硬质路面条件下履带车辆转向模型分析及验证

履带车辆与地面之间的作用关系复杂,基于地面剪切位移的方法通常会用到对时间和位置的积分,模型较为复杂,无法直接应用到车辆的实时控制算法中。通常情况下,履带车辆转向分析会将接地压力看作连续线性分布或者多矩形分布,但是试验和计算结果均表明硬质土壤条件下,履带接地压力为多峰值分布,前述两种分布均不能体现接地压力的真实状态。本文针对上述问题,在前人研究的基础上,对履带接地压力分布进行求解,提出了履带车辆接地压力简化模型。该简化模型更符合硬质路面履带接地压力的真实状态,并被应用于履带车辆转向动力学分析与验证。利用J.Y.Wong提出的垂向负载-剪切位移变化关系解决了垂向压力变化的同时剪切位移计算的问题,提出了履带车辆转向分析模型(以下简称分析模型),试验结果表明该模型有较高的精度。但是其复杂度仍然较高,为了进一步简化模型,借鉴轮式车辆轮胎侧偏角和滑转率的概念,利用履带车辆履带-地面剪切位移关系推导了简化履带车辆动力学模型(以下简称简化模型)。该模型避免了复杂的积分或者求和,显著降低了履带车辆动力学模型的复杂度,能够应用于基于模型的无人驾驶履带车辆轨迹控制方法中,且模型精度接近前述履带车辆转向分析模...     

基于代理模型进化的履带车辆动力学参数优化

为解决履带车辆动力学优化过程因代理模型构建和应用的不足而导致的参数寻优精度和效率不高的问题,提出基于代理模型进化的参数优化方法,将优化迭代和代理模型动态构建相融合,来降低仿真模型调用次数和提高优化效率。根据车辆几何拓扑结构,构建考虑履带包络效应的车辆多体动力学模型;提出优化设计变量空间的3层子空间划分方法,以及具有空间聚焦、空间约简和跳出局部寻优的多级模糊聚类空间约简方法,实现设计参数在3层子空间的高效缩减。以履带车辆多体动力学模型参数优化过程为例进行应用验证。研究结果表明：在3种路况下的履带车辆多体动力学优化过程降低仿真模型调用次数最高可达85%;表征履带车辆行进特性的综合性能指标分别提升约32.4%、24.5%、20.4%。证明了新方法可有效提高动力学模型的优化效率和精度。     

多轮分布式驱动车辆可重构集成协调控制方法

多轮分布式独立驱动平台运动控制技术的演进对提升特种无人车辆的快速机动性及操纵稳定性具有重要的战略意义,然而其底盘主动执行系统的故障率或相互干涉的可能性也大大增加。提出一种面向该平台的可重构集成协调控制方法,以实现车辆动力学性能的进一步提升。基于自顶向下的分层控制结构,在运动控制层引入考虑参数不确定性的自适应滑模控制器,以保证对车辆运动目标状态的准确跟踪,并生成所需的广义控制力;在控制分配层提出一种加权伪逆控制分配器,基于控制效率矩阵的零空间特性,在主动执行器饱和约束可行域内进行再分配修正,以完成从广义控制力到各车轮处轮胎力的优化分配,其中引入的配置矩阵与优化权重系数则分别实现对控制模型的重新配置以及分配目标的调节;通过设置主动执行器实现分配目标的执行。基于6×6分布式电驱动车辆原理样机,进行两种工况下的仿真和试验验证。研究结果表明,该控制器提升了多轮车辆在转向过程中的操纵稳定性,并获得了更高效更精准的多轮车辆驱动力分配控制效果。     

基于MPC-MFAC的双侧独立电驱动无人履带车辆轨迹跟踪控制

简化模型带来的模型失配以及外部环境不确定性是导致轨迹跟踪误差的主要原因,尤其对于无人履带车辆,其复杂的物理特性和工作环境更放大了两大因素的不利影响。针对该问题,将基于模型和基于数据的控制方法结合起来,提出一种基于模型预测控制结合无模型自适应控制补偿的双侧独立电驱动无人履带车辆轨迹跟踪控制方法。在平衡建模准确度和求解耗时的基础上,利用模型预测控制进行前馈求解。针对模型预测控制中简化模型与车辆实际模型之间必然存在的差异以及环境不确定性,基于动态跟踪效果构建无模型自适应控制算法进行补偿,即利用车辆实际轨迹与模型预测所得轨迹之间的误差,对模型预测控制求解的两侧履带速度控制量进行实时修正。仿真实验结果表明,该方法能够在一定程度上抑制系统内外部不确定因素的影响,提高动态环境下双侧独立电驱动无人履带车辆轨迹跟踪控制的精度。     

微小型四旋翼飞行器的研究现状与关键技术

微小型化是世界无人机发展的重要方向之一.对一种新颖的微小型四旋翼无人飞行器进行了介绍,综合了微小型四旋翼飞行器的概念和特性,然后主要从机构设计和飞行控制两方面介绍了世界微小型四旋翼飞行器的发展现状,详细叙述了小型四旋翼飞行器的发展技术路线.在此基础之上,进一步分析了相关的关键技术问题,并对未来发展、应用前景作了展望.最后介绍了某微小型四旋翼飞行器研究进展情况.     

