铁路瓦斯隧道施工特点及问题探讨

通过对铁路瓦斯隧道现有施工规范分析,并参考《煤矿安全规程》,对铁路瓦斯隧道施工特点进行总结;同时通过对相关条款的分析、研究,并对照国内已发生的瓦斯隧道施工、低瓦斯矿井生产事故,对现有规范中存在的问题进行探讨,提出以下建议：1) 进一步明确进洞管理系统的标准和要求;2) 进一步明确和细化瓦斯隧道电力供应原则;3) 进一步明确和改进瓦斯隧道机电设备防爆性配备的原则和相关条款。     

����GA¬¬-BP�ĸ��ٹ�·����ѵ�ģ������������о�

鉴于模糊神经网络具有良好的非线性特性、学习能力、自适应能力和抗干扰能力,本文将模糊神经网络技术引入到高速公路入口匝道控制中。提出一种基于GA和BP算法的模糊神经网络控制器,并对控制器进行了详细设计。设计过程主要分为三部分：输入输出参数的选择、模糊神经网络的结构设计以及基于GA-BP的学习算法设计。最后,使用MATLAB软件对其进行了仿真。仿真结果表明,本文提出的方法是有效的,较之基于BP的模糊神经网络控制和ALINEA控制,能更好地稳定主线交通流密度。     

宝马车系诊断设备及电控发动机的重点组成部件

介绍宝马发动机电控系统诊断信息、车间诊断设备、电控发动机的重点组成部件。     

Fuzzy and adaptive fuzzy control for the automobiles’ active suspension system

Two typical criteria for good vehicle suspension performance are their ability to provide good road handling and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. This paper describes fuzzy and adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road holding and riding comfort over a wide range of road profiles. The efficacy of the proposed control schemes is demonstrated via simulations. With respect to the optimal linear quadratic regulator (LQR), it is shown that superior results have been achieved by the AFC.     

Optimal roll control of an articulated vehicle: theory and model validation

This paper investigates optimal roll control of an experimental articulated vehicle. The test vehicle and the mathematical model used to design the control strategies are presented. The vehicle model is validated against experimental data from the test vehicle in passive configuration. The initial controller design, performed by Sampson (Sampson, D.J.M. and Cebon, D., 2003a, Achievable roll stability of heavy road vehicles. Proc. Instn. Mech. Engrs, Part D, J. Automobile Engineering, 217(4), 269–287), is reviewed and adapted for the experimental vehicle. The effect of not controlling all the axles on the vehicle is investigated and a variable vehicle speed controller is designed by interpolating between constant speed controllers. Substantial reduction in normalized load transfer is achieved for a range of manoeuvres, both in steady-state and transient conditions.     

Fault tolerant nonlinear control with applications to an automated transit bus

This paper presents an integrated structure for a passive and active fault tolerant control (FTC) design approach in the framework of a robust nonlinear control technique called Dynamic Surface Control (DSC). As motivated by the automated vehicle application, we consider two categories of possible faults: pre-specified (a priori) and non-specified faults. It is first shown that DSC can be considered as a passive FTC approach in the sense that it gives simultaneous robust stability to a set of nonlinear systems even in the presence of model uncertainties and the pre-specified faults. Then, the non-specified fault is classified depending on the fault’s impact on the closed-loop system and isolatability from a fault detection and diagnosis (FDD) system. If a fault is both intolerable and isolatable, an active FTC approach is taken which includes FDD and controller reconfiguration. More specifically, trajectory reconfiguration is considered to accommodate the actuator fault, i.e., to compensate for the performance loss due to the fault within the framework of a switched hierarchical structure. Finally, the integrated structure for the longitudinal control of an automated transit bus is designed through the proposed method. Simulation results of the fault tolerant controller are shown for both single and multiple multiplicative faults. This controller was implemented on the California PATH transit buses in a demonstration of automated public transportation technology in San Diego, California in August of 2003.     

Heavy duty vehicle rollover detection and active roll control

This paper presents the results of a comprehensive study on heavy-duty vehicle (HDV) roll stability improvement technology. The proposed rollover threat warning system uses the real-time dynamic model-based time-to-rollover (TTR) metric as a basis for online rollover detections. Its feasibility for implementation in a HDV rollover threat detection system is demonstrated through vehicle dynamic simulation studies. The research on the development of a rollover threat detection system is further enhanced in combination with an active roll control system using active suspension mechanism to improve heavy-duty trucks’ roll stability both in the static cornering and in emergency maneuvers. It has been demonstrated that the roll stability of typical heavy-duty trucks has been largely improved by the proposed active safety monitoring and control system.     

A model-based traction control strategy non-reliant on wheel slip information

A traction control system (TCS) for two-wheel-drive vehicles can conveniently be realised by means of slip control. Such a TCS is modified in this paper in order to be applicable to four-wheel-drive vehicles and anti-lock braking systems, where slip information is not readily available. A reference vehicle model is used to estimate the vehicle velocity. The reference model is excited by a saw-tooth signal in order to adapt the slip for maximum tyre traction performance. The model-based TCS is made robust to vehicle modelling errors by extending it with (i) a superimposed loop of tyre static curve gradient control or (ii) a robust switching controller based on a bi-directional saw-tooth excitation signal. The proposed traction control strategies are verified by experiments and computer simulations.     

The IMMa optimisation algorithm without control input parameters

The IMMa optimisation algorithm (IOA) consists of a heuristic method based on a differential evolution algorithm for choosing the Magic Formula (MF) tyre model parameters. In a previous paper, we demonstrated that the IOA improved the searching procedure of optimum MF parameters with respect to the starting value optimisation (SVO) methods. But we had to introduce some control input parameters that were fixed during the running process. Now, the new version does not require control input variables to be chosen by the user. That is, we use an algorithm with self-adapting control parameters and it continues being easy to use, robust and fast. Hence, users do not need any kind of knowledge to use the IOA.     

Application of time-variant predictive control to modelling driver steering skill

The paper addresses the need for improved mathematical models of human steering control. A multiple-model structure for a driver's internal model of a nonlinear vehicle is proposed. The multiple-model structure potentially offers a straightforward way to represent a range of driver expertise. The internal model is combined with a model predictive steering controller. The controller generates a steering command through the minimisation of a cost function involving vehicle path error. A study of the controller performance during an aggressive, nonlinear steering manoeuvre is provided. Analysis of the controller performance reveals a reduction in the closed-loop controller bandwidth with increasing tyre saturation and fixed controller gains. A parameter study demonstrates that increasing the multiple-model density, increasing the weights on the path error, and increasing the controller knowledge range all improved the path following accuracy of the controller.