智能车辆队列横纵向有限时间滑模控制

针对智能车辆队列横纵向控制及误差快速收敛问题,本文提出一种分布式横纵向有限时间滑模控制策略.首先,考虑跟踪误差的连锁反应及横纵向耦合效应,利用投影变换建立车辆队列横纵向误差模型,提出一种车辆队列横纵向控制框架.而后,针对误差快速收敛问题,设计非奇异积分终端滑模面(NITSM)与自适应幂次积分趋近律(APIRL),通过构造Lyapunov函数分析系统的有限时间稳定性与队列稳定性.最后,基于Trucksim/Simulink联合仿真以及实车实验进一步验证了本文方法的有效性.结果表明,本文所提方法能保证队列稳定性,并实现误差快速收敛,规避跟踪误差的连锁反应及车辆横向运动对纵向车间距误差的影响.     

SAS和EPS多Agent体协调控制系统

本文针对SAS和EPS系统协调控制的不足,引进了多智能体(Multi-Agent)理论控制技术。详细提出半主动悬架、电动助力转向、轮胎、故障诊断等智能体的属性和特点,基于分层递阶控制方法并结合多智能体理论,建立了集成系统协调求解机制,解决半主动悬架和电动助力转向的匹配和协调控制问题,为日后车辆大系统的集成控制研究做出了尝试和铺垫。     

车辆主动安全性的底盘子系统集成控制研究

为简化车辆控制系统结构及提高车辆行驶的主动安全性,采用底盘子系统分层协调结构对车辆纵向、侧向及垂向运动进行了集成控制。该集成控制采用主环路-伺服环路-子系统执行层的控制结构,在主环路上,考虑建模不确定性、扰动以及运动状态参数耦合,通过滑模控制跟踪车辆参考模型,获得车辆稳定行驶所需的期望广义力;在伺服环路上,考虑轮胎力非线性及其耦合关系,利用二次规划算法将广义力优化分配到子系统。特别是在集成控制中加入侧倾力矩分布控制,有效调控垂向载荷的内外侧转移,抑制车身的侧倾,对车辆主动安全性的改善起到一定的作用。仿真结果表明,底盘混合式分层协调控制提升了子系统工作潜力,可以有效跟踪期望运动轨迹,抑制了侧滑,提高了车辆的主动安全性。     

智能电动车EPS鲁棒性控制律的建模与仿真

智能电动汽车配备电动助力转向系统(EPS)以提高转向系统的稳定.EPS是非线性系统,为了改进其鲁棒性能,结合EPS的结构和动力学特性,建立了EPS的动力学方程.构建结合整车、轮胎、EPS系统的整体仿真模型,利用李雅普诺夫方法的克拉索夫斯基定理设计EPS控制律,并用李雅普诺夫再设计方法设计具有鲁棒性的EPS控制律.在多领域建模软件Dymola中对智能电动汽车转向系统建模,并进行阶跃仿真,结果表明,李雅普诺夫再设计方法得到的EPS控制律具有较强鲁棒性.     

不确定非线性多智能体系统的分布式模糊自适应镇定控制

针对一类具有未知非线性和未知参数摄动的非线性多智能体系统, 提出一种分布式模糊自适应镇定控制方法. 基于邻接智能体信息和部分智能体的自身信息, 分别设计静态耦合和动态耦合的分布式模糊自适应控制律. 基于Lyapunov 稳定性理论, 证明了所提出的控制器能使得系统状态最终稳定于原点的邻域内. 仿真实例验证了所提出方法的有效性.

