一种可搜索无限个邻域的改进A*算法

传统A*算法在栅格地图上进行路径规划时,求解得到的路径长度不是最短并且转折点较多.针对这些不足,提出了一种改进A*算法,将传统A*算法的可搜索邻域个数从离散的8个拓展为无限个,可以沿任意方向进行搜索.这样不仅求解出来的路径长度更短,并且大大降低了其转折点的个数.该算法被应用于自主研发的"智能先锋"号系列无人驾驶车辆上,实车试验以及它们在"中国智能车未来挑战赛"中的优异表现证明该方法能够在栅格地图中求解出一条更优的可行驶路径,可以显著提升无人驾驶车辆行驶的效率和平稳性.     

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。     

车辆荷载对浅埋大断面隧道围岩的影响研究

依托在建的甸头隧道,开展隧道开挖是否考虑初期支护下车辆荷载对围岩及大西二级公路的影响研究。结果表明:隧道开挖引起隧道顶部及腰部发生沉降,底部发生隆起,初衬的施加可以有效抑制隧道周边围岩的变形,且可减小车辆荷载对围岩位移的影响;三台阶开挖时,隧道中部开挖引起地表发生剧烈沉降,初衬的施加可以减小地表的沉降,减小车辆荷载对地表沉降的影响。因此,无初支的情况下,当公路有车辆通过时,隧道整体变形较大,路面可能由于差异沉降产生裂缝。     

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.     

An integrated approach to hypersonic entry attitude control

This paper presents an integrated approach based on dynamic inversion(DI)and active disturbance rejection control(ADRC)to the entry attitude control of a generic hypersonic vehicle(GHV).DI is frstly used to cancel the nonlinearities of the GHV entry model to construct a basic attitude controller.To enhance the control performance and system robustness to inevitable disturbances,ADRC techniques,including the arranged transient process(ATP),nonlinear feedback(NF),and most importantly the extended state observer(ESO),are integrated with the basic DI controller.As one primary task,the stability and estimation error of the second-order nonlinear ESO are analyzed from a brand new perspective:the nonlinear ESO is treated as a specifc form of forced Li′enard system.Abundant qualitative properties of the Li′enard system are utilized to yield comprehensive theorems on nonlinear ESO solution behaviors,such as the boundedness,convergence,and existence of periodic solutions.Phase portraits of ESO estimation error dynamics are given to validate our analysis.At last,three groups of simulations,including comparative simulations with modeling errors,Monte Carlo runs with parametric uncertainties,and a six degrees-of-freedom reference entry trajectory tracking are executed,which demonstrate the superiority of the proposed integrated controller over the basic DI controller.     

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.     

改进型蚁群算法参数优化研究

研究在不使用局部搜索情况下参数组合对改进型蚁群算法的影响。以带时间窗的车辆路径问题为例,针对基于最大最小蚁群算法的改进蚁群算法中的五个参数,运用均匀设计法对最优参数配置问题进行了研究。仿真实验表明改进的蚁群算法效果明显,能有效解决Solomon数据集中的R类和RC类问题,且具有较强的鲁棒性。对最优参数的局部调整没有明显提高算法获取最优解能力的问题,分析了其可能的原因。     

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.