Integrated control of ground vehicles dynamics via advanced terminal sliding mode control

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.     

汽车线控转向系统的关键技术及发展前景

线控转向（ Steer-By-Wire,SBW）系统,指通过通讯网络连接各部件的控制系统,取消了传统的机械式转向装置,转向器与转向柱间无机械连接。该系统转动效率高,响应时间快,降低车辆底盘开发成本,改善车辆驾驶特性,并且利于环境的保护,在一定程度上提高了车辆的操纵稳定性、汽车碰撞安全性和整车主动安全性等。主要研究了汽车线控转向系统的关键技术,对线控转向技术的发展进行了前景的展望。     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。     

汽车主动悬架与电动助力转向系统自适应模糊集成控制

建立了包含转向运动模型、俯仰运动模型和侧倾运动模型的汽车整车模型,在设计了电动助力转向系统PD控制的基础上,构建了基于自适应模糊控制的汽车主动悬架与电动助力转向系统集成控制器,当控制系统偏差变小或变大时,调整因子总能保证系统稳定,便于工程应用。计算结果表明,该自适应模糊集成控制策略,既保证了车辆操纵轻便性,又显著提高了整车操纵稳定性、安全性和行驶平顺性等整车综合性能。     

基于增益模糊滑模变结构的线控液压转向控制

在分析全液压转向结构与转向偏差机理的基础上,设计了一种线控液压转向系统以实现车辆转向同步,消除转向偏差;针对现有方法确定的期望转向曲线可跟踪性差而无法实现转向同步,提出一种基于转向效率的期望转向曲线及其可行域确定方法,以最大、最小转向效率对应转向曲线为期望转向曲线可行域的上、下边界,确保期望转向曲线的可跟踪性;针对系统扰动不确定性及油液泄漏非线性,基于组合趋近律滑模控制,并引入饱和函数代替符号函数,在一定程度上抑制了控制系统的抖振;由于组合趋近律增益自适应性不足,导致车轮转角及角速度发生变化时,存在系统动态响应能力差的问题,通过分析车轮转角、角速度与趋近律增益的关系,制定了基于车轮转角及角速度的模糊规则表以自适应调整趋近律增益,实现增益模糊滑模控制,进一步提高油液补偿自适应能力和线控液压转向系统的鲁棒性;最后基于MATLAB/Simulink进行了仿真和试验验证。结果表明：提出的基于转向效率的期望转向曲线均具有良好的可跟踪性能;增益模糊滑模变结构控制具有良好的动态响应特性及控制精度,可有效地消除转向偏差,实现线控液压转向系统的同步转向。     

Automatic path-tracking controller of a four-wheel steering vehicle

The present paper proposes an automatic path-tracking controller of a four-wheel steering (4WS) vehicle based on the sliding mode control theory. The controller has an advantage in that the front- and rear-wheel steering can be decoupled at the front and rear control points, which are defined as centres of percussion with respect to the rear and front wheels, respectively. Numerical simulations using a 27-degree-of-freedom vehicle model demonstrated the following characteristics: (1) the automatic 4WS controller has a more stable and more precise path-tracking capability than the 2WS controller, and (2) the automatic 4WS controller has robust stability against system uncertainties such as cornering power perturbation, path radius fluctuation, and cross-wind disturbance.     

Advanced Steering System Adaptable to Lateral Control Task and Driver's Intention

This paper proposes an advanced steering system that adaptively varies the static gain and dynamics of the steering system. The steering system gain is adjusted, depending on whether the driver is in an aggressive or leisurely driving mood. The steering system dynamics is so designed that the command mode of the steering system will be either a rate-command or an attitude-command according to the lateral control task performed by the driver. The recognition system for lateral control tasks, a lane-following or lane-change task is proposed. The findings of simulator tests indicate proposed advanced steering system would remarkably improve the vehicle handling qualities.     