     

导弹交流电动舵机的非线性解耦控制与仿真

针对交流电动舵机系统非线性,多变量和强耦合的特性,提出了一种基于微分几何方法和变结构控制理论的非线性解耦控制方法。建立了交流电动舵机的非线性模型,利用微分几何理论,通过对系统进行微分同胚变换和反馈变换,实现了非线性系统的精确线性化和输入/输出解耦,并针对电动舵机系统参数摄动和负载扰动的特点,利用指数趋近律设计了电动舵机的变结构控制器。仿真结果表明不仅可以有效地实现交流电动舵机系统的非线性解耦,具有良好的静、动态特性。     

小型无人直升机横纵向模型参数辨识方法

针对小型无人直升机具有多变量、非线性和强耦合的特点,提出一种基于参数辨识的横纵向通道动力学建模方法.该方法根据直升机小扰动运动学方程和小型无人直升机空气动力学特点,推导了小型无人直升机横纵向通道动力学模型.在悬停条件下通过对模型进行简化,得到小型无人直升机横纵向通道待辨识线性耦合模型.根据飞行实验数据,通过采用多变量最小二乘方法估计出该耦合模型的未知参数.模型预测数据和实际飞行数据的比较结果表明,所建模型能充分反映该小型无人直升机在悬停状态下的横纵向通道动力学特性,具有较高精度且结构相对简单,可作为自主飞行控制器设计的参考模型.     

智能车辆路径跟踪控制方法

为了提高智能车辆路径跟踪控制器的可靠性和控制精度,提出一种基于误差动力学模型的路径跟踪控制方法.基于车辆运动学模型和动力学模型建立系统误差动力学模型,并在此基础上推导出车辆路径跟踪控制的稳态控制律,利用李雅普诺夫稳定性理论验证稳态控制律的正确性.为了减小外部干扰对控制性能的影响,提高控制器的可靠性,进一步设计基于车辆侧向位移误差的瞬态控制律,并利用李雅普诺夫稳定性理论验证闭环系统的稳定性.稳态控制律和瞬态控制律构成了非线性的路径跟踪控制器.通过与车辆路径跟踪常用的线性控制器和非线性控制器对比验证所提出控制方法的有效性,线性控制器选用LQR控制器,非线性控制器选用Stanley控制器.仿真结果表明,与LQR控制器相比,所提出控制方法的路径跟踪控制精度、抗干扰性和可靠性更好.与Stanley控制器相比,所提出控制方法具有更好的路径跟踪控制精度和控制收敛速度,且在大曲率路径跟踪过程中具有更好的可靠性.     

先进布局无人机多目标自适应概率引导控制分配

针对先进布局无人机多操纵面冗余的控制分配问题, 提出一种基于自适应概率引导的混合多目标控制分配方法. 首先, 根据冗余舵面操纵特性, 建立带约束的舵面动态效能模型, 提出精度需求不同的混合多目标优化指标. 随后, 为了综合平衡各目标寻优精度与求解速度提出基于自适应概率引导的多目标粒子群控制分配方法. 该方法根据各目标最优值与期望精度差值构建自适应概率函数, 依概率选择全局最优解, 引导种群向各目标期望精度方向精细搜索以提升算法解算精度, 减少无用搜索以提高求解速度; 同时, 根据收敛性指标增加变异因子, 避免算法陷入局部最优. 最后, 仿真验证该方法可有效处理舵面耦合及非线性特性, 减少能耗损失, 实现操纵面多目标控制分配, 使得无人机快速平稳跟踪控制指令.     

四轮独立驱动电动汽车转向稳定控制

四轮驱动电动汽车在中高速转向行驶过程中,轮胎的非线性特性会使得汽车出现大摆动、侧滑、过度或不足转向等安全问题.针对可能出现的问题,提出了四轮驱动电动汽车转向稳定分层控制策略.上层横摆稳定控制器采用基于图表的滑模控制算法规划出使车辆转向稳定的附加横摆力矩.下层转矩优化分配控制器采用模型预测控制方法实现4个轮胎的转矩分配,...     

