Real-time weighted multi-objective model predictive controller for adaptive cruise control systems

In this paper, a novel spacing control law is developed for vehicles with adaptive cruise control (ACC) systems to perform spacing control mode. Rather than establishing a steady-state following distance behind a newly encountered vehicle to avoid collision, the proposed spacing control law based on model predictive control (MPC) further considers fuel economy and ride comfort. Firstly, a hierarchical control architecture is utilized in which a lower controller compensates for nonlinear longitudinal vehicle dynamics and enables to track the desired acceleration. The upper controller based on the proposed spacing control law is designed to compute the desired acceleration to maintain the control objectives. Moreover, the control objectives are then formulated into the model predictive control problem using acceleration and jerk limits as constrains. Furthermore, due to the complex driving conditions during in the transitional state, the traditional model predictive control algorithm with constant weight matrix cannot meet the requirement of improvement in the fuel economy and ride comfort. Therefore, a real-time weight tuning strategy is proposed to solve time-varying multi-objective control problems, where the weight of each objective can be adjusted with respect to different operating conditions. In addition, simulation results demonstrate that the ACC system with the proposed real-time weighted MPC (RW-MPC) can provide better performance than that using constant weight MPC (CW-MPC) in terms of fuel economy and ride comfort.     

7自由度主动悬架整车模型最优控制的研究

应用汽车系统动力学理论,建立了七自由度主动悬架的动力学模型。根据线性二次型最优控制原理设计了主动悬架线性二次型(LQR)控制器,并构建了实现该控制策略的主动悬架控制仿真模型。仿真结果表明:对主动悬架进行最优控制,能够有效地降低车身垂直振动加速度、车身侧倾角加速度和俯仰角加速度。     

基于预测恒定车头时距策略的自适应巡航控制研究

为了进一步提高车辆跟车过程中的跟踪性、安全性、舒适性和燃油经济性，针对已有间距策略表现过于保守或反应过于激烈等不足之处，提出了一种预测恒定车头时距策略。该策略考虑了相对加速度，建立了一种预测型期望车间距模型，进而应用于模型预测控制的多目标自适应巡航控制系统中，能进一步提高模型预测控制对多个控制目标的综合协调能力。搭建上层控制器、下层PID控制器、油门制动切换、逆纵向动力学模型。在多工况下仿真，通过建立性能评判指标对多目标进行量化分析。结果表明，所提出的间距策略在保证安全性的前提下，提升了自适应巡航控制系统的综合性能。在不同驾驶风格的车头时距下，跟踪性、舒适性和燃油经济性均有良好表现。     

基于磁流变阻尼器的半主动车辆座椅悬架模糊控制研究

设计基于磁流变阻尼器的半主动车辆座椅悬架系统的模糊控制器。用ADAMS对系统建立三维多刚体动力学模型,用MATLAB设计系统模糊控制器,并联合两者对整个系统进行仿真。仿真和台架试验结果表明,模糊控制策略能使该系统较好抑制垂直振动加速度,提高乘坐的舒适性。     

基于神经网络控制的半主动空气悬架仿真研究

以某空气悬架大客车1/4车辆模型为仿真对象,设计了模型参考神经网络自适应控制器,并以正弦和随机输入为路面激励,以簧载质量垂直方向振动加速度值为控制量,对模型进行了计算机仿真,从簧载质量加速度时间历程可以看出神经网络控制器对工况和结构参数的变化具有较好的自适应能力.     

电动汽车纵向加速度控制仿真研究

提出一种基于电动汽车变速均匀性控制的加速度模型,在对永磁同步电动机驱动系统分析的基础上,建立系统单变量CARIMA模型,采用递推最小二乘法对模型参数进行辨识;并设计速度预测PI控制器,以柔化加速度变动带来的冲击。最后对电动汽车的变速过程进行仿真,仿真结果表明:该方法能够实现对电动汽车纵向加速度的有效控制且鲁棒性强。     

Driver models for personalised driving assistance

We propose a learning-based driver modelling approach which can identify manoeuvres performed by drivers on the highway and predict the future driver inputs. We show how this approach can be applied to provide personalised driving assistance. In a first example, the driver model is used to predict unintentional lane departures and a model predictive controller is used to keep the car in the lane. In a second example, the driver model estimates the preferred acceleration of the driver during lane keeping, and a model predictive controller is implemented to provide a personalised adaptive cruise control. For both applications, we use a combination of real data and simulation to evaluate the proposed approaches.     

