基于滑转率的六轮纵列式月球车驱动控制研究

基于车轮滑转率和车轮地面力学,研究了月球车在松软月面行驶时的车轮过度下陷问题.将 月球车车轮下陷和车轮—土壤作用力表达为车轮滑转率的函数,结合车辆地面力学理论并考 虑纵列式车轮多通过性土壤参数的修正,建立了月球车的动力学模型.判断车轮是否发生过 度下陷的标准为土壤所提供给驱动轮的土壤推力能否克服土壤对车轮的阻力.利用建立的动 力学模型,计算出能够保证车轮不会过度下陷的期望滑转率.考虑到月球车动力学系统的非 线性和不确定性,设计了以车轮滑转率为状态变量的滑模驱动控制器.仿真结果表明,采用 该控制器可以较快地跟踪期望滑转率,避免车轮的过度滑转下陷,保证月球车能够在软质路 面上正常行驶.     

月球车驱动轮爬坡牵引性能预测

月球表面可通过性较差,预测月球车驱动轮的爬坡牵引性能,对于保证探测工作的正常进行有重要意义。在传统地面车辆理论与研究方法的基础上,考虑斜坡角度对浅层月壤应力分布的影响和轮刺作用,给出了刚性车轮与月壤的相互作用模型。通过实例,计算和分析了不同参数的变化对车轮牵引性能的影响。分析结果表明:车轮的挂钩牵引力和滚动阻转矩受到车轮滑转率、结构尺寸和轮刺高度等参数变化的影响;车轮驱动效率随滑转率变化呈现先增大后减小的趋势,在最优的滑转率区间内能获得较大值。分析结论为月球车车轮的设计和控制提供了参考。     

基于改进PSO算法的拖拉机驱动防滑PID控制策略

为提高拖拉机等非道路车辆在正常行驶和工作阶段的通过性,针对拖拉机ASR控制策略进行了研究。基于Carsim和MATLAB/Simulink联合建立了拖拉机仿真模型,结合新提出的路面识别方法,实时更新目标滑转率,并利用改进的粒子群算法自适应的调整PID控制参数。针对不同路面进行一系列仿真实验,结果表明,目标滑转率随车辆行驶不断更新并最终达到所处路面的最优滑转率;基于改进PSO算法的PID参数自适应调整迅速,拖拉机滑转率收敛至目标值的响应较快,平均约1.5 s;在对接路面上行驶时,能有效的抑制拖拉机从高附着系数路面刚进入低附着系数路面时滑转率骤升情况,在高、低附着系数路面的稳定时间分别为2.63 s和1.55 s。     

滑转率对月球车车轮驱动力学特性的影响分析

应用车辆地面力学理论研究滑转率对月球车车轮挂钩牵引力、驱动效率以及功率消耗的影响.建立刚性车轮与松软月壤交互作用的动力学模型.通过实例对月球车车轮驱动动力学特性进行仿真分析.研究结果表明,车轮的挂钩牵引力、驱动效率以及驱动能耗均受到车轮滑转率的制约.存在一个最优的滑转率区间,在此区间内车轮可获得较大的挂钩牵引力、较高的驱动效率以及较低的驱动能耗.求取轮、地相对速度,对月球车车轮的地面摩擦力功率进行了估算.     

基于地面力学的月球车爬坡轮—地相互作用模型

月球车爬坡地面力学模型在月球车的设计、越障性能评价、控制和仿真等方面具有极其重要作用．利 用月球车轮地相互作用测试系统进行车轮爬坡性能实验,结合实验数据在传统车轮—土壤相互作用应力分布模型之 上推导出爬坡轮—地相互作用模型,同时考虑爬坡角度对浅层月壤应力分布的影响,提出了随滑转率变化的沉陷 因数经验公式,来反映月壤压实、刮带、侧向流动等引起的滑转沉陷．通过对应力分布公式进行积分转化得到集中 力／力矩计算模型,利用ADAMS 二次开发的柔性爬坡仿真环境并结合实验数据进行模型验证．在斜坡角度为16±, 载荷为100 N,当滑转率从0 增加到0.6 时,将模型的车轮斜坡法向载荷、挂钩牵引力和驱动力矩的计算值与实验数 据相对比,结果相对误差不超过10%,因而该爬坡模型可以有效地用于月球车轮地相互作用的力学计算．     

月球车驱动轮爬坡性能的影响因素研究

研究了驱动轮的滑转率、结构参数和载荷对月球车爬坡性能的影响。针对月表复杂路况下车辆通过性较差问题,为提高月球车爬坡性能,基于车辆地面力学中土壤的承压和剪切特性理论,建立了刚性驱动轮与月面斜坡松软月壤间的相互作用模型。通过车轮实例对月球车爬坡性能进行预测和分析。实验结果表明,增大驱动轮的滑转率、半径、宽度、轮刺高度和减小载荷能够增强月球车爬坡能力和提高车轮驱动效率,但随着爬坡能力的增强,车轮驱动效率呈现先增大后减小的趋势。研究结果为月球车轮结构设计以及控制策略的研究提供了参考。     

