基于非线性扰动估计的客车防侧翻控制

针对客车防侧翻控制中,实际车辆系统建模容易受到各种未知非线性扰动及参数摄动,难以建立精确的车辆模型,标准滑模控制(sliding mode control, SMC)存在较大抖振等问题,本文中提出径向基神经网络自适应滑模控制(radial basis function-adaptive sliding mode control, RBF-ADSMC)算法。首先,利用RBF神经网络控制器对车辆建模过程中的各种未知扰动项及参数摄动项进行估计;然后,利用RBF神经网络对标准SMC的关键参数进行自适应调节;最后,搭建电控气压硬件在环试验台,对控制算法进行硬件在环试验验证。试验结果表明,RBF-ADSMC算法控制效果良好,能够满足客车防侧翻控制需求。RBF-ADSMC算法与SMC算法相比较,能够减小客车的侧倾角和侧向加速度,提高客车的防侧翻控制效果。     

基于非线性扰动观测的商用车ESC自适应滑模控制研究

针对商用车ESC控制中,实际车辆存在各种扰动,难以建立精确的车辆模型,传统滑模控制存在较大抖振等问题,本文中提出基于非线性扰动观测(NDOB)的自适应滑模控制(ADSMC)算法。首先,利用非线性扰动观测器对车辆建模的扰动项进行估计;然后,采用径向基神经网络对滑模控制器的关键参数进行自适应调节,以简化参数调节过程、减小滑模抖振、提高控制精度;最后,在TruckSim中建立车辆模型,在MATLAB中建立控制策略模型,在电控气压硬件在环试验台上,对控制算法进行试验验证。试验结果表明,NDOB-ADSMC算法的ESC控制效果良好,能够满足车辆ESC控制需求。     

汽车稳定性控制系统的研究与仿真

在线性二自由度车辆模型基础上,采用直接横摆力矩控制方法,选取质心侧偏角和横摆角速度作为稳定性控制系统的主控变量,设计了三种具有针对性的基于滑模变结构理论的车辆操纵稳定性控制策略——质心侧偏角、横摆角速度和两者联合的滑模变结构控制。在Matlab,Simulink平台上,对三种汽车稳定性控制策略的具体应用进行仿真分析,验证了所设计稳定性控制算法的有效性和鲁棒性。     

车辆横向稳定性自适应神经网络控制策略研究

设计了一种"前馈+反馈"自适应神经网络控制器,通过直接横摆力矩和前轮主动转向的复合控制来提高车辆横向稳定性。反馈控制器采用PD控制策略,以实际横摆角速度与目标横摆角速度的偏差为输入量;前馈控制器采用RBF神经网络,以反馈控制器的输出为误差进行学习,而实现自适应控制。仿真结果表明,采用上述复合控制,能有效跟踪目标横摆角速度并降低质心侧偏角,提高了车辆在高速急转向时的稳定性。     

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。     

基于IEHB系统的车辆稳定性控制研究

以某小型乘用车为研究对象,为提高线控制动车辆的转向稳定性,通过扩展卡尔曼滤波进行质心侧偏角的估计,以质心侧偏角和横摆角速度为控制变量,设计模糊滑模联合控制器得到附加横摆力矩,以单轮差动制动方式施加到被控车轮上。利用CarSim与Simulink联合仿真平台,基于IEHB系统及控制系统的集成模型在双移线工况下进行了仿真实验。结果表明所设计的IEHB系统压力控制器能够较好地实现压力跟踪,并能验证所提出的车辆稳定性控制策略的有效性与合理性。     

融合预瞄特性的智能电动汽车稳定性模型预测控制研究

提出了一种融合预瞄特性的智能电动汽车稳定性前馈+反馈控制方法。建立车辆预瞄模型，通过汽车在环境感知时的前视行为，引入道路曲率作为车辆动力学特性的影响因素。基于在前视信息指导下的车辆位姿变化，根据道路附着能力和车速指数模型描述期望纵向车速，建立轮胎侧偏刚度补偿的稳定性前馈控制方法。同时，采用模型预测控制（MPC）设计稳定性反馈控制律，根据车辆的预瞄信息自适应调整预测模型参数和预测时间，消除前馈控制误差及路面扰动等不确定性因素带来的影响。研究结果表明，本文提出的控制策略下汽车质心侧偏角、横摆角速度和侧向加速度小，且跟踪精度更高。仿真试验中，相比于无控制、MPC反馈控制与前馈+定参数MPC反馈控制，本文提出的控制策略在双移线工况1下质心侧偏角峰值分别减小了41.3%、28.9%和10.0%，横摆角速度峰值分别减小了18.0%、6.7%和2.0%，双移线工况2下质心侧偏角峰值分别减小了27.2%、8.7%和8.0%，横摆角速度峰值分别减小了16.9%、12.9%和8.6%；相比于MPC反馈控制与前馈+定参数MPC反馈控制，在蛇行工况1下，质心侧偏角峰值分别减小了49.8%与34.8%，横摆角速...     

