Hierarchical CNNPID Based Active Steering Control Method for Intelligent Vehicle Facing Emergency Lane-Changing

To resolve the response delay and overshoot problems of intelligent vehicles facing emergency lane-changing due to proportional-integral-differential(PID)parameter variation,an active steering control method based on Convolutional Neural Network and PID(CNNPID)algorithm is constructed.First,a steering control model based on normal distribution probability function,steady constant radius steering,and instantaneous lane-change-based active for straight and curved roads is established.Second,based on the active steering control model,a three-dimensional constraint-based fifth-order polynomial equation lane-change path is designed to address the stability problem with supersaturation and sideslip due to emergency lane changing.In addition,a hierarchical CNNPID Controller is constructed which includes two layers to avoid collisions facing emergency lane changing,namely,the lane change path tracking PID control layer and the CNN control performance optimization layer.The scaled conjugate gradient backpropagation-based forward propagation control law is designed to optimize the PID control performance based on input parameters,and the elastic backpropagation-based module is adopted for weight correction.Finally,comparison studies and simulation/real vehicle test results are presented to demonstrate the effectiveness,significance,and advantages of the proposed controller.

Nonlinear Derivative and Integral Sliding Control for Tracked Vehicle Steering with Hydrostatic Drive

In the steering process of tracked vehicle with hydrostatic drive,the motion and resistance states of the vehicle are always of uncertain and nonlinear characteristics,and these states may undergoe large-scale changes.Therefore,it is significant to enhance the steering stability of tracked vehicle with hydrostatic drive to meet the need of future battlefield.In this paper,a sliding mode control algorithm is proposed and applied to achieve desired yaw rates.The speed controller and the yaw rate controller are designed through the kinematics and dynamics analysis.In addition,the nonlinear derivative and integral sliding mode control algorithm is designed,which is supposed to efficiently reduce the integration saturation and the disturbances from the unsmooth road surfaces through a conditional integrator approach.Moreover,it improves the response speed of the system and reduces the chattering by the derivative controller.The hydrostatic tracked vehicle module is modeled with a multi-body dynamic software RecurDyn and the steering control strategy module is modeled by MATLAB/Simulink.The co-simulation results of the whole model show that the control strategy can improve the vehicle steering response speed and also ensure a smooth control output with small chattering and strong robustness.

Theoretical and Experimental Investigation of Driver Noncooperative-Game Steering Control Behavior

This paper investigates two noncooperative-game strategies which may be used to represent a human driver's steering control behavior in response to vehicle automated steering intervention.The first strategy,namely the Nash strategy is derived based on the assumption that a Nash equilibrium is reached in a noncooperative game of vehicle path-following control involving a driver and a vehicle automated steering controller.The second one,namely the Stackelberg strategy is derived based on the assumption that a Stackelberg equilibrium is reached in a similar context.A simulation study is performed to study the differences between the two proposed noncooperativegame strategies.An experiment using a fixed-base driving simulator is carried out to measure six test drivers'steering behavior in response to vehicle automated steering intervention.The Nash strategy is then fitted to measured driver steering wheel angles following a model identification procedure.Control weight parameters involved in the Nash strategy are identified.It is found that the proposed Nash strategy with the identified control weights is capable of representing the trend of measured driver steering behavior and vehicle lateral responses.It is also found that the proposed Nash strategy is superior to the classic driver steering control strategy which has widely been used for modeling driver steering control over the past.A discussion on improving automated steering control using the gained knowledge of driver noncooperative-game steering control behavior was made.

Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration During Automated Driving

Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization.The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation,the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner.The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Study on Steering Control Strategy for High-Speed Tracked Vehicle with Hydrostatic Drive

Steering control strategy for high-speed tracked vehicle with hydrostatic drive is designed based on analyzing the fundamental steering theories of the hydrostatic drive tracked vehicle. The strategy is completed by the cooperation between integrated steering control unit and pump ＆ motor displacement controller. The steering simulation is conducted by using Simulink of Matlab. It is indicated that this steering control strategy can reduce the average vehicle speed automatically to achieve the driver＇s expected steering radius exactly in the case of en- suring not exceeding the system pressure threshold and no sideslip.

