In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and d...In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and design a path-tracking controller to guide the robot tractor along the reference course. A time-minimum suboptimal control method was used to generate the reference turning course based on the mechanical parameters of the test tractor. A path-tracking controller consisting of both feedforward and feedback component elements was also proposed. The feedforward component was directly determined by the desired steering angle of the current navigation point on the reference course, whereas the feedback component was derived from the designed optimal controller. Computer simulation and field tests were performed to validate the path-tracking performance. Field test results indicated that the robot tractor followed the reference courses precisely on flat meadow, with average and standard lateral devia- tions being 0.031 m and 0.086 m, respectively. However, the tracking error increased while operating on sloping meadow due to the employed vehicle kinematic model.展开更多
为解决实验室环境下的小型自航模能快速、准确、稳定地实现航迹跟踪问题,利用视线法(line of sight,LOS)将自航模的位置跟踪问题转化为自航模的航向控制问题,通过PID控制器,使自航模的航向角收敛于期望航向角,从而使自航模不断驶向期望...为解决实验室环境下的小型自航模能快速、准确、稳定地实现航迹跟踪问题,利用视线法(line of sight,LOS)将自航模的位置跟踪问题转化为自航模的航向控制问题,通过PID控制器,使自航模的航向角收敛于期望航向角,从而使自航模不断驶向期望航向点。通过设置不同的期望航向点,实现自航模航迹跟踪控制。之后通过MATLAB对其进行仿真研究,验证了其可行性。最后将其用于实验室环境下的自航模航迹跟踪,得到了良好的效果,进一步验证了其工程实用性。展开更多
This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used t...This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used to control linear and angular velocities on the midpoint of the front frame. The novel controller based on the error dynamics model is eventually realized to track the path high-precisely with constant speed. The results of simulation and experiment show that the LQR-GA controller has a better tracking performance than the existing methods under a low speed of 3 m/s. In this paper, kinematics model and simulation control models based on co-simulation of ADAMS and Matlab/Simulink are established to verify the proposed strategy. In addition, a real vehicle experiment is designed to further more correctness of the conclusion. With the proposed controller and considering the steering model in the simulation, the control performance is improved and matches the actual situation better. The research results contribute to the development of automation of ADT.展开更多
An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual...An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.展开更多
Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking acc...Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.展开更多
To improve the trajectory tracking robust stability of agricultural vehicles,a path tracking control method combined with the characteristics of agricultural vehicles and nonlinear model predictive control was present...To improve the trajectory tracking robust stability of agricultural vehicles,a path tracking control method combined with the characteristics of agricultural vehicles and nonlinear model predictive control was presented.Through the proposed method,the path tracking problem can be divided into two problems with speed and steering angle constraints:the trajectory planning problem,and the trajectory tracking optimization problem.Firstly,the nonlinear kinematics model of the agricultural vehicle was discretized,then the derived model was inferred and regarded as the prediction function plant for the designed controller.Second,the objective function characterizing the tracking performance was put forward based on system variables and control inputs.Therefore,the objective function optimization problem,based on the proposed prediction equation plant,can be regarded as the nonlinear constrained optimization problem.What’s more,to enhance the robust stability of the system,a real-time feedback and rolling adjustment strategy was adopted to achieve optimal control.To validate the theoretical analysis before,the Matlab simulation was performed to investigate the path tracking performance.The simulation results show that the controller can realize effective trajectory tracking and possesses good robust stability.Meanwhile,the corresponding experiments were conducted.When the test vehicle tracked the reference track with a speed of 3 m/s,the maximum lateral deviation was 13.36 cm,and the maximum longitudinal deviation was 34.61 cm.When the added horizontal deviation disturbance Yr was less than 1.5 m,the controller could adjust the vehicle quickly to make the test car return to the reference track and continue to drive.Finally,to better highlight the controller proposed in this paper,a comparison experiment with a linear model predictive controller was performed.Compared to the conventional linear model predictive controller,the horizontal off-track distance reduced by 36.8%and the longitudinal deviation reduced by 32.98%w展开更多
基金Project (No. 2006AA10A304) supported by the Hi-Tech Researchand Development Program (863) of China
文摘In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and design a path-tracking controller to guide the robot tractor along the reference course. A time-minimum suboptimal control method was used to generate the reference turning course based on the mechanical parameters of the test tractor. A path-tracking controller consisting of both feedforward and feedback component elements was also proposed. The feedforward component was directly determined by the desired steering angle of the current navigation point on the reference course, whereas the feedback component was derived from the designed optimal controller. Computer simulation and field tests were performed to validate the path-tracking performance. Field test results indicated that the robot tractor followed the reference courses precisely on flat meadow, with average and standard lateral devia- tions being 0.031 m and 0.086 m, respectively. However, the tracking error increased while operating on sloping meadow due to the employed vehicle kinematic model.
