Active control strategy for the running attitude of high-speed train under strong crosswind condition

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host–target computer technology provided by Matlab/Simulink.     

Second-order sliding mode controller with model reference adaptation for automatic train operation

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.     

Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces

Although backstepping control design approach has been widely utilised in many practical systems, little effort has been made in applying this useful method to train systems. The main purpose of this paper is to apply this popular control design technique to speed and position tracking control of high-speed trains. By integrating adaptive control with backstepping control, we develop a control scheme that is able to address not only the traction and braking dynamics ignored in most existing methods, but also the uncertain friction and aerodynamic drag forces arisen from uncertain resistance coefficients. As such, the resultant control algorithms are able to achieve high precision train position and speed tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations.     

Real-time multiple-model estimation of centre of gravity position in automotive vehicles

In this paper, we present a methodology based on multiple models and switching for real-time estimation of centre of gravity (CG) position in automotive vehicles. The method utilises well-known simple linear vehicle models for lateral and roll dynamics and assumes the availability of standard stock automotive sensors. We illustrate the technique with numerical simulations as well as with measured sensor data from an sport utility vehicle. We also compare our estimation results with traditional linear least-squares estimators to show the efficacy of our technique. Finally, we give a simple application example for implementing the idea in automotive vehicles as a switch for rollover controller activation.     

An adaptive fuzzy-sliding lateral control strategy of automated vehicles based on vision navigation

Lateral control is considered to be one of the toughest challenges in the development of automated vehicles due to their features of nonlinearities, parametric uncertainties and external disturbances. In order to overcome these difficulties, an adaptive fuzzy-sliding mode control strategy used for lateral control of vision-based automated vehicles is proposed in this paper. First, a vision algorithm is designed to provide accurate location information of vehicle relative to reference path. Then, an adaptive fuzzy-sliding mode lateral controller is proposed to counteract parametric uncertainties and strong nonlinearities, and the asymptotic stability of the closed-loop lateral control system is proven by the Lyapunov theory. Finally, experimental results indicate that the proposed algorithm can achieve favourable tracking performance, and it has strong robustness.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

铣刨机自功率控制系统的研究

针对铣刨机的作业特点,分析了铣刨机的自功率控制原理,提出了铣刨机自功率控制方案,最后应用可编程控制器(PLC)完成了控制系统的硬件与软件设计.     

A comprehensive review of the development of adaptive cruise control systems

It has been 15 years since the first generation of adaptive cruise control (ACC)-equipped vehicles was available on the market and 7 years since the ISO standard for the first generation of ACC systems was produced. Since the next generation of ACC systems and more advanced driver-assistant systems are at the verge of complete introduction and deployment, it is necessary to summarise the development and research achievements of the first generation of ACC systems in order to provide more useful experiential guidance for the new deployment. From multidimensional perspectives, this paper looks into the related development and research achievements to objectively and comprehensively introduce an ACC system to researchers, automakers, governments and consumers. It attempts to simply explain what an ACC system is and how it operates from a systematic perspective. Then, it clearly draws a broad historical picture of ACC development by splitting the entire history into three different phases. Finally, the most significant research findings-related ACC systems have been reviewed and summarised from the human, traffic and social perspectives respectively.     

高速列车动载下岩溶盾构隧道动力响应分析

为了更好地分析岩溶盾构隧道在高速列车荷载作用下盾构管片及地层的动力响应,利用FLAC3D有限差分软件对其进行了数值模拟。研究表明:地层竖向位移分布呈不对称状态,左侧竖向位移较小,右侧竖向位移较大,位移等值线斜向上发展。管片下部与左侧围岩竖向位移衰减较快,上部及右侧围岩竖向位移衰减较慢。行车动载引起的管片环位移响应主要发生在竖向,总体趋势为右侧比左侧大,所以管片有整体顺时针旋转趋势,下部竖向位移大于上部竖向位移,管片环发生竖向椭变。     