独立轮电驱动车辆主动操纵稳定控制研究

提出了采用变增益参考模型的滑模跟踪控制策略,以横摆角速度和侧滑速度为控制对象,独立控制左右轮驱动力产生直接横摆力矩,提高了车辆在极限工况下的操纵稳定性,并改善了车辆固有的转向特性。改进的滑模控制算法减小了系统抖振并具有较强的鲁棒性。     

Advanced Steering System Adaptable to Lateral Control Task and Driver's Intention

This paper proposes an advanced steering system that adaptively varies the static gain and dynamics of the steering system. The steering system gain is adjusted, depending on whether the driver is in an aggressive or leisurely driving mood. The steering system dynamics is so designed that the command mode of the steering system will be either a rate-command or an attitude-command according to the lateral control task performed by the driver. The recognition system for lateral control tasks, a lane-following or lane-change task is proposed. The findings of simulator tests indicate proposed advanced steering system would remarkably improve the vehicle handling qualities.     

Rollover prevention for heavy trucks using frequency shaped sliding mode control

Control and handling of heavy commercial vehicles carrying liquid cargo are influenced by liquid movement within the partially filled tank. During steering and braking maneuvering tasks, the truck may exhibit unstable behavior at lateral acceleration levels of 0.3 g to 0.4 g [m/s²]. The fluid slosh forces and dynamic load transfers in the lateral and longitudinal directions and parametric uncertainties caused by moving liquid cargo affect the overall dynamics of the vehicle. To solve a physical problem about the minimal excitation of the slosh dynamics associated with the longitudinal and lateral excitation of the vehicle, dynamic sliding surface design combined with recursive backstepping algorithm is introduced. Compensator dynamics are introduced in the sliding mode through a class of switching surfaces which has the interpretation of linear operators such that the resulting closed-loop system retains the insensitivity to uncertainties in the sliding mode while minimizing the excitation of flexible modes and unmodeled dynamics. The frequency shaped backstepping sliding mode algorithm, proposed by Acarman and Özgüner [Frequency shaping compensation for backstepping sliding mode control. Paper presented at the 15th IFAC World Congress, Barcelona, Spain, 2002], is designed to stabilize and to attenuate the sloshing effects of moving cargo by properly choosing the crossover frequencies of the dynamic compensators in accordance with the fundamental frequencies of the slosh dynamics.     

基于功能安全的分布式驱动电动汽车前轮失效补偿控制

分布式驱动电动汽车可以实现四轮转矩分配和差动转向,提升整车的动力学控制性能和经济性,但是四轮转矩独立可控的特点也对功能安全提出挑战。当前轮单侧电机出现执行器故障失效情况时,不仅会产生附加横摆力矩降低车辆安全性,差动转向功能的存在还会使车辆严重偏航。基于此,在设计分布式驱动-线控转向一体化底盘的基础上,基于功能安全提出一种分布式驱动电动汽车前轮失效补偿控制策略。首先建立分布式驱动失效动力学模型,分析前轮失效对车辆状态的影响机理,发现单一的驱动转矩截断控制无法满足车辆状态修正需求;其次设计一套备用的线控转向结构,通过变截距滑模控制算法提高切换状态下线控转向系统的转角跟踪性能,并用台架试验验证跟踪的准确性;然后设计自适应失效诊断观测器实时诊断驱动系统的电机故障,在将对应轮进行驱动转矩截断后,通过模型预测控制算法对车轮转矩重新分配实现纵向和侧向的状态跟踪;最后通过仿真和实车试验验证所提失效补偿控制策略的有效性和可用性。研究结果表明：分布式驱动电动汽车前轮单侧电机失效后,备用的线控转向系统能及时矫正前轮转角,所提出的失效补偿控制策略能够快速恢复车辆的稳定性和路径跟踪能力。     

A novel integrated chassis controller for full drive-by-wire vehicles

In this paper, a systematic design with multiple hierarchical layers is adopted in the integrated chassis controller for full drive-by-wire vehicles. A reference model and the optimal preview acceleration driver model are utilised in the driver control layer to describe and realise the driver's anticipation of the vehicle's handling characteristics, respectively. Both the sliding mode control and terminal sliding mode control techniques are employed in the vehicle motion control (MC) layer to determine the MC efforts such that better tracking performance can be attained. In the tyre force allocation layer, a polygonal simplification method is proposed to deal with the constraints of the tyre adhesive limits efficiently and effectively, whereby the load transfer due to both roll and pitch is also taken into account which directly affects the constraints. By calculating the motor torque and steering angle of each wheel in the executive layer, the total workload of four wheels is minimised during normal driving, whereas the MC efforts are maximised in extreme handling conditions. The proposed controller is validated through simulation to improve vehicle stability and handling performance in both open- and closed-loop manoeuvres.     