星球车松软星壤的轮腿式探测系统:Ⅱ-感知车轮

为增强星球车松软星壤的穿越通过能力,提出了轮壤交互接触信息的感知车轮设计。该车轮是一种星球车的前置轮腿式探测系统(WOLS)的关键部分,可实现动态轮壤交互的关键量测量(轮壤作用力/力矩、轮壤接触角和车轮沉陷量)。研究分析了轮壤力学的关键测量参量及其分组,完成了感知车轮的硬件设计和集成,提出了待测参数的在线测量模型和方法,通过标定校准和实车测试验证了该感知车轮的性能。     

一种车辆轮廓尺寸参数全自动测量系统

设计一种车辆轮廓尺寸参数全自动测量系统,该装置由测量支架、光电开关、摄像装置、测量雷达、照明装置等构成,能够准确测量处车辆的宽度、高度和轮间距等信息,该系统测量过程为实时,被测车辆在测量过程中不需要停车,只需要以正常车速通过测量区域后即有测量结果,测量效率高;测量误差<1%;适应环境广,可安装在室外或室内,安装过程简单。可用于车辆检测部门和交警部门查验违规改造的车辆。     

基于三维成像技术的四轮定位参数建模方法

鉴于现有四轮定位仪参数求取方法误差大、参数项目少、对测量环境要求高等不足,提出了一种基于三维成像技术的四轮定位参数建模方法;该方法通过双摄像机对目标板拍摄获得的图像信息,应用空间向量方法,求取车体运动状态下的轮轴信息,动态建立四轮定位参数测量模型,解决测量平面的动态建立、测量平台的补偿等问题;经过零标定平台测试,当车轮旋转在18~22°时,定位参数求取方法正确有效,通过实车对比测量验证,平均误差小于0.07°。     

具有CAN接口的低成本农用测速模块开发

针对一般轮速澍量模块无CAN总线接口且低速性能差价格高的问题,开发了一种具有CAN总线接口的农用低成本轮速传感器模块.该模块采用51系列单片机,通过测量安装在车轮附近的霍尔接近开关产生的脉冲周期信号来计算轮速,并通过CAN总线接口按照专用通信协议将速度值传送到其他控制设备,为变量作业控制设备提供实时可靠的速度信息.同时,通过专用通讯协议,能够时其进行参数设定,并在LCD屏上显示相关信息.所开发的测速模块实用性强、准确度高,具有广阔的应用前景.     

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

动态限载系统的设计和分析

提出了一种新的动态限载系统设计方案，主要功能是将动态的重量信号通过传感器转化成电信号，经过数字电路进行信号处理，由微机进行计算，根据车辆本身的信息，确定汽车是否超载，实现了全自动、不停车称重的功能。系统采取的数学模型在推导过程中，对时变非线性方程采用分段曲线拟合的处理方法，将动态测重转化为瞬时速度的测量和系统参数的辨识问题。试验结果表明在车速低于20km／h时，误差小于3％。     

车用ABS制动性能评价技术

本文采用的是一种硬件在环仿真技术,将实物汽车嵌入到仿真系统中,利用单轮模型相关理论依据求出轮胎即时转速,将转速信号送入实物汽车ECU中,ECU便控制压力调节电磁阀动作,以达到调节制动油路压力的目的,仿真计算机采集回压力信号,达到跟踪轮速的目的,从而也就实现了跟踪汽车纵向滑移率的目的。     

Relating Torque and Slip in an Odometric Model for an Autonomous Agricultural Vehicle

This paper describes a method of considering the slip that is experienced by the wheels of an agricultural autonomous guided vehicle such that the accuracy of dead-reckoning navigation may be improved. Traction models for off-road locomotion are reviewed. Using experimental data from an agricultural AGV, a simplified form suitable for vehicle navigation is derived. This simplified model relates measurements of the torques applied to the wheels with wheel slip, and is used as the basis of an observation model for odometric sensor data in the vehicle's extended Kalman filter (EKF) navigation system. The slip model parameters are included as states in the vehicle EKF so that the vehicle may adapt to changing surface properties. Results using real field data and a simulation of the vehicle EKF show that positional accuracy can be increased by a slip-aware odometric model, and that when used as part of a multi-sensor navigation system, the consistency of the EKF state estimator is improved.     

