半挂汽车列车多轴主动转向控制策略研究

针对半挂汽车列车低速机动性和高速稳定性较差的问题,建立三轴半挂汽车列车三自由度线性参考模型,以牵引车与挂车横摆角速度趋近于参考值、质心侧偏角趋近于零为设计目标,采用线性二次型调节器(linear quadratic regulator, LQR),制定牵引车挂车主动转向控制策略;应用仿真软件,在低速360°圆形工况与高速单移线工况下对LQR主动转向控制车辆进行仿真,并与无控制车辆模型进行对比分析。仿真结果表明,LQR主动转向控制车辆的低速机动性和高速稳定性得到了有效改善,证明所制定的控制策略具有较好的控制效果。

Sliding-mode control of path following for underactuated ships based on high gain observer

A nonlinear robust control strategy is proposed to force an underactuated surface ship to follow a predefined path with uncertain environmental disturbance and parameters.In the controller design,a high-gain observer is used to estimate velocities,thus only position and yaw angle measurements are required.The control problem of underactuated system is transformed into a control of fully actuated system through adopting an improved line-of-sight(LOS) guidance law.A sliding-mode controller is designed to eliminate the yaw angle error,and provide the control system robustness.The control law is proved semi-globally exponentially stable(SGES) by applying Lyapunov stability theory,and numerical simulation using real data of a monohull ship illustrates the effectiveness and robustness of the proposed methodology.

Calculation method for trajectory following control for autonomous vehicles

The current literature lacks uniform calculation methods for following trajectory control for autonomous vehicles,including the calculation of errors,determination of tracking points,and design of feedforward controllers.Hence,a complete calculation method is proposed to address this gap.First,a control equation in the form of an error is obtained according to the dynamic equation of the vehicle coordinate system and the trajectory following model.Secondly,the deviation of the vehicle state is obtained according to the current vehicle s state and the following control model.Finally,a linear quadratic regulator(LQR)controller with feedforward control is designed according to the characteristics of the dynamic equation.With the proposed LQR,the simulation of computational time,anti-interference,and reliability analysis of the trajectory following control is performed by programming using MATLAB.The simulation outcomes are then compared with the experimental results from the literature.The comparison indicates that the proposed complete calculation method is effective,reliable,and capable of achieving real-time and anti-interference following control performance.The simulation results with or without feedforward control show that the steady-state error is eliminated and that good control performance is obtained by introducing feedforward control.

Following Control for a UUV using Temporary Path Generation Guidance

A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.

Fuzzy robust path tracking strategy of an active pelagic trawl system with coordinated ship and winch regulation

A fuzzy robust path tracking strategy of an active pelagic trawl system with ship and winch regulation is proposed.First,nonlinear mathematic model of the pelagic trawl system was derived using Lagrange equation and further simplified as a low order model for the convenience of controller design.Then,an active path tracking strategy of pelagic trawl system was investigated to improve the catching efficiency of the target fish near the sea bottom.By means of the active tracking control,the pelagic trawl net can be positioned dynamically to follow a specified trajectory via the coordinated winch and ship regulation.In addition,considering the system nonlinearities,modeling uncertainties and the unknown exogenous disturbance of the trawl system model,a nonlinear robust H2 /H∞ controller based on Takagi-Sugeno(T-S) fuzzy model was presented,and the simulation comparison with linear robust H2 /H∞ controller and PID method was conducted for the validation of the nonlinear fuzzy robust controller.The nonlinear simulation results show that the average tracking error is 0.4 m for the fuzzy robust H2 /H∞ control and 125.8 m for the vertical and horizontal displacement,respectively,which is much smaller than linear H2 /H∞ controller and the PID controller.The investigation results illustrate that the fuzzy robust controller is effective for the active path tracking control of the pelagic trawl system.

Path-Following Based on Nonlinear Model Predictive Control with Adaptive Path Preview

This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.

Path planning and stability control of collision avoidance system based on active front steering

Vehicle collision avoidance system is a kind of auxiliary driving system based on vehicle active safety,which can assist the driver to take the initiative to avoid obstacles under certain conditions,so as to effectively improve the driving safety of vehicle.This paper presents a collision avoidance system for an autonomous vehicle based on an active front steering,which mainly consists of a path planner and a robust tracking controller.A path planner is designed based on polynomial parameterization optimized by simulated annealing algorithm,which plans an evasive trajectory to bypass the obstacle and avoid crashes.The dynamic models of the AFS system,vehicle as well as the driver model are established,and based on these,a robust tracking controller is proposed,which controls the system to resist external disturbances and work in accordance with the planning trajectory.The proposed collision avoidance system is testified through CarSim and Simulink combined simulation platform.The simulation results show that it can effectively track the planning trajectory,and improve the steering stability and anti-interference performance of the vehicle.