文摘为解决实验室环境下的小型自航模能快速、准确、稳定地实现航迹跟踪问题,利用视线法(line of sight,LOS)将自航模的位置跟踪问题转化为自航模的航向控制问题,通过PID控制器,使自航模的航向角收敛于期望航向角,从而使自航模不断驶向期望航向点。通过设置不同的期望航向点,实现自航模航迹跟踪控制。之后通过MATLAB对其进行仿真研究,验证了其可行性。最后将其用于实验室环境下的自航模航迹跟踪,得到了良好的效果,进一步验证了其工程实用性。
基金the Fundamental Research Funds for the Central Universities of China(No.FRF-TP-15-023A1)the National Key R&D Program Project(Nos.2016YFC0802905 and 2018YFC0604403)
文摘This paper designs a novel controller to improve the path-tracking performance of articulated dump truck(ADT). By combining linear quadratic regulator(LQR) with genetic algorithm(GA), the designed controller is used to control linear and angular velocities on the midpoint of the front frame. The novel controller based on the error dynamics model is eventually realized to track the path high-precisely with constant speed. The results of simulation and experiment show that the LQR-GA controller has a better tracking performance than the existing methods under a low speed of 3 m/s. In this paper, kinematics model and simulation control models based on co-simulation of ADAMS and Matlab/Simulink are established to verify the proposed strategy. In addition, a real vehicle experiment is designed to further more correctness of the conclusion. With the proposed controller and considering the steering model in the simulation, the control performance is improved and matches the actual situation better. The research results contribute to the development of automation of ADT.
基金Harbin Technological Innovation Research Fund(NO:2012RFXXG039)
文摘An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.
基金Supported by National Key R&D Program of China (Grant No.2021YFB2501800)National Natural Science Foundation of China (Grant No.52172384)+1 种基金Science and Technology Innovation Program of Hunan Province of China (Grant No.2021RC3048)State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle of China (Grant No.72275004)。
文摘Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.
基金This work is supported by Shandong Agricultural Machinery and Equipment Research and Development Innovation Initiative(2018YF020-07,2017YF002)Modern Agricultural Technology System Innovation Team Post Project in Shandong Province(SDAIT-16-10)+1 种基金the National Key Research Projects(2017 YFD0700705)the Natural Science Foundation of Shandong Province(ZR2019BC018).
文摘To improve the trajectory tracking robust stability of agricultural vehicles,a path tracking control method combined with the characteristics of agricultural vehicles and nonlinear model predictive control was presented.Through the proposed method,the path tracking problem can be divided into two problems with speed and steering angle constraints:the trajectory planning problem,and the trajectory tracking optimization problem.Firstly,the nonlinear kinematics model of the agricultural vehicle was discretized,then the derived model was inferred and regarded as the prediction function plant for the designed controller.Second,the objective function characterizing the tracking performance was put forward based on system variables and control inputs.Therefore,the objective function optimization problem,based on the proposed prediction equation plant,can be regarded as the nonlinear constrained optimization problem.What’s more,to enhance the robust stability of the system,a real-time feedback and rolling adjustment strategy was adopted to achieve optimal control.To validate the theoretical analysis before,the Matlab simulation was performed to investigate the path tracking performance.The simulation results show that the controller can realize effective trajectory tracking and possesses good robust stability.Meanwhile,the corresponding experiments were conducted.When the test vehicle tracked the reference track with a speed of 3 m/s,the maximum lateral deviation was 13.36 cm,and the maximum longitudinal deviation was 34.61 cm.When the added horizontal deviation disturbance Yr was less than 1.5 m,the controller could adjust the vehicle quickly to make the test car return to the reference track and continue to drive.Finally,to better highlight the controller proposed in this paper,a comparison experiment with a linear model predictive controller was performed.Compared to the conventional linear model predictive controller,the horizontal off-track distance reduced by 36.8%and the longitudinal deviation reduced by 32.98%w