Integrated Dynamics Control and Energy Efficiency Optimization for Overactuated Electric Vehicles

A large number of studies have been conducted on the dynamics control of electric vehicles or on the optimization of their energy efficiency but few studies have looked at both of these together. In this study, an integrated dynamics control and energy efficiency optimization strategy is proposed for overactuated electric vehicles, where the control of both longitudinal and lateral dynamics is dealt with while the energy efficiency is optimized. First, considering the trade‐off between control performance and energy efficiency, criteria are defined to categorize the vehicle motion status as linear pure longitudinal motion and non‐linear motion or turning motion. Then different optimization targets are developed for different motion status. For the pure linear longitudinal motion and cornering motion, the energy efficiency and vehicle dynamics performance are equally important and a trade‐off control performance between them needs to be achieved. For the non‐linear turning motion, vehicle handling and stability performance are the primary concerns, and energy efficiency is a secondary target. Based on the defined targets, the desired longitudinal and lateral tyre forces and yaw moment are then optimally distributed to the wheel driving and steering torques. Finally numerical simulations are used to verify the effectiveness of the proposed strategies. The simulation results show that the proposed strategies can provide good dynamics control performance with less energy consumption.     

Velocity-based Lateral Stability Control for Four-wheel Independently Actuated Electric Vehicles with Homogeneous Polynomial Approach

This paper presents a control strategy to enhance the lateral dynamics stability and handling performance of the four-wheel independently actuated (FWIA) electric vehicles (EVs). The vehicle longitudinal velocity uncertainty and controller saturation are considered, a double layers control scheme is adopted. In the upper layer, the homogeneous polynomial parameter-dependent approach is introduced to track the uncertainty problem, and a multi-objective controller is designed to obtain the desired external yaw moment. In the lower layer, an optimal force distribution method with considering the distribution error and tire workload is employed to allocate the desired external yaw moment into forces of the four in-wheel motors. Simulation results verify the effectiveness of the proposed control strategy.

     

Resilient and Safe Platooning Control of Connected Automated Vehicles Against Intermittent Denial-of-Service Attacks

Connected automated vehicles (CAVs) serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety, and reducing fuel consumption and vehicle emissions. A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads. This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service (DoS) attacks that disrupt vehicle-to-vehicle communications. First, a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties, including diverse vehicle masses and engine inertial delays, unknown and nonlinear resistance forces, and a dynamic platoon leader. Then, a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability, attack resilience, platoon safety and scalability. Furthermore, a numerically efficient offline design algorithm for determining the desired platoon control law is developed, under which the platoon resilience against DoS attacks can be maximized but the anticipated stability, safety and scalability requirements remain preserved. Finally, extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.      

基于ROS平台的智能车运动线控系统设计及实现

针对无人操作智能车辆依靠特定硬件平台等问题,提出了一种基于ROS平台的无人小车的低成本运动线控系统解决方案。该方案基于上位机和下位机的控制结构,上位机代替驾驶员的功能负责决策,下位机负责执行命令。重点给出了上位机、下位机以及上下位机通信的软硬件设计思路和方法,并在ROS平台上使用了Modbus通信,构建了一个结构相对简单、功能可行的低速的无人车运动控制系统。该解决方案的所有软件都是开源或可自行设计的,为更多的研究人员以更低成本研究无人智能车提供了参考。实验结果表明,该运动控制系统解决方案是可行并且有效的,未来可应用于园区、学校等地的小型无人车的控制系统设计。     

智能交通系统车道保持纵横向耦合控制

考虑车辆纵横向运动之间的相互影响,采用位置预瞄和固定车辆间距跟随策略,对基于一列车队的自动化公路系统车道保持纵横向耦合控制进行了研究.利用车载前后双位置传感器检测车辆位置偏差,基于车辆纵横向动力学耦合模型,推导了基于预瞄的车道保持控制系统数学模型;采用非奇异的终端滑模控制技术,设计了车道保持纵横向耦合控制规律.通过构造李雅普诺夫函数,结合相平面方法,分析了控制系统的有限时间收敛性.采用6车辆编队,通过计算机仿真,对文中设计的控制规律进行了验证.仿真结果显示,车队中每个被控车辆在纵向上跟随期望状态的同时能够实现对期望车道轨迹的理想跟踪,跟踪误差精度不超过0.05 m.     