Exploiting wheel slips of mobile robots to improve navigation performance

Improving navigation performance of autonomous wheeled mobile robot (WMR) in a dynamic unstructured environment requires improved maneuverability. In such cases, the dynamics of wheel slip may violate the ideal no-slip kinematic constraints generally used to model nonholonomic WMR. In this paper, a new method is proposed to tackle the modeling inadequacy that arises when slip is neglected by including both longitudinal and lateral slip dynamics into the overall dynamics of the WMR. This new model of the WMR provides a realistic simulation environment that can be utilized to develop model-based controllers to improve WMR navigation. In this paper, a dynamic planner with a path-following controller is designed to allow the WMR to navigate efficiently by autonomously regulating the generated traction force due to wheel slip. Extensive simulation results demonstrate the importance of the proposed modeling technique to capture slip phenomenon and the efficacy of the presented control technique to exploit such slip for better navigation performance.     

线控转向系统全状态反馈控制策略的研究

为了根据车况和驾驶员喜好实现最优的操纵特性(不足转向、过度转向和中性转向),需要主动控制前轮转角.线控转向系统利用车辆全状态(横摆角速度和质心侧偏角)反馈控制策略优化驾驶员的转向输入,主动控制前轮转角来优化车辆的转向特性,高速时具有适当的不足转向特性,低速时具有适当的过度转向特性,从而在反应快速和安全性之间很好的权衡.其中通过状态观测器估计侧偏角.结果表明,在紧急操纵时可以代替驾驶员协调使车辆保持稳定,正常操纵时补偿物理参数或操纵条件的变化而保持操纵特性的一致.     

An intelligent approach to the lateral forces usage in controlling the vehicle yaw rate

A direct yaw moment control system (DYC) is designed to improve the handling and stability of a four‐wheel‐drive electric vehicle. The main task of this paper is to use the lateral forces in the process of optimally controlling vehicle stability. This is performed by defining a variable optimum region for the slip ratio of each wheel. A hierarchical structure is selected to design the control system. The higher‐level control system controls the yaw rate of the vehicle based on the fuzzy logic technique. The lower‐level control system, installed in each wheel, maintains the slip ratio of the same wheel within an optimum region using the fuzzy logic technique. This optimum region for each wheel is continuously modified based on the impact of the lateral force on the generated control yaw moment and the friction coefficient of the road. Therefore, an algorithm for estimation of the friction coefficient is proposed. Computer simulations are carried out to investigate the effectiveness of the proposed method. This is accomplished by comparison of the results of control methods with a fixed slip ratio region and the results of the proposed method with a variable slip ratio region in some maneuvers. The robustness of the proposed controller against hard braking and noise contamination, as well as the effect of steering wheel angle amplitude, is verified. The simulation results show that the influence of the proposed method on enhancing vehicle performance is significant. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于阿克曼原理的4WID/4WIS汽车循迹控制研究

针对四轮独立驱动、独立转向汽车循迹控制精度和转向稳定性兼容问题,同时考虑减小轮胎磨损,延长轮胎使用寿命,本文基于阿克曼转向原理和RBF神经网络PID理论,提出了一种自适应的循迹控制方法.首先,设计了基于RBF神经网络PID理论的自适应转向控制器,用于控制前内轮转角,保证循迹精度;其次,后内轮以减小质心侧偏角为目标进行辅助转向,保证转向稳定性;接着,基于阿克曼转向原理,确定外轮转角,保证各轮侧偏力分配合理;最后,采用同一瞬心法,确定各车轮转速,以减小轮胎滑动率.本文搭建了CarSim和MATLAB/Simulink联合仿真平台,进行了仿真实验,结果表明：本文提出的循迹控制方法,不仅能获得较小的循迹偏差和质心侧偏角,保证了足够的循迹控制精度和转向稳定性,同时还减小了轮胎滑动率,有利于减小轮胎的磨耗.     

In situ slip estimation for mobile robots in outdoor environments

Accounting for wheel–terrain interaction is crucial for navigation and traction control of mobile robots in outdoor environments and rough terrains. Wheel slip is one of the surface hazards that needs to be detected to mitigate against the risk of losing the robot's controllability or mission failure occurring. The open problems in the Terramechanics field addressed are (1) the need for in situ wheel-slippage estimation in harsh environments using low-cost/power and easy to integrate sensors, and (2) removing the need for prior information of the soil, which is not always available. This paper presents a novel slip estimation method that utilizes only two proprioceptive sensors (IMU and wheel encoder) to estimate the wheel slip using deep learning methods. It is experimentally shown to be real-world feasible in outdoor, uneven terrains without prior soil information assumptions. Comparison with previously used machine learning algorithms for continuous and discrete slip estimation problems show more than 9% and 14% improvement in estimation performance, respectively.     

Slip control for IWM vehicles based on hierarchical LQR

A proper dynamical model with the physical interconnection is necessary to accurately capture the slip phenomena of in-wheel-motored vehicles, since the wheels interact with each other through the vehicle body to make up the vehicle motion. Considering the uptrend in the number of in-wheel-motors, this paper proposes a way to effectively model the slip phenomena as a multi-agent dynamical system. A hierarchical LQR for time-varying interconnected system, which can significantly reduce the design burden, is presented for managing the wheel slip ratios properly, and the effectiveness of our proposed method is verified by both simulations and experiments.