Steering Control of Wheeled Armored Vehicle with Brushless DC Motor

Considering the steering characters of one type of wheeled armored vehicle, a brushless direct current （DC） motor is adapted as the actuator for steering control. After investigating the known algorithms, one kind of algorithm, which combines the fuzzy logic control with the self-adapting PID control and the startup and pre-hrake control, is put forward. Then a test-bed is constructed, and an experiment is conducted. The result of experiment confirms the validity of this algorithm in steering control of wheeled armored vehicle with brushless DC motor.

Research on Vehicle Control Technology Using Four-Wheel Independent Steering System

The enhancement of vehicle handling stability and maneuverability through active and independent rear wheels control is presented. Firstly, the configuration of four-wheel independent steering prototype vehide is introduced briefly. Then the concrete overall design of the electronic controllers of four wheel independent steering system （4WIS） is formulated in details. Under the control strategy of zero sideslip angle at mass center, the mathematical model of 4WIS is established to deduce the equations of separated rear wheel steering angles. According to these equations, simulation analysis for 4WIS vehicle performances is finished to show that 4WIS vehicle can improve the maneuverability greatly at low speed and increase the handling stability at high speed. Finally, the road test of 4WIS vehide has performed to verify the correctness of simulation and show that compared with the conventional four wheel steering （4WS） vehicle, the 4WIS vehicle not only improves the kinematical harmony but also decreases steering resistance and lighten abrasion of tires.

Generalized Internal Model Robust Control for Active Front Steering Intervention

Because of the tire nonlinearity and vehicle＇s parameters＇uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system（AFS）controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control（GIMC）that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections：a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters＇uncertainties and some external disturbances.Simulations of double lane change（DLC）maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle＇s parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.

Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

Error analysis and a new steering law design for spacecraft control system using SGCMGs

Based on the singular value decomposition theory,this paper analyzed the mechanism of escaping/avoiding singularity using generalized and weighted singularity-robust steering laws for a spacecraft that uses single gimbal control moment gyros （SGCMGs） as the actuator for the attitude control system.The expression of output-torque error is given at the point of singularity,proving the incompatible relationship between the gimbal rate and the output-torque error.The method of establishing a balance between the gimbal rate and the output-torque error is discussed,and a new steering law is designed.Simulation results show that the proposed steering law can effectively drive SGCMGs to escape away from singularities.

HUMAN-SIMULATING VEHICLE STEERING CONTROL ALGORITHM

A new vehicle steering control algorithm is presented. Unlike the traditional methods do, the algorithm uses a sigmoid function to describe the principle of the human driver＇s steering strategy. Based on this function, a human simulating vehicle steering model, human-simulating steering control（HS） algorithm is designed. In order to improve the adaptability to different environments, a parameter adaptive adjustment algorithm is presented. This algorithm can online modify the value of the key parameters of the HS real time. HS controller is used on a vehicle equipped with computer vision system and computer controlled steering actuator system, the result from the automatic vehicle steering experiment shows that the HS algorithm gives good performance at different speed, even at the maximum speed of 172 km/h.

Fuzzy steering control to serpentine tracked robots in unknown environment

To solve the problem of multi-turning attitudes,unknown ground parameters and complex skidsteering control for serpentine tracked robots(STR),a fuzzy control method based on the estimation of track curvature and side slip angles is proposed.Based on the track-ground interaction,mathematical models are established for stable turning in the way of recursive homogeneous transformation.The navigation parameters such as rack curvature and side slip angles have approximately linear relationship with the yaw angles of articulate joints.Then attitude models in turning control are studied and summarized.Transforming strategies of attitude models are optimized.Based on the strategies,an adjustable fuzzy controller is designed.In the controller,an estimator is set to solve the problem of unknown and variable universe.The estimator predicts the track curvature by metabolic linear least squares estimate.Experiments have verified the feasibility and validity of the controller.

