The wheel loader as the research object in present article,its steering mechanism is analyzed for the relationship between the steering cylinder displacement and the steering angle,which means,the relationship between...The wheel loader as the research object in present article,its steering mechanism is analyzed for the relationship between the steering cylinder displacement and the steering angle,which means,the relationship between the arm of steering resistance moment and the steering angle.In addition,the relationship between the in-situ steering resistance moment and the wheel angle is also be analyzed by integrating the interaction between the tire and the ground.The Matlab will help to build the mathematical modeling for verification.展开更多
Aiming at the application environment of paddy agricultural machinery with bumpy and undulating changes,the problems affecting the method for steering wheel angle measurement by MEMS gyroscope were analyzed,and a whee...Aiming at the application environment of paddy agricultural machinery with bumpy and undulating changes,the problems affecting the method for steering wheel angle measurement by MEMS gyroscope were analyzed,and a wheel angle measurement method combining Dual-MEMS gyroscope(dual MEMS gyroscope)and RTK-GNSS was designed.The adaptive weighting method was used to fuse the heading angle differentiation of RTK-GNSS,the MEMS gyroscope angle rate,and velocity data,and the rod-arm compensation was performed to accurately obtain the angle rates of the body and steering wheels of agricultural machinery;the difference between the combined angular rate of the steering wheel of the agricultural machinery and the angular rate of the agricultural machinery body was obtained,and the integrator is used to integrate the difference to get the wheel steering angle value,and the Kalman filter was designed to make feedback correction for the integration process of angle calculation to eliminate the errors caused by the gyroscope zero bias,random drift,and gyroscope rod arm effect,and to obtain the accurate value of wheel steering angle.A comparative test with the connecting rod wheel angle sensor was designed,and the results show that the maximum deviation is 4.99°,the average absolute average value is 1.61°,and the average standard deviation is 0.98°.The method in this study and the connecting rod wheel angle sensor were used on paddy farm machinery.The wheel angle measurement deviation of the proposed method and the connecting rod wheel angle sensor was not more than 1°,which is relatively small.It has good stability,speed adaptability,and dynamic responsiveness that meets the accuracy requirements of steering wheel angle measurement for paddy field agricultural machinery unmanned driving and can be used instead of connecting rod angle sensors for unmanned agricultural machinery.展开更多
为了解决传统农机导航系统中前轮转角测量传感器不易安装、维护困难以及转角估计不准确等问题,本文提出了一种基于受控自回归滑动平均模型和卡尔曼滤波器的组合模型(Auto-regressive moving average with exogenous input-Kalman filter...为了解决传统农机导航系统中前轮转角测量传感器不易安装、维护困难以及转角估计不准确等问题,本文提出了一种基于受控自回归滑动平均模型和卡尔曼滤波器的组合模型(Auto-regressive moving average with exogenous input-Kalman filter,ARMAX-KF)与速度补偿的拖拉机无前轮传感器转角估计方法。首先,利用Hammerstein非线性系统对拖拉机的转向系统建模,并采用递归最小二乘法(Recursive least squares method,RLS)将其辨识为ARMAX模型;其次,对后轮轴中心接地点速度进行杆臂误差补偿;最后,提出了ARMAX-KF方法,利用卡尔曼滤波器的校正特性,以拖拉机的运动学转角作为观测值,修正ARMAX模型预测的转角速度积分值,从而估计拖拉机的前轮转角。在速度杆臂补偿测量方法试验验证中,补偿后运动学转角平均绝对误差为1.110°,标准差为1.727°,相比补偿前分别减少61.13%和31.55%;在动态转角试验中,ARMAX模型预测的转角速度标准差为2.439(°)/s,相比采用固定传动比方法误差减少56.58%;采用基于ARMAX-KF的前轮转角估计绝对平均误差为0.649°,标准差为0.371°,相比采用固定传动比和卡尔曼滤波器的方法分别减少56.9%和78.82%;在直线导航跟踪试验中,采用基于ARMAX-KF的前轮转角估计标准差为0.649°,本文提出的方法提高了转角估计精度和农机导航作业质量。展开更多
文摘The wheel loader as the research object in present article,its steering mechanism is analyzed for the relationship between the steering cylinder displacement and the steering angle,which means,the relationship between the arm of steering resistance moment and the steering angle.In addition,the relationship between the in-situ steering resistance moment and the wheel angle is also be analyzed by integrating the interaction between the tire and the ground.The Matlab will help to build the mathematical modeling for verification.
