The Intelligent Vehicle Motion Research Based On Linear Active Disturbance Rejection Control

Intelligent vehicle,also known as a wheeled mobile robot or an autonomous vehicle,refers to a ground wheeled sports tool that can automatically sense the surrounding environment and make motion decisions.Conpared with the transmission car,it has the advantages of keen environmental awareness,efficient behavioral decision-making and stable control.If widely used,it will reduce the number of traffic accidents,improve urban tra:ffic congestion and save energy.This paper studies its motion control problems,the specific work is as follows:Firstly,taking the two-wheel mobile car AmigoBot as the research object,the dynamic model of the car is established.The model has parameter uncertainty,and the deflection angle linear auto disturbance rejection controller is designed.The root path method is used to perform the pole configuration to determine the controller,parameter.Matlab numerical simulation experiments show that the system is stable,and the deflection angle of the car can reach a given expected angle in a short time.In the experiment of the simulation platform MobileSim,the use of linear auto-disturbance as a deflection angle controller can achieve the desired steering angle and no overshoot faster than using the self-contained steering algorithm.Note that linear auto disturbance rej ection can reduce steering delay.Then,the common methods of lane change trajectory planning for smart cars are studied.The lane change trajectory based on the sin function is the most intuitive and simple,but the initial lateral acceleration is not zero;the arc curve takes into account the shortest lane change time,but does not limit the lateral acceleration.Trapezoidal lane change must reasonably choose lateral acceleration and acceleration rate.Otherwise,the lane change time will be longer and the flexibility will be poor.The numerical simulation in Matlab shovws that these three methods only start from the lane changing task itself without considering the actual limitations of vehicle operation.The polynomial-based lane-chaging trajectory planning does not have these defects,the trajectory itself and the first-order second-order derivative of the trajectory.All are smooth transitions,which means that the displacement,velocity and acceleration of the road line are excessively smooth to avoid rough lane change,and the algorithm has strong scalability.Therefore,the lane change trajectory planning in this paper adopts the method of polynomial fitting.Finally,the lane change trajectory tracking of smart cars is studied.On the basis of the traditional single-point preview method,the multi-point preview is used to improve the accuracy of the algorithm.The selection of the preview distance is dynamically adjusted according to the curvature of the tracking road and the speed of the trolley,and finally the desired steering angle is determined.Based on this,a trajectory tracking controller is established based on linear auto-disturbance,and the experiment is carried out under the condition that the tracking trajectory is circular,stra:ight,and polynomial.Compared with PID control,the experimental results show that linear auto-interference can be used.The cart is closer to the tracking traj ectory and the overshoot is smaller.In the case where the initial posture of the trolley and the lane change trajectory are the same,if the lane change trajectory is continuous,it is possible to ensure that the planning curve is tracked at zero error.