基于双目视觉的车辆行驶跑偏在线自动检测系统

为了解决车辆行驶跑偏测量问题,研制了一种车辆行驶跑偏在线自动检测系统。该系统通过建立的双目机器视觉模型实现了车辆行驶跑偏量的自动测量,研制的大视场激光光源解决了测量中的环境干扰问题,采用优化数据处理算法解决了测量精度不高的难题,构建的无线网络测试系统实现了车辆行驶跑偏在线自动检测。该系统测量精度高、运行稳定可靠,可广泛应用于汽车生产企业及各种车辆检测线上车辆行驶跑偏量的在线自动测量。     

基于行驶工况的插电式混合动力公交车控制参数自动化标定方法

为解决行驶工况下插电式混合动力汽车控制参数仿真标定过程中标定参数选取缺少科学性和人工实时在线标定效率较低等问题,提出一种面向任意行驶工况的控制参数自动化标定方法。基于实际公交行驶工况,设计了正交试验对控制策略参数的油耗影响度进行分析,选取5个影响度较大的控制参数作为标定参数。利用优化算法自主寻优特性代替人工分析结果和调整参数,构建控制参数优化模型。利用Cruise、MicroAutoBox、Isight等工具开发出控制参数自动化标定的实时仿真平台。仿真结果表明：与人工标定相比,相同标定次数下自动化标定的时间缩短了75.51%,通过合理的转矩分配,减小了超级电容SOC的波动,标定后控制策略百公里燃油消耗降低了12.30％,从而验证了该标定方法的可行性。     

FORCE FEEDBACK MODEL OF ELECTRO-HYDRAULIC SERVO TELE-OPERATION ROBOT BASED ON VELOCITY CONTROL

The tele-operation robotic system which consists of an excavator as the construction robot, and two joysticks for operating the robot from a safe place are useful for performing restoration in damaged areas. In order to accomplish a precise task, the operator needs to feel a realistic sense of task force brought about from a feedback force between the fork glove of slave robot and unfamiliar environment. A novel force feedback model is proposed based on velocity control of cylinder to determine environment force acting on fork glove. Namely, the feedback force is formed by the error of displacement of joystick with velocity and driving force of piston, and the gain is calculated by the driving force and threshold of driving force of hydraulic cylinder. Moreover, the variable gain improved algorithm is developed to overcome the defect for grasping soft object. Experimental results for fork glove freedom of robotic system are provided to demonstrate the developed algorithm is available for grasping soft object.     

工程车辆智能自动变速控制系统仿真研究

智能换挡是车辆自动变速技术的发展方向.为此以最佳动力性作为控制目标,研究了工程车辆的动力换挡变速器如何实现智能化控制的问题.以装备有4D180型液力机械式变速器的 ZL50装载机为对象,建立了工程车辆动力传动系统仿真模型,在此基础上,应用混沌神经网络(CNN)设计了工程车辆自动换挡智能控制系统,并利用 Matlab 软件进行了仿真,仿真结果表明:所提出的智能换挡控制系统的结构和算法是可行的,可以实现工程车辆的自动换挡.     

基于MC9S12XS128单片机的汽车智能照明系统设计

基于MC9S12XS128单片机设计汽车智能照明系统,可根据车辆当前行驶路况选择合适的照明模式,极大地消除驾驶员视野盲区,提高行车安全系数。此系统还具有自动和手动两种控制方式,驾驶员可根据自身习惯和驾驶需要合理进行选择,有效降低驾驶者的视觉疲劳,使得设计更加符合人机工程原理。     

基于云控系统高精度地图驱动的深度强化学习型混合动力汽车集成控制

在智能化、网联化与新能源化的发展背景下,汽车工业将联合计算机、信息通信、人工智能等领域实现融合性发展。基于新一代信息与通信技术——智能网联汽车云控系统,通过网联数据驱动的形式实现新能源汽车的云控级自动驾驶,将为车辆行驶与动力系统提供革新的规划与控制思路。首先,基于云控系统的资源平台获取目标路段的经纬度、海拔、气象信息,建立包含坡度、曲率、转角等数据在内的高精度模型。其次,提出了一种基于高精地图驱动的深度强化学习型混合动力汽车集成控制方法,通过利用两种深度强化学习算法对整车层的速度与转向以及动力系统层的发动机与变速器进行控制,实现了四种控制策略的同步学习。最后,采用高性能边缘计算设备NVIDIA Jetson AGX Xavier进行了处理器在环测试。结果表明,当变量空间涉及14种状态与4种动作时,深度强化学习型集成控制策略在全程172 km的高速工况下实现了在整车层对速度与转向的精准控制,同时取得了5.53 L/100 km的燃油经济性,并且在嵌入式处理器在环测试中仅消耗104.14 s的计算时间,有效验证了学习型多目标集成控制策略的优化性与实时性。     