基金supported by Science and Technology Innovation 2030–“New Generation Artificial Intelligence”Major Project(Grant No.2021ZD011090202,No.2021ZD011090503)the National Key Research and Development Program of China(Grant No.2021YFD2000602)the National Natural Science Foundation of China(Grant No.32071913,No.32101623).
文摘Aiming at the application environment of paddy agricultural machinery with bumpy and undulating changes,the problems affecting the method for steering wheel angle measurement by MEMS gyroscope were analyzed,and a wheel angle measurement method combining Dual-MEMS gyroscope(dual MEMS gyroscope)and RTK-GNSS was designed.The adaptive weighting method was used to fuse the heading angle differentiation of RTK-GNSS,the MEMS gyroscope angle rate,and velocity data,and the rod-arm compensation was performed to accurately obtain the angle rates of the body and steering wheels of agricultural machinery;the difference between the combined angular rate of the steering wheel of the agricultural machinery and the angular rate of the agricultural machinery body was obtained,and the integrator is used to integrate the difference to get the wheel steering angle value,and the Kalman filter was designed to make feedback correction for the integration process of angle calculation to eliminate the errors caused by the gyroscope zero bias,random drift,and gyroscope rod arm effect,and to obtain the accurate value of wheel steering angle.A comparative test with the connecting rod wheel angle sensor was designed,and the results show that the maximum deviation is 4.99°,the average absolute average value is 1.61°,and the average standard deviation is 0.98°.The method in this study and the connecting rod wheel angle sensor were used on paddy farm machinery.The wheel angle measurement deviation of the proposed method and the connecting rod wheel angle sensor was not more than 1°,which is relatively small.It has good stability,speed adaptability,and dynamic responsiveness that meets the accuracy requirements of steering wheel angle measurement for paddy field agricultural machinery unmanned driving and can be used instead of connecting rod angle sensors for unmanned agricultural machinery.
文摘为了解决传统农机导航系统中前轮转角测量传感器不易安装、维护困难以及转角估计不准确等问题,本文提出了一种基于受控自回归滑动平均模型和卡尔曼滤波器的组合模型(Auto-regressive moving average with exogenous input-Kalman filter,ARMAX-KF)与速度补偿的拖拉机无前轮传感器转角估计方法。首先,利用Hammerstein非线性系统对拖拉机的转向系统建模,并采用递归最小二乘法(Recursive least squares method,RLS)将其辨识为ARMAX模型;其次,对后轮轴中心接地点速度进行杆臂误差补偿;最后,提出了ARMAX-KF方法,利用卡尔曼滤波器的校正特性,以拖拉机的运动学转角作为观测值,修正ARMAX模型预测的转角速度积分值,从而估计拖拉机的前轮转角。在速度杆臂补偿测量方法试验验证中,补偿后运动学转角平均绝对误差为1.110°,标准差为1.727°,相比补偿前分别减少61.13%和31.55%;在动态转角试验中,ARMAX模型预测的转角速度标准差为2.439(°)/s,相比采用固定传动比方法误差减少56.58%;采用基于ARMAX-KF的前轮转角估计绝对平均误差为0.649°,标准差为0.371°,相比采用固定传动比和卡尔曼滤波器的方法分别减少56.9%和78.82%;在直线导航跟踪试验中,采用基于ARMAX-KF的前轮转角估计标准差为0.649°,本文提出的方法提高了转角估计精度和农机导航作业质量。
