Wheel Deflection Control of Agricultural Vehicles with Four-Wheel Independent Omnidirectional Steering

Abstract

Due to the Fharsh working environment of wheeled agricultural vehicles in the field, it is difficult to ensure that all wheels make contact with the ground at the same time, which is easy to unequally distribute the yaw moments of each independent wheel. The commonly used vehicle lateral control methods are mostly controlled by coordinating the individual torque between different wheels. Obviously, this control method is not suitable for agricultural four-wheeled vehicles. The goal of this study was to provide a wheel steering angle control method that uses electric push rods as actuators that can cope with this problem. The design of a four-wheel steering controller generally adopts the linear PID control method, but the research object of this paper is difficult to establish an accurate and linear mathematical model due to the complex working environment. Therefore, fuzzy adjustment is added on the basis of PID control, which can meet the requirements of model difficulty and control accuracy at the same time. In order to verify the feasibility and rationality of the designed wheel steering mechanism, the model dynamics simulation based on ADAMS software and the response analysis of the electric linear actuator thrust were completed. Based on the kinematics model of the controlled object, the rotation angle of the actuator motor is used as the control target, the lateral deviation e and deviation variation ec are taken as input variables and the parameters KP, KI and KD are taken as output variables, thereby establishing a fuzzy PID controller. Then, this controller is constructed in the Matlab/ Simulink simulation environment to analyze the lateral deviation and response stability during the process of vehicle path tracking. From the verification results of the linear path walking test under the fuzzy PID control method, the maximum lateral deviation of vehicle chassis is 2.7 cm when the driving speed is set as 1 m/s, and the deviation adjustment stable time of the system is 0.15 s. It can be seen that the proposed steering control strategy has good response performance and effectively increases the steering stability.

Research on Speed Control Methods and Energy-Saving for High-Voltage Transmission Line Inspection Robots along Cable Downhill

“…Ultimately, the initial values of the three parameters, K P , K I , and K D , for the fuzzy PID controller were set as K P0 = 55, K I0 = 102, and K D0 = 50. nature of the inspection robot's downhill speed control system and its susceptibility to external environmental factors like cable corrosion, wear, and wind force, it is challenging to establish an accurate mathematical model to control the walking wheel motor's speed. Hence, a combination of the Ziegler-Nichols tuning method and the ultimate gain method was used to adjust the parameters of the inspection robot's downhill speed control system [31]. The Ziegler-Nichols tuning method adjusts the proportional coefficient KP first, then the integral coefficient KI, and finally the derivative coefficient KD, to initially determine the range of values for the three parameters of the PID controller.…”

Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle

“…Q. Xu et al constructed a fuzzy PID controller to solve the problem of wheel deflection control of agricultural vehicles with four-wheel independent steering and conducted simulation experiments and field tests. The results showed that their steering control strategy has good real-time performance and effectively improves steering stability [16].…”

Research on Running Performance Optimization of Four-Wheel-Driving Ackerman Chassis by the Combining Method of Quantitative Experiment with Dynamic Simulation

“…To solve the problem of uneven distribution of yaw torque on each independent wheel of agricultural four-wheel vehicles, Xu et al [16] proposed a steering wheel steering angle control method using electric push rods as actuators, which combines PID control and fuzzy regulation for controlling. The feasibility and rationality of the designed wheel steering mechanism were verified through dynamic simulation and virtual simulation of fuzzy PID controller.…”