高速铁路声屏障气动特性仿真分析

基于三维粘性非稳态可压缩Navier-Stokes方程和k-ε两方程紊流模型,采用有限体积法对高速列车通过时声屏障上气体压力和气动作用力进行计算。分析了两种高度、三种形式声屏障和四种列车运行速度条件下,单车通过与会车过程中的声屏障气动特性。结果表明:列车通过时,直立板型声屏障所受单位长度气动力最小,倒L型声屏障最大,内倾45°型居中;不同类型声屏障单位长度上气动力与列车运行速度均成2次方函数关系。会车过程中作用在声屏障上气动作用力大于单车通过时相应的气动作用力。     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

The performance improvements of train suspension systems with mechanical networks employing inerters

This paper investigates the performance benefits of train suspension systems employing a new mechanical network element called an inerter. An inerter is a true mechanical two-terminal element with the applied force proportional to the relative acceleration across the terminals. Until now, ideal inerters have been applied to car and motorcycle suspension systems, for which a significant performance improvement was reported. In this paper, we discuss the performance benefits of train suspension systems employing inerters. The study was carried out in three phases. First, fixed suspension structures were applied to train suspension systems, and optimised for two performance measures. Secondly, this optimisation was further carried out using linear matrix inequality approaches to discuss the achievable performance of passive networks. The resulting networks can then be realised by synthesis methods, such as the Brune and Bott–Duffin realisation. Finally, the nonlinear properties of inerter models and their impact on system performance were discussed. From the results, the inerter was deemed effective in improving the performance of train suspension systems.     

汽车半主动悬架的模型参考自适应控制

在1／4车辆动力学模型的基础上，基于李雅普诺夫稳定性理论，以天棚阻尼半主动悬架为参考模型，设计了半主动悬架模型参考自适应控制器。自适应控制器包括可调前置控制器和状态反馈控制器两个部分。推导了自适应控制律与相应的约束条件。仿真结果表明：该控制器对于模型参数的不确定性具有良好的鲁棒特性。自适应控制器不仅明显降低了车身加速度，提高了平顺性，同时也使汽车的行驶安全性获得了改善，悬架动变形稍有增大。     

Implementation and verification of adaptive longitudinal traction control

Human in the loop (HIL) simulation has experienced a significant increase in popularity in recent years. In this work, a novel approach to traction control is developed and implemented in a HIL environment, exploiting the significant advantages of framing the problem in a manner that more closely matches how a human expert drives a vehicle. An adaptive gradient ascent algorithm is at the heart of the proposed solution to longitudinal traction control. A real-time implementation of the gradient ascent algorithm is developed using linear operator techniques, even though the tyre–ground interface is highly non-linear. The adaptive traction control algorithm is based on two separate, but related, estimation algorithms that estimate both the instantaneous traction force and a unique predictive traction force model. This adaptive control algorithm, the necessary estimation algorithms and their real-time implementation are described in this work. The results, when implemented as a driver assist application on a 6-DOF motion platform, with a HIL, are also presented. This work demonstrates the utility of a 6-DOF motion platform in developing and verifying vehicle control algorithms with a HIL.     

工程车辆液压行走驱动系统模糊自适应PID控制策略研究

在现有工程机械PID控制器的基础上,利用模糊推理实现了对PID参数在线自整定模糊自适应控制,并且在MATLAB软件下将该控制器在车辆液压底盘试验台系统中的应用进行了研究,仿真结果表明,参数自适应模糊PID控制能使系统达到满意的控制效果.     

Influence of long-wavelength track irregularities on the motion of a high-speed train

Vertical track irregularities over viaducts in high-speed rail systems could be possibly caused by concrete creep if pre-stressed concrete bridges are used. For bridge spans that are almost uniformly distributed, track irregularity exhibits a near-regular wave profile that excites car bodies as a high-speed train moves over the bridge system. A long-wavelength irregularity induces low-frequency excitation that may be close to the natural frequencies of the train suspension system, thereby causing significant vibration of the car body. This paper investigates the relationship between the levels of car vibration, bridge vibration, track irregularity, and the train speed. First, this study investigates the vibration levels of a high-speed train and bridge system using 3D finite-element (FE) transient dynamic analysis, before and after adjustment of vertical track irregularities by means of installing shimming plates under rail pads. The analysis models are validated by in situ measurements and on-board measurement. Parametric studies of car body vibration and bridge vibration under three different levels of track irregularity at five train speeds and over two bridge span lengths are conducted using the FE model. Finally, a discontinuous shimming pattern is proposed to avoid vehicle suspension resonance.     