Robust control for four-wheel-independent-steering electric vehicle with steer-by-wire system

A four-wheel-independent-steering (4WIS) electric vehicle (EV) with steer-by-wire (SBW) system is proposed in this paper. The fast terminal sliding mode controller (FTSMC) is designed for the SBW system to suppress external disturbances. Taking unstructured and structured uncertainties into consideration, a robust controller is designed for the 4WIS EV utilizing μ synthesis approach and the controller order reduction is implemented based on Hankel-Norm approximation. Since sideslip angle is the feedback signal of robust controller and it is hard to measure, the extended Kalman filter (EKF) is employed to estimate sideslip angle. To evaluate the vehicle performance with the designed control system, step and sinusoidal steering maneuvers are simulated and analyzed. Simulation results show that the designed control system have good tracking ability, strong robust stability and good robust performance to improve vehicle stability and handing performance.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

An adaptive fuzzy-sliding lateral control strategy of automated vehicles based on vision navigation

Lateral control is considered to be one of the toughest challenges in the development of automated vehicles due to their features of nonlinearities, parametric uncertainties and external disturbances. In order to overcome these difficulties, an adaptive fuzzy-sliding mode control strategy used for lateral control of vision-based automated vehicles is proposed in this paper. First, a vision algorithm is designed to provide accurate location information of vehicle relative to reference path. Then, an adaptive fuzzy-sliding mode lateral controller is proposed to counteract parametric uncertainties and strong nonlinearities, and the asymptotic stability of the closed-loop lateral control system is proven by the Lyapunov theory. Finally, experimental results indicate that the proposed algorithm can achieve favourable tracking performance, and it has strong robustness.     

Coordinated control strategies for active steering,differential braking and active suspension for vehicle stability,handling and safety improvement

ABSTRACT

In this paper, a coordinated control strategy is proposed to provide an effective improvement in handling stability of the vehicle, safety, and comfortable ride for passengers. This control strategy is based on the coordination among active steering, differential braking, and active suspension systems. Two families of controllers are used for this purpose, which are the high order sliding mode and the backstepping controllers. The control strategy was tested on a full nonlinear vehicle model in the environment of MATLAB/Simulink. Rollover avoidance and yaw stability control constraints have been considered. The control system mainly focuses on yaw stability control. When rollover risk is detected, the proposed strategy controls the roll dynamics to decrease rollover propensity. Simulation results for two different critical driving scenarios, the first one is a double lane change and the other one is a J-turn manoeuvre, show the effectiveness of the coordination strategy in stabilising the vehicle, enhancing handling and reducing rollover propensity.     

Vehicle handling dynamics modelling by a data-driven identification method

Modelling of vehicle handling dynamics has received a renewed attention in recent years. Different from traditional vehicle modelling, a novel data-driven identification method for vehicle handling dynamics is proposed, which can avoid the problems of the under-modelling and parameter uncertainties in the first-principle modelling process. By first-order Taylor expansion, the nonlinear vehicle system can be linearised as a slowly linear time-varying system with fourth-order. In order to identify the derived identifiable model structure, a recursive subspace method is presented. Derived by optimal version of predictor-based subspace identification (PBSID_opt) and projection approximation subspace tracking (PAST), the identification method is numerical stability and gives an unbiased estimation for the closed-loop system. Based on standard road tests, the proposed modelling method is proven effective and the obtained model has good predictive ability. Additionally, it is noted that the model obtained from the initial phase of straight driving is just a mathematical model to describe the relationship between input and output. And when the vehicle is steering, the model can converge to a stable phase quickly and represent vehicle dynamic performance.     

Second-order sliding mode controller with model reference adaptation for automatic train operation

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.     

线控转向稳态增益与动态反馈校正控制算法

以29自由度汽车动力学模型为基础,提出了保证线控汽车转向增益不变的稳态控制策略,使线控汽车转向特性不随车速和转向盘转角变化;提出了基于状态反馈的动态校正稳定性控制算法。仿真和驾驶模拟器实验表明,基于转向增益不变的稳态控制策略保证了汽车转向特性不变,减轻了驾驶员的负担,适合于更多的驾驶人群;基于状态反馈的动态校正稳定性控制算法有效提高了汽车的稳定性。     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).