贫燃条件下汽车尾气净化催化技术的发展与展望

本文介绍了用于贫燃发动机尾气，柴油机尾气净化催化技术的发展状况，对各种催化剂及其载体材料的性能进行了比较，提出了开发贫燃条件汽车尾气净化催化技术尚需解决的问题。     

国外柴油车减少排放污染的发展趋势

叙述了美国和欧共体柴油车排放法规和最新发展及世界主要固定柴油质量和规格的最新发展趋势，报道了柴油组成和性质对排放物影响的主要研究结果；分析了减少柴油车排放污染的主要措施，例如改进发动机、改进炼油工艺、采用尾气处理、采用颗粒物过滤－捕集器及采用减少尾气排污的三类柴油添加剂，最后提出了几点建议。     

Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles

An obstacle avoidance problem of rear-steered wheeled vehicles in consideration of the presence of uncertainties is addressed. Modelling errors and additional uncertainties are taken into consideration. Controller designs for driving and steering motors are designed. A proportional-derivative-type driving motor controller and a sliding-mode steering controller combined with radial basis function neural network (RBFNN) based estimators are proposed. The convergence properties of the RBFNN-based estimators are proven by the Stone–Weierstrass theorem. The stability of the proposed control law is proven using Lyapunov stability analysis. The obstacle avoidance strategy utilising the sliding surface adjustment to an existing navigation method is presented. It is concluded that the driving velocity and steering-angle performances of the proposed control system are satisfactory.     

Employing early model-based safety evaluation to iteratively derive E/E architecture design

ISO 26262 addresses development of safe in-vehicle functions by specifying methods potentially used in the design and development lifecycle. It does not indicate what is sufficient and leaves room for interpretation. Yet the architects of electric/electronic systems need design boundaries to make decisions during architecture evolutionary design without adding a risk of late changes. Correct selection of safety mechanisms from alternatives at early design stages is vital for time-to-market of critical systems. In this paper we present and discuss an iterative architecture design and refinement process that is centered around ISO 26262 requirements and model-based analysis of safety-related metrics. This process simplifies identification of the most sensitive parts of the architecture, selection of the best suitable safety mechanisms to reduce thereby failure rate on the system level and improve the metrics defined by the standard. To support the defined process we present the metamodels that can be integrated with existing DSL (domain-specific language) frameworks to extend them with information supporting further extraction of fault propagation behavior. We provide a framework for architecture model analysis and selection of safety mechanisms. We provide details on the model-based toolset that has been developed to support the proposed analysis and synthesis methods, and demonstrate its application to analysis of a steer-by-wire system model and selection of safety mechanisms for it.     

Adaptive tracking control of an autonomous underwater vehicle

This paper presents the trajectory tracking control of an autonomous underwater vehicle(AUV). To cope with parametric uncertainties owing to the hydrodynamic effect, an adaptive control law is developed for the AUV to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results under hydrodynamic parametric uncertainties.Stability of the developed controller is verified using the Lyapunov s direct method. Numerical simulations are carried out to study the efficacy of the proposed adaptive controller.     

Sliding‐Mode Velocity Control of a Two‐Wheeled Self‐Balancing Vehicle

Underactuated vehicles are those in which the number of control inputs is less than the degrees of freedom to be controlled. Using actuated wheels, velocity control of the two‐wheeled self‐balancing vehicle drives the vehicle at a desired speed and balances the body of the vehicle. First, we investigate the effects of friction on the wheel and derive the hybrid model of rolling and slipping. Second, we propose a nonlinear sliding mode velocity control scheme for the pure rolling model of the two‐wheeled vehicle. We present the design of the corresponding sliding surfaces and internal dynamics of the two‐wheeled vehicle. Our stability analysis reveals that the proposed sliding mode method can guarantee the asymptotic stability of the error dynamics for velocity control of the underactuated vehicle. Compared to linear optimal control, our numerical simulations demonstrate that the proposed sliding mode schemes can effectively control the velocity under the circumstances of parametric variations, emergency braking, and rapid acceleration in slippery road conditions. The proposed velocity control and the simulation improve our understanding on designing velocity control of the two‐wheeled self‐balancing vehicle.     

基于参数依赖滚动时域H∞控制的高超声速飞行器控制

针对输入受限的高超声速飞行器强耦合、强非线性以及严重不确定性的特点,提出一种参数依赖滚动时域?∞控制(PD-RHHC)的方法.首先在考虑控制输入约束的条件下,引入参数依赖Lyapunov函数和松弛因子并提出了基于LMI优化的PD-RHHC;然后采用函数替换方法,结合张量积模型转换方法实现高超声速飞行器(HSV)纵向非线性弹性模型的LPV描述,并将PD-RHHC应用到高超声速飞行器纵向控制中,以实现HSV在大飞行包线内的机动飞行;最后通过仿真实验验证了所提出算法的有效性.     

求解整合资源条件下的运输调度问题

针对传统的物流运输调度问题(Vehicle Routing Problem,VRP)中车辆之间不协作会造成资源浪费的情况,提出整合资源条件下的运输调度问题(Vehicle Routing Problem with Integration of resources,VRPIR),建立了相应的数学模型。由于混沌具有良好的遍历性,而粒子群优化算法(Particle Swarm Optimization,PSO)具有概念简单,参数少,容易实现等优点,将混沌优化方法引入到粒子群优化算法中,应用混沌粒子群优化算法(Chaos Particle Swarm Algorithm,CPSO)求解VRPIR和VRP,并用CPSO和PSO分别求解VRPIR,实验结果证明该算法优于粒子群优化算法,也证明了提出的VRPIR模型优于VRP,能节省资源,且最小化成本。     

基于混沌蚁群算法的应急救援车辆调度优化

针对应急救援车辆调度优化问题的特征和需求,以可变双向距离、道路风险和成本最小为主要目标,建立了应急救援车辆调度优化问题的多目标优化模型.为避免过早陷入局部最优,提出了基于混沌扰动的改进蚁群系统优化算法.该算法可对信息素进行全局更新混沌扰动,有效地提高了算法的适应性、求解效率和求解质量.仿真实验表明该算法是可行的,能较好地满足应急救援车辆调度的优化需求.