汽车主动悬架的单神经元自适应控制

在1/4汽车动力学模型的基础上,设计了汽车主动悬架的自适应神经元控制器。以车辆的行驶平顺性为主要控制目标,车身垂直加速度、悬架动挠度、车轮动位移为具体评价参数,研究了系统在随机路面激励条件下的时域响应,计算了振动响应的均方根值,考察了在变参数条件下控制器的鲁棒性。仿真结果表明,该控制器能有效改善车辆的综合性能,尤其是平顺性和舒适性,并且具有较好的鲁棒性,对模型参数的变化有一定的适应性。     

基于免疫算法的汽车主动悬架控制研究

应用免疫算法理论,以车身垂直加速度、悬架动行程和车轮动载为控制目标,设计了基于汽车1/4模型的主动悬架控制策略。该算法利用信息熵作为评价抗体亲和力的指标,具有多样识别能力、强鲁棒性和免疫记忆功能。仿真结果表明,基于免疫控制器的主动悬架对汽车的平顺性和操纵稳定性有较明显的改善。     

Investigation of the impact of locomotive creep control on wear under changing contact conditions

This paper presents the locomotive traction controller performance with respect to the track wear under different operation conditions. In particular, an investigation into the dynamic response of a locomotive under changing wheel–rail friction conditions is performed with an aim to determine the effect of controller setting on track wear. Simulation using a full-scale longitudinal–vertical locomotive dynamic model shows that the appropriately designed creep threshold, controller, settings can effectively maintain a high tractive effort while avoiding excessive rail damage due to wear, especially during acceleration under low speed.     

面向车道变换的路径规划及模型预测轨迹跟踪

为解决智能车辆在车道变换过程中的路径规划和路径跟踪问题,首先,利用梯形加速度法设计了车道变换虚拟理想轨迹,该路径规划方法的适应性取决于车道变换时间、横向加速度及变化率等关键变量的约束条件,因而对各关键变量之间的数学关系进行了定量计算,并绘制了不同工况下的车道变换虚拟理想轨迹,用于分析各关键变量对路径规划的影响;其次,建立了线性离散的车辆动力学预测模型,综合分析了车辆模型的控制输入、状态变量以及道路结构参数等约束条件,构建了多约束模型预测控制（MMPC）系统用于车道变换路径跟踪,并基于Hildreth二次规划算法对其目标函数进行了求解,获得前轮转向角控制量,从而保证智能车辆在车道变换过程中的路径跟踪性能及操纵稳定性能;最后,利用MATLAB和Carsim软件对提出的多约束模型预测控制系统进行联合仿真,并构建单约束模型预测控制（SMPC）系统与其进行性能比较,分别对车道变换时间为3 s和6 s时的车道变换性能进行比较分析。结果表明：当车道变换时间为6 s时,2种控制系统都能较好地实现车道变换功能;当车道变换时间为3 s时,与SMPC控制系统相比较,MMPC控制系统能够在有效跟踪期望行驶路径的同时改善车辆的操纵稳定性,从而提高车辆在路径跟踪过程中的主动安全性能。     

一种引入行驶状态识别的半主动悬架PID控制修正算法

基于车辆不同行驶状态（路面不平度和车速）下悬挂质量垂向加速度和悬架动挠度响应不相同的客观事实,针对半主动悬架PID控制器无自适应能力的局限,以悬挂质量垂向加速度和悬架动挠度响应作为车辆行驶状态的识别判据．建立起一种引入行驶状态识别的半主动悬架PID控制修正算法,进而以某型轿车为对象,采用MATLAB／Simulink建立起半主动悬架PID控制的仿真模型,针对不同行驶状态计算出PID控制算法修正前、后的车辆平顺性响应并加以对比,表明所提出的PID控制修正算法是有效的。     

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.     