基于视觉的低空跟踪系统

构建了一个以无人飞行器为载体的基于视觉的低空跟踪系统。该系统由地面站和机载模块两部分组成,构建了机载自动跟踪与地面人工干预两个并联的控制回路;采用了基于灰度直方图的自适应容忍度多阈值分割算法,并在此基础上采用了基于双重子窗口的动态聚类目标提取方法;用目标的形心脱靶量作为云台的控制参数,根据目标的运动趋势对速度参数进行调整。系统通过用鼠标对监控视野中心的坐标替换目标的形心脱靶量实现机载自动跟踪和地面人工干预的平滑切换;保留不同照度下目标的灰度阈值,使得运动区域在阴影下也能被分割。经过2~3次的聚类迭代,较精确地计算出目标的形心位置,排除了干扰目标的影响,系统的处理速度达到15 frame/s。结果表明,上述算法和方法是可行的,系统具有较大的实用性。     

Design,implementation, and test of skid steering-based autonomous driving controller for a robotic vehicle with articulated suspension

This paper describes an autonomous driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consisted of four parts: speed controller for following the desired speed, trajectory tracking controller to track the desired trajectory, longitudinal tire force distribution algorithm which determines the optimal desired longitudinal tire force and wheel torque controller which determines the wheel torque command at each wheel to keep the slip ratio below the limit value as well as to track the desired tire force. The longitudinal and vertical tire force estimators were designed for optimal tire force distribution and wheel slip control. The dynamic model of the RVAS is validated using vehicle test data. Simulation and vehicle tests were conducted in order to evaluate the proposed driving control algorithm. Based on the simulation and test results, the proposed driving controller was shown to produces satisfactory trajectory tracking performance.     

Direct yaw moment control for distributed drive electric vehicle handling performance improvement

For a distributed drive electric vehicle (DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control (DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error (ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.     

Recursive least square vehicle mass estimation based on acceleration partition

Vehicle mass is an important parameter in vehicle dynamics control systems. Although many algorithms have been developed for the estimation of mass, none of them have yet taken into account the different types of resistance that occur under different conditions. This paper proposes a vehicle mass estimator. The estimator incorporates road gradient information in the longitudinal accelerometer signal, and it removes the road grade from the longitudinal dynamics of the vehicle. Then, two different recursive least square method （RLSM） schemes are proposed to estimate the driving resistance and the mass independently based on the acceleration partition under different conditions. A 6 DOF dynamic model of four In-wheel Motor Vehicle is built to assist in the design of the algorithm and in the setting of the parameters. The acceleration limits are determined to not only reduce the estimated error but also ensure enough data for the resistance estimation and mass estimation in some critical situations. The modification of the algorithm is also discussed to improve the result of the mass estimation. Experiment data on asphalt road, plastic runway, and gravel road and on sloping roads are used to validate the estimation algorithm. The adaptability of the algorithm is improved by using data collected under several critical operating conditions. The experimental results show the error of the estimation process to be within 2.6%, which indicates that the algorithm can estimate mass with great accuracy regardless of the road surface and gradient changes and that it may be valuable in engineering applications. This paper proposes a recursive least square vehicle mass estimation method based on acceleration partition.     