基于电动方向盘的拖拉机自动导航转向控制方法

为提高轮式拖拉机自动导航过程中转向控制的精度与稳定性,该研究以雷沃欧豹M704-2H拖拉机作为试验平台,采用电动方向盘作为转向执行机构,分析转向机械间隙对控制精度的影响,针对转向间隙特性设计转向控制算法。首先,为了获得准确的转向角,利用GNSS(global navigation satellite system)与二轮车模型快速标定虚拟轮转角,标定结果表明:虚拟轮转角的最大误差为1.3°,平均误差为0.11°。然后,对转向系统的机械间隙进行分析,设计一种带有间隙补偿的模糊PD(proportional derivative)转向控制算法,并在Simulink中验证算法的可行性。实车试验结果表明,该算法跟踪方波转角信号的响应时间为1.1 s,最大稳态误差为0.65°,平均稳态绝对误差为0.132°。跟踪正弦波转角信号的平均延时为0.5 s,最大误差为1.91°,平均绝对误差为1.09°。与无间隙补偿算法相比,有间隙补偿算法跟踪方波信号最大稳态误差减小了0.022°,平均稳态绝对误差减少了0.112°,角度误差在±0.2°内的时间提升了71%;跟踪正弦波信号最大误差减小了0.68°,平均绝对误差减小0.23°。田间直线导航转向控制试验结果表明,转角跟踪的绝对平均误差为0.61°,最大跟踪误差为2.82°,转向控制跟踪精度较高,稳定性好,满足导航作业需求。

船舶远程驾驶人机主从博弈控制方法研究

针对船舶远程驾驶场景下的人机目标非一致性问题,本文设计了系统人主机辅的运行模式,提出一种主从博弈框架下的共享控制方法,将船舶协同避碰转向任务中的人机交互作用描述为完全信息条件下的非合作博弈关系,通过构造驾驶员和共驾控制器的状态空间推导主从博弈的Stackelberg微分对策,使用Fan-GFlicksberg不动点定理证明纳什均衡解的存在性与唯一性。根据驾驶风格和操纵技能预分配驾驶权重,基于模型预测控制方法设计轨迹跟踪器,采取反馈校正方式在有限时域内滚动优化,综合考虑船舶安全航行边界、碰撞风险和人机冲突程度在线进行调节。选取船舶横向偏移误差和驾驶员操作负荷等评价指标,在内河操纵环境下验证了方法的有效性。仿真结果表明:本文所提出的主从博弈控制方法能够为具备不同驾驶风格和操纵技能的作业人员提供个性化辅助,当驾驶员和共驾控制器发生意图冲突时,根据航行风险对预分配权重进行调节,在确保航行安全的前提下使船舶尽可能满足驾驶员的操纵意图。

汽车线控转向系统稳定性控制策略研究

以汽车线控转向系统为研究对象,构建滑模观测器对汽车质心侧偏角进行实时估计,用于主动前轮转向控制器设计。以汽车线性二自由度模型为参考模型,设计了基于扰动补偿的主动前轮转向滑模控制器,由主动转向控制器决策出额外附加前轮转角,使车辆响应跟随理想横摆角速度与质心侧偏角,改善汽车的横向稳定性。通过所建立的Carsim和Simulink联合仿真平台,在双移线低路面附着系数,有、无侧向风的工况下验证了主动转向控制策略的有效性。

基于热缩材料的气动柔性机器人转向机构设计

气动柔性机器人具有质量轻、环境适应性强、无需元件驱动、在恶劣条件下拥有较好的可靠性等优点。然而,转向运动控制一直是气动柔性机器人开发的最大难题并制约其大规模应用。针对此问题,设计一种通过电控加热使得热收缩膜实现主动转向的充气臂式柔性机器人,对其端部执行机构进行建模设计,对充气壁材料和热缩膜材料进行了实验选择;在此基础上,构建热致收缩的转向控制数学模型,搭建实验样机,并对转向效果进行验证。得到结论如下:充气壁带膜选择0.08 mm厚的PE筒膜,热缩膜选取厚度0.075 mm、宽度20 mm的PVC热缩膜,最佳的热缩温度为80℃。通过脉冲控制,实现了直角转向。该柔性机器人在管道检测方面具有良好的应用潜力。