Modeling and performance analysis of VI‐CRA: A congestion control algorithm for vehicular networks

This study proposes a Vehicle ID‐based CAM Rate Adaptation (VI‐CRA) algorithm for beacon messages in the vehicular network. Foremost, an improved vehicle ID–based analytical model is proposed at the MAC layer of vehicular network. The model weighs the random back‐off number chosen by vehicles participating in the back‐off process, with the vehicle ID incorporated in their respective CAMs. This eventually leads to the selection of a vehicle ID–based random back‐off number, minimizing the probability of collision due to same back‐off number selection. It is worth noting that the improved analytical model outperforms the existing works in terms of average packet delay since only one fourth of the contention window size is used throughout the simulation. To enhance the performance of the analytical model, the paper incorporates a congestion control algorithm, by adapting the rate of CAM broadcast over the control channel. The algorithm is designed considering a wide range of scenarios, ranging from nonsaturated to extremely saturated network (in terms of collision probability) and sparsely distributed to teemed network (in terms of vehicular density). For better analyses of simulation results, the algorithm is applied over different vehicle ID–based back‐off numbers. Simulation results for all the back‐off numbers show that vehicle ID–based CAM rate adaptation algorithm performs better than the traditional fixed CAM rate IEEE 802.11p, even at high vehicular density.     

Software‐defined network‐enabled opportunistic offloading and charging scheme in multi‐unmanned aerial vehicle ecosystem

Unmanned aerial vehicles (UAVs) are autonomous fliers, which can play different roles in modern day applications. In one of the important role, UAVs can act as aerial data forwarding nodes for communication range enhancement in remote areas. UAVs form a web of drones, which can be geo‐distributed across a large area to serve various applications. However, the two major contradicting challenges with respect to multi‐UAV networks are channel congestion and flight time enhancement. The use of effective data transmission techniques to handle congestion can lead to higher battery dissipation, which in turn end up in the reduction in flight time. However, it is utmost necessity to provide an effective framework, which can provide a viable solution for handling congestion in multi‐UAV networks while enhancing the flight time of UAVs. To handle these issues, software‐defined network (SDN)–enabled opportunistic offloading and charging scheme (SOOCS) in multi‐UAV ecosystem is designed in this paper. In this scheme, an opportunistic offloading scheme is proposed, which uses an SDN‐based control model to handle congestion issues. Apart from this, an opportunistic energy‐charging scheme is designed, wherein the UAVS can either replenish their batteries using solar plates or they can wirelessly charge energy from charging points deployed at various geo‐distributed locations. The proposed scheme is evaluated using a simulation‐based study over the realistic deployment of charging points in Chandigarh City, India. The results obtained show the superiority of SOOCS over other variants of its category in terms of end‐to‐end delay, throughput, and hand‐over latency.     

高动态临近空间飞行器海上组网测控方案设计

为解决高动态临近空间飞行器海上测控对测量船数量需求较多、现有船队规模无法满足的难题,在分析测控需求特点的基础上,提出了一种基于测量船与临近空间飞艇组网测控的新模式。结合近中程、远程飞行试验分别进行了测控总体方案设计,并讨论了海上组网测控需要研究的关键技术。相关研究对我国后续开展高动态临近空间飞行器海上测控系统建设具有一定的参考价值。     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.     

磁阻发生装置设计及其在功率车中的应用研究

针对现有功率车在测试训练过程中由于踩踏速度的变化无法维持功率恒定的问题,设计了一种新型磁阻发生装置。 首 先,基于永磁同步电机的原理对磁阻装置基本结构进行设计,通过功率车的整体结构确定装置的基本结构尺寸,结合测试时所 需的最大功率确定电磁负荷,选择永磁体,再进行定转子的结构尺寸以及绕组连接形式设计,并确定径向气隙参数,最后,分析 了系统恒功率控制原理,并通过模糊 PID 控制与迭代学习控制(ILC)对系统恒功率控制效果进行了仿真与实验。 结果表明,新 型磁阻式功率车在踩踏速度在 60( ±10) r/ min 的范围内变化时,功率误差控制在±5 W 以内,可以接受。 采用新型磁阻发生装 置的功率车提高了恒功率控制效果,验证了其在维持恒功率方面的先进性。