手动式冲孔打桩机自动化改进及稳定性研究

通过对传统手动式冲孔打桩机进行机械改装,采用飞思卡尔公司生产的MC9S12XS128芯片作为微控制器,添加气动装置,通过相关传感器检测冲孔打桩机的工作状态; 同时通过对FFT算法、余绳最优控制算法和专家系统等控制算法进行研究,以保证改进后的自动冲孔打桩机工作时的稳定性和可靠性。     

Driving Performance Analysis of the Adaptive Cruise Controlled Vehicle with a Virtual Reality Simulation System

Nowadays, with the advancement of computers, computer simulation linked with VR (Virtual Reality) technology has become a useful method for designing the automotive driving system. In this paper, the VR simulation system was developed to investigate the driving performances of the ASV (Advanced Safety Vehicle) equipped with an ACC (Adaptive Cruise Control) system. For this purpose, VR environment which generates visual and sound information of the vehicle, road, facilities, and terrain was organized for the realistic driving situation. Mathematical models of vehicle dynamic analysis, which includes the ACC algorithm, have been constructed for computer simulation. The ACC algorithm modulates the throttle and the brake functions of vehicles to regulate their speeds so that the vehicles can keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamics simulation with VR rendering. With the developed VR simulation system, several scenarios are applied to evaluate the adaptive cruise controlled vehicle for various driving situations.     

Test bed for vehicle longitudinal control using chassis dynamometer and virtual reality: An application to adaptive cruise control

In this study, a test bed for vehicle longitudinal control is developed using a chassis dynamometer and real time 3-D graphics. The proposed test bed system consist of a chassis dynamometer on which test vehicle can run longitudinally, a video system that shows virtual driver view, and computer that control the test vehicle and realize the real time 3-D graphics. The purpose of the proposed system is to test vehicle longitudinal control and warning algorithms such as Adaptive Cruise Control (ACC), stop and go systems, and collision warning systems. For acceleration and deceleration situations which only need throttle movements, a vehicle longitudinal spacing control algorithm has been tested on the test bed. The spacing control algorithm has been designed based on sliding mode control and road grade estimation scheme which utilizes the vehicle engine torque map and gear shift information.     

Stabilization of a bicycle with two-wheel steering and two-wheel driving by driving forces at low speed

Recently, the personal mobility vehicle (PMV), a vehicle suitable for personal use, has been developed. It moves at low speed and is sufficiently small that it can be ridden in pedestrian space. This vehicle is expected to be a new method of transportation that is practical and environmentally friendly. As one form of PMV, the authors propose a twowheel vehicle with two modes: a two-wheel steering and two-wheel driving bicycle mode and a parallel two-wheel mode. This vehicle has four electric motors, two for driving and two for steering, and one generator connected to the pedals. In the bicycle mode, the rider rotates the pedals to generate electric power, and the motors in the wheels produce torque using the generated energy. The front and rear wheels are steered by the electric motor according to the angle of the handle. Therefore, this bicycle is controlled by a steer-by-wire and a drive-by-wire system. In the parallel two-wheel mode, the vehicle is stabilized according to the theory of the inverted pendulum. In this paper, we focus on the bicycle mode and analyze its stability. Stabilizing the bicycle is not easy since the proposed vehicle has tires with small diameters and the traveling speed is assumed to be low. It is known that the stability of bicycles is tuned by adjusting the bicycle parameters and changing the rear steer angle. However, since we aim to use the vehicle in a narrow walking space at low speed, such conventional methods are not always suitable. The authors propose the stabilization of the bicycle using driving forces and design a controller using linear-quadratic control theory. The results of the numerical simulations show the proposed method is effective in stabilizing the bicycle. This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008. Chihiro Nakagawa received her M.S. degree in Department of Engineering Synthesis from University of Tokyo, Japan, in 2007. She is currently a doctoral student at the department at University of Tokyo and serves as a JSPS Research Fellow. Yoshihiro Suda received his Dr. Eng. degree in Department of Engineering Synthesis from University of Tokyo, Japan, in 1987. He is currently a Professor at the Institute of Industrial Science and the Director of Chiba Experiment Station, University of Tokyo. Kimihiko Nakano received his Dr. Eng. degree in Department of Engineering Synthesis from University of Tokyo, Japan, in 2000. He is currently an Associate Professor at the Institute of Industrial Science, University of Tokyo. Shoichiro Takehara received his Dr. Eng. degree in Department of Engineering Synthesis from Sophia University, Japan, in 2004. He is currently an Assistant Professor at the Department of Mechanical Engineering at Tokyo Metropoli-tan University.     

