbance rejection controller ADRC,the control precision is higher and the robustness is better.

关 键 词：高地隙喷雾机 主动前轮转向 自抗扰控制 BP神经网络 鲁棒性 BP神经网络自抗扰控制 

分 类 号：U461.1[机械工程—车辆工程]