自适应时域参数MPC的智能车辆轨迹跟踪控制

为了解决智能车辆在低附着路面下主动转向跟踪控制的稳定性和控制精度问题,提出了一种基于自适应时域参数的智能车辆轨迹跟踪控制策略。基于车辆动力学模型和模型预测控制算法(MPC)建立线性时变MPC控制器,并加入包括轮胎侧偏角约束、质心侧偏角约束以及前轮转角约束的动力学约束,求解出最优前轮转向角。分析控制器中的时域参数对控制效果的影响,设计了一种自适应时域参数控制器,能够根据获取的车辆速度,将求解得到最优的预测时域和控制时域参数输入到控制器,提高控制器在不同速度下的控制精度和稳定性。通过搭建MATLAB/SimuLink与CarSim联合仿真平台,在低附着路面情况下对固定时域控制器和自适应时域控制器进行对比仿真实验。结果表明:自适应时域控制器能够有效改善控制器的性能、减少横向偏差、提高轨迹跟踪控制精度,同时对不同速度也具有较强的适应性,车辆质心侧偏角也控制在0°~15°内,有效保证了车辆行驶的稳定性。

线控主动四轮转向汽车控制策略研究

目的针对线控四轮转向汽车横向稳定性不足及控制鲁棒性差等问题,提出一种主动转向反馈控制策略。方法使用Simulink搭建线控转向系统转向执行机构动力学模型,将MATLAB/Simulink与Carsim联合仿真,建立线控四轮转向整车模型;基于二自由度模型分析横摆角速度和质心侧偏角对汽车稳定性的影响,推导理想的横摆角速度和质心侧偏角;以横摆角速度增益恒定为依据设计理想传动比,得到期望前轮转角,以横摆角速度误差为控制量设计模糊控制器得到附加前轮转角对期望转角实时修正,实现前轮主动转向;针对横摆角速度和质心侧偏角与理想值之间的误差,加权得到稳定性控制目标;设计自适应积分滑模反馈控制策略输出后轮转角,对理想值进行跟踪,实现后轮主动转向。结果仿真实验结果表明:所搭建的线控转向系统能够准确反映汽车动力学特性。相比无控制的机械前轮转向汽车与横摆反馈控制的四轮转向汽车,线控主动四轮转向汽车在双移线工况下将质心侧偏角控制在0值附近波动,横摆角速度跟踪误差控制在1.149 deg/s以内;在角阶跃工况下将质心侧偏角稳态值控制在0.065 deg,横摆角速度稳态值误差为0.074 deg/s。结论线控主动四轮转向控制策略在双移线和角阶跃工况下控制效果显著,鲁棒性能好,能有效提高汽车的操纵稳定性和主动安全性。

差动转向无人车轨迹跟踪和车身姿态控制研究

针对分布式驱动无人车转向时车身在离心力作用下外倾,引起内侧车轮载荷减小,严重时会导致差动转向失效乃至车辆侧翻等问题,提出了一种差动转向无人车的轨迹跟踪和车身姿态控制方法;该控制方法可通过差动转向实现无人车轨迹跟踪,同时通过主动悬架实现转向时车身主动内倾来保证差动转向有效性,提高了无人车的操纵稳定性。建立考虑侧倾因素的车辆模型及参考模型,通过分数阶单点预瞄驾驶员模型得到了参考模型跟踪期望路径所需的参考前轮转角;基于此,设计了H_(∞)鲁棒控制器,通过控制差动转向无人车的横摆角速度和车身内倾角,分别跟踪参考模型提供的参考值,得到了所需的差动力矩及左右侧主动悬架控制力。研究结果表明:所设计的分数阶单点预瞄驾驶员模型和H_(∞)鲁棒控制器能有效保证差动转向无人车实现轨迹跟踪,同时实现了车身姿态控制。