Vibration control in train–bridge–track systems

To study the problems associated with vibration control of train–bridge–track systems a mathematical model with the capability of representing supplementary vibrational control devices is proposed. The train system is assumed as rigid bodies supported on double-deck suspension mechanism with semi-active features. The bridge system is modeled using the modal approach. Vibration control for bridge responses is provided by tuned mass dampers. A non-classical incremental Eigen analysis is proposed to trace the system characteristics across the time. In an example, the capability of the proposed model in investigating the vibration control prospects of a bridge–train system is shown. The results indicate the effectiveness of active suspension mechanism in reducing train's body movements, particularly the pitching angle and the vertical accelerations. Accordingly, the results also verify the potential of TMD devices in reducing the bridge responses at resonance motions.     

Optimal design of adaptive shaking vibration control for electric vehicles

This paper provides a complete design solution about adaptive optimal shaking vibration control for electric vehicles. A general 4-DOF and 5-order linear torsional vibration model is established under given wheel speed, and the frequency characteristics of the vibration system are elaborately analysed in terms of variation of wheel speed and different model parameters. Aiming at decreasing the shaking vibration at the least sacrifice of acceleration loss, and improving the robustness of the system against external disturbance, a combination of feed-forward and feed-backward adaptive control structure is proposed. Further, a non-linear multi-constraint optimisation problem is formulated for solving the optimal adaptive control variables within the two-dimensional design space composed of the wheel speed and driver's torque command. Furthermore, the distribution of the optimal adaptive control variables within the design space and its extended application under different tyre road conditions are discussed. Eventually, several simulation test cases are particularly designed to verify the performances of the controller on all aspects. Test results show that the optimal adaptive controller achieves satisfactory anti-shaking vibration, acceleration maintaining and robustness performances within the whole adaptive design space as desired.     

考虑驾驶策略的高速列车运行图节能优化方法

为了降低高速列车从始发站至终到站运行的牵引能耗, 研究了针对多列车区间运行时分同步分配的列车运行图节能优化方法。基于高速列车在站间采用的“四阶段”操纵策略构建最优驾驶策略集, 以牵引距离和巡航距离为变化因子, 以牵引能耗和区间运行时分为计算目标, 求解出最优驾驶策略集里牵引能耗与区间运行时分的线性关系。在此基础上构建多列车区间运行时分最优分配的节能运行图模型。模型以牵引能耗最低为目标, 考虑了列车总运行时间约束、变量取值范围约束以及安全间隔时分约束。在模型求解方面, 选取拉格朗日松弛算法, 将复杂约束松弛至目标函数当中, 从而把原问题分解为各区间可独立求解的子问题, 利用次梯度优化的方法得出精确解, 实现了多列车区间运行时分同步分配的目标。以宝兰高速铁路为背景进行算例验证, 结果表明: 通过重新分配区间运行时分, 10列车总共节约了595.958 kW·h牵引能耗, 平均节能率达到了1.2%;从运行图的层面分析, 该算例下通过调整区间运行时分的节能方法对其影响幅度较小, 具有较强的现实意义; 所提出的模型及算法的计算时间为10 s, 针对列车开行对数较多的高速铁路, 可有效提高求解效率。     

基于自适应模糊PI的汽车直接摆力矩控制研究

针对汽车直接横摆力矩控制,论文研究了基于自适应模糊PI的控制方法。设计了基于自适应模糊PI的附加横摆力矩决策控制器和基于规则分配的制动力分配器。横摆力矩决策控制器根据汽车横摆角速度期望值和车辆状态决策出所需的附加横摆力矩,通过规则制动力分配方法进行主动差动制动实现,并采用Matlab/Simulink与CarSim联合仿真对控制方法进行仿真试验验证。结果表明:基于自适应模糊PI的横摆力矩控制方法相对于未控制能够使汽车较好地跟踪期望,有效提高汽车操纵稳定性。