汽车TCS控制算法的研究

驱动力控制系统（Traction Control System,TCS）是在制动防抱死系统的基础上发展起来的一套主动安全控制系统,它根据汽车的行驶状况,通过采用适当的控制算法使汽车驱动轮在恶劣路面或复杂行驶条件下也能产生最佳的纵向驱动力,从而提高汽车的驱动性能和行驶稳定安全性能.通过时TCS控制原理的分析,明确滑转率的控制目标,结合TCS的控制方式,阐述TCS的常用控制算法,并对其进行比较,探讨TCS控制算法的选择依据和方法.     

电动轮式小车控制系统设计与可靠性分析

针对电动轮式小车驱动控制及可靠性问题,建立了动力、转向驱动控制系统。设计了一种电动轮式小车的动力及转向系统,并对其可靠性进行了分析和实验验证。动力部分由STM32作为主控制器,通过基于全桥驱动芯片IR2136的驱动电路对4个无刷直流电机进行驱动控制,转向部分由基于半桥驱动芯片IR2103的驱动电路驱动2个有刷直流电机进行转向控制,控制系统采用速度环、电流环双闭环,算法上采用模糊自适应比例-积分-微分(proportion integration differentiation,简称PID)算法。对系统可靠性进行实验并分析的结果表明,能够很好地跟随负载以及降低启动电流,使小车可靠运行。此驱动控制系统负载能力良好,启动电流小,安全稳定,转向精确,满足设施农业作业需求。     

超声电机伺服控制的研究评述

为改善超声电机性能,实现超声电机快速、准确、稳定的控制,对于超声电机的现有的伺服控制策略和方法进行评述和比较,并且根据超声电机运动机理不同于传统的电磁电机,具有复杂的动力学现象及时变、强非线性等特点,提出了基于参考模型的模糊神经网络控制方法、遗传算法或其他的组合控制方法将是适用于超声电机的控制策略。     

时栅角位移传感器自动检定系统

针对时栅角位移传感器产业化过程中产品质量检定环节采用人工检定方式导致工作效率低且容易产生漏记、错记进而影响产品质量检定的问题,研制了时栅角位移传感器自动检定系统。系统采用PMAC作为运动控制单元,以直驱电机作为驱动机构,有效减小传动环节误差,质量检定选用ELCOMAT3000型双轴电子自准直仪,全量程检定误差小于±0.25″。构建了参数化的直线梯形加速运动模型与产品质量检定算法,整个产品质量检定全部自动完成,检定精度高,工作效率得到有效提升,产品质量得到可靠的保证。     

Tunnel ventilation controller design using an RLS-based natural actor-critic algorithm

Tunnel ventilation systems provide drivers with a comfortable and safe driving environment by generating sufficient airflow and by diluting the concentration of noxious contaminants below an acceptable level. For that purpose, tunnel ventilation systems contain mechanical equipment such as jet-fans, blowers and dust collectors. These machines consume large amount of energy, therefore, it is necessary to have an efficient operating algorithm for tunnel ventilation in terms of energy savings and safe driving. In this paper, a new reinforcement learning (RL) method is applied as the control algorithm. In the process of formulating the reward of the tunnel ventilation system, which is a performance index to be maximized in the RL methodology, the following two objectives are of great interest: maintaining an adequate level of pollutants and minimizing power consumption. The RL control algorithm adopted in this research is based on an actor-critic architecture and natural gradient method. Due to its ability to achieve the truly steepest direction of gradients, the natural gradient method can be a promising route to improving the efficacy of the actor module. Also, the recursive least-squares (RLS) method is employed to the critic module in order to improve the efficiency by which data is used. Using actual data collected from an existing tunnel ventilation system, extensive simulation studies were performed. It was confirmed that the suggested algorithm achieved the desired control goals and, when compared to previously developed RL-based control algorithms, improved the performance considerably.     

基于光电传感器的智能小车自动寻迹控制系统

在智能车自动寻迹系统中,自动寻线、避障及速度控制是智能车自动寻迹控制的基本功能。用于检测路径引导线的光电传感器阵列采用发光二极管和光敏电阻制作,检测车速和障碍物的功能则采用反射式红外光电传感器FS-359F实现,采用单片机STC12C5A60S2作为控制器,通过PWM控制方式对驱动电机进行调速,并根据路面和车速信息进行转向控制。试验表明,采用上述光电传感器的智能小车寻迹控制系统实现了智能小车沿路径引导线自动避障行驶。系统体积小、成本低、性能稳定可靠。