High-speed optimal steering of a tractor–semitrailer

A high-speed optimal trailer steering controller for a tractor–semitrailer is discussed. A linear model of a tractor–semitrailer with steered trailer axles is described, and an optimal trailer steering controller is introduced. A path-following controller is derived to minimise the path-tracking error in steady-state manoeuvres using active trailer steering. A roll stability controller is introduced by adding the lateral acceleration of trailer centre of gravity as another objective in the steering controller, so as to improve roll stability in transient manoeuvres. A strategy to switch between these two control modes is demonstrated. Simulation results show that the steering controller can ensure good path tracking of articulated vehicles in steady-state manoeuvres and improve roll stability significantly in transient manoeuvres, while maintaining the path-tracking deviation within an acceptable range. Tests with an experimental tractor–semitrailer equipped with a high-bandwidth active steering system validate the controller design and simulation results. The roll stability controller reduces the measured rearward amplification by 27%.     

A combined-slip predictive control of vehicle stability with experimental verification

In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.     

半主动悬架模糊控制仿真

为缓和路面传递给车身的冲击,改善汽车行驶的平顺性和操作稳定性,文章建立了二自由度1／4车体半主动悬架非线性动力学模型,利用MATLAB模糊逻辑控制工具箱设计半主动悬架的模糊控制器,通过运用MATLAB／SIMULINK,对悬架系统进行了仿真分析。结果表明,该控制方法能有效地降低车身垂直加速度、悬架的动挠度和车轮动载荷,提高了汽车的平顺性和操纵稳定性。     

汽车转向与悬架系统的集成控制研究

在建立了汽车转向与悬架系统的综合模型的基础上,运用一种具有扩展的调节器结构LQG控制方法,设计了 主动悬架控制器,实现对车身横摆角速度、车身垂直加速度、车身侧倾角和俯仰角的集成控制,从而显著提高汽车的 平顺性、操纵稳定性和安全性。     

基于参数自调整模糊控制方法的半主动空气悬架仿真分析

基于参数自调整模糊控制方法对半主动空气悬架系统进行了仿真分析和试验验证．以某空气悬架大客车1／4车辆模型为仿真对象，设计了参数自调整的模糊控制器，并以随机路面为输入、悬架动行程为约束条件、簧载质量振动加速度和车轮动载荷为评价指标，对模型进行了计算机仿真，同时依据仿真模型设计了空气悬架试验台。仿真和试验结果表明，当汽车行驶工况变化时，引入参数自调整模糊控制方法可以有效降低簧载质量振动加速度和车轮动载荷。     

基于汽车车身垂直加速度的典型道路路面谱识别研究

以1/4汽车振动模型为研究对象,推导出以汽车车身垂直振动加速度作为输入信号、路面不平度作为输出信号的数学模型及其模拟图,并利用MATLAB/SIMULINK搭建系统模型求解路面不平度,对路面不平度进行谱估计完成路谱的识别。通过实际测试和数据处理分析,说明该方法理论依据正确可行,可以为虚拟样机仿真路面的生成提供数据支持。     

智能汽车轨迹跟踪与横摆稳定性协同控制

为了提高四轮独立驱动智能电动汽车在变曲率弯道下的轨迹跟踪精度和横摆稳定性,提出了一种模型预测控制与直接横摆力矩控制协同的综合控制方法。建立了横纵向耦合的车辆动力学模型,采用2阶龙格库塔离散法保证了离散模型的精度,并基于简化的2自由度动力学模型推导了车辆横摆稳定性约束,设计了非线性模型预测控制器;利用直接横摆力矩控制能够改变车辆横摆角速度和航向角的特点,考虑模型预测控制器的预测状态、控制量以及跟踪误差,设计了协同控制规则。仿真结果表明,协同控制方法解决了考虑横摆稳定性约束的模型预测控制器中存在的稳定性约束与控制精度相矛盾的问题,并补偿了模型预测控制器没有可行解时对横摆稳定性的约束,同时提高了智能汽车的轨迹跟踪精度和横摆稳定性。