A novel integrated control framework of AFS,ASS, and DYC based on ideal roll angle to improve vehicle stability

The current research on vehicle stability control mainly focuses on following the ideal yaw rate and sideslip angle, without considering the potential of ideal roll angle in improving the vehicle stability. In addition, the mutation of tire-road friction coefficient promotes a great challenge to the stability control. To improve the vehicle stability, in this study, firstly, the three-dimensional stability region of “lateral speed-yaw rate-roll angle” was studied, and a method to determine the ideal roll angle was proposed. Secondly, a novel integrated control framework of AFS, ASS, and DYC based on ideal roll angle was proposed to actively control the front tire slip angles, suspension forces, and motor torques: In the upper-level controller, model predictive control and tire force distribution algorithm were used to obtain the optimal four-tire longitudinal forces, front tire lateral forces and additional roll moment under constraints; In the lower-level controller, the upper virtual target was realized by the optimal allocation algorithm of actuators and the tire slip controller. Finally, the proposed control framework was verified on the varied-µ road. The results indicated that compared with the two existing control strategies, the proposed framework can significantly improve the vehicle following performance and stability.     

Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

Intelligent vehicles can effectively improve traffic congestion and road traffic safety. Adaptive cruise following-control (ACFC) is a vital part of intelligent vehicles. In this paper, a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model, type-2 fuzzy control, feedforward + fuzzy proportion integration (PI) feedback (F+FPIF) control, and inverse longitudinal dynamics model of vehicles. Firstly, a traditional variable time headway model is improved considering the acceleration of the lead car. Secondly, an interval type-2 fuzzy logic controller (IT2 FLC) is designed for the upper structure of the ACFC system to simulate the driver’s operating habits. To reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration, the control strategy of F+FPIF is given for the lower control structure. Thirdly, the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method (no lower controller for tracking desired acceleration) separately. Meanwhile, the proportion integration differentiation (PID), linear quadratic regulator (LQR), subsection function control (SFC) and type-1 fuzzy logic control (T1 FLC) are respectively compared with the IT2 FLC in control performance under different scenes. Finally, the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.      

复杂环境中多无人智能车协同控制

该文对多无人智能车以领航-跟随法在复杂环境下运动的编队控制问题进行了探讨,通过采用闭环控制律设计了一种编队控制器和编队控制方案,该编队控制器的优点在于其主要考虑智能车之间的距离和角度,同时参考领航者与相邻跟随者之间的信息实现精准控制。基于所搭建的模拟测试环境,测试改进的控制方法与传统编队方法。实验结果显示,该文所提出的方法在复杂环境下具有更好的运动控制效果。     

基于agents系统的汽车转向制动稳定协同控制*

为了解决车辆转向过程中防抱死制动稳定性问题,提出multi-agents协同控制方法。首先利用黑板规则,根据转向系统和各个车轮agent状态以及整车状态进行任务协同,得到使汽车转向制动稳定的期望参考值。这些值可以自适应调节。其次在车辆伺服系统中采用改进自抗扰控制方法设计汽车纵向控制器和转向控制器,使伺服控制系统有更好的鲁棒性能进行精确跟踪期望输入命令。最后用仿真结果验证所设计的鲁棒自适应控制算法的稳定性和有效性。     

一种基于跟踪微分器的智能车辆加速度闭环控制方法

为了满足智能车辆进行L3及以上级别智能驾驶的需求,文章开发了一种基于跟踪微分器的加速度闭环控制方法.该方法采用跟踪微分器对加速度进行辨识,并对加速度进行闭环控制.其上层控制器根据车辆的当前速度、目标速度以及加速或者减速的距离计算一个加速度指令,并通过CAN网络将该指令发送到加速度闭环控制器中,从而实现对智能车辆进行加速...