基于联合滑模变结构的电动轮汽车DYC系统研究

设计了基于横摆角速度与质心侧偏角的联合滑模变结构控制策略,基于Car Sim和MATLAB软件建立了电动轮汽车整车模型和整车控制模型,对电动轮汽车的驱动DYC系统进行了仿真分析。结果表明,设计的联合滑模变结构控制器具有良好的鲁棒性,能较好地控制车辆的横摆角速度和质心侧偏角;所采用的轴载比例分配算法对车辆的纵向加速度影响较小,既实现了车辆横向稳定性的控制,同时提高了车辆的舒适性。     

考虑侧倾影响的汽车横摆角速度与质心侧偏角滤波估计

为准确识别汽车前方弯道路段曲率信息,考虑侧倾运动的实际影响,建立了汽车质心运动、横摆运动及侧倾运动具有非线性特征的3自由度车辆操纵稳定性模型,设计了汽车质心侧偏角与横摆角速度扩展卡尔曼滤波估计器,实现了巡航车辆运动特征的在线实时估计。采用双移线输入,通过Car Sim与Matlab/Simulink的联合仿真进行验证,结果表明,即使在大噪声条件下,所设计的扩展卡尔曼滤波估计器也能较好地实现车辆横摆角速度与质心侧偏角的准确估计。     

商用车电液耦合转向系统主动回正控制研究

针对装有传统液压助力转向系统的商用车在回正过程中存在低速回正不足或高速回正过度的问题,综合考虑载荷转移、路面条件和轮胎非线性等对回正工况的影响,基于电液耦合转向系统,设计一种车辆质心侧偏角和横摆角速度联合控制的非线性滑模控制器。针对控制算法部分状态量难以获取和影响车辆回正稳定性的路面附着系数难以直接测量的问题,利用UKF观测器为滑模控制器动态估计车辆状态信息和路面附着系数,并将质心侧偏角的观测值和横摆角速度与其期望值之差作为控制系统输入,来求取回正控制所需的转角修正量。最后通过TruckSim、Matlab/Simulink和转向试验台架对不同工况下的转向回正性能进行仿真和台架试验,结果表明,所提出的主动回正控制策略可有效提高转向盘回正的稳定性和控制精准性。     

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.     

基于滑模自抗扰的电制动系统动态负载模拟

为精准模拟传动系弹性及齿隙作用下电制动系统非线性机械负载,提出了自适应模糊滑模自抗扰的测功机控制算法。首先,针对一款前驱电动汽车,建立融合感应电机模型的车辆及台架机电一体化模型,引入典型正常制动和防抱死制动控制作为测试对象。其次,构建扩张状态观测器估计台架系统未建模动态,以自适应模糊滑模控制测功机实时模拟高度非线性机械负载。最后,开展了制动控制策略台架测试的仿真研究。结果表明:提出的方法可精确模拟电制动系统动态负载,有效提高制动控制算法台架测试精度。     

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。     

基于三自由度的智能汽车模糊滑模横向运动控制研究

针对智能汽车运动过程中存在的车身姿态变化问题以及运动控制精度问题，设计了一种基于非线性3自由度动力学模型的模糊滑模横向运动控制器。建立了包括侧倾运动的3自由度动力学模型，进行了模型线性化；对基于线性化处理后的动力学模型进行了滑模控制器设计，通过控制前轮转角实现了路径跟踪横向控制，并引入了模糊控制提高控制效果，本控制系统能够在跟踪过程中对车身姿态变化进行观察。仿真结果表明，搭建的基于3自由度动力学模型的模糊滑模控制器能够在考虑侧倾运动的基础上，实现路径跟踪，且构建的模糊滑模控制系统相较于传统滑模控制其横向偏差与方向偏差分别降低了7.28%和1.50%，同时模糊控制也减弱了滑模控制固有的抖振影响。     

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.     

A novel direct yaw moment controller for in-wheel motor electric vehicles

A novel direct yaw moment controller is developed in this paper. A hierarchical control architecture is adopted in the controller design. In the upper controller, a driver model and a vehicle model are used to obtain the driver's intention and the vehicle states, respectively. The upper controller determines the desired yaw moment by means of sliding mode control. The lower controller distributes differential longitudinal forces according to the desired yaw moment. A nonlinear tyre model, ‘UniTire’, is utilised to develop the novel distribution strategy and the control boundary.     

An alternative approach to automotive ESC based on measured wheel forces

Traditional electronic stability control (ESC) systems act on one or more wheels on the basis of a logic aiming at the control of variables that cannot be directly measured (vehicle sideslip angle and the tyre slip). Hence, a vehicle state estimator capable of evaluating the needed variables from the data of the input sensors is necessary. In the present paper, the authors discuss a different approach to the estimation problem, assuming that the forces acting on the wheels can be directly measured. The ESC feed-forward control logic is designed through a vehicle frequency response analysis in order to obtain a faster active system activation. The variable controlled by the logic is the tyre longitudinal force. Experimental results obtained on an ESC hardware-in-the-loop test bench prove the validity of the approach, showing enhanced dynamic performances, together with the limits due to the delays in the actuation of the ESC motor pump, which needs some time to build the pressure requested for the intervention on the selected callipers. Finally, the tests demonstrate the opportunity of closing the control loop on a variable (i.e. the force) that can be directly measured.     

Lateral dynamics emulation via a four-wheel steering vehicle

In this paper, we examine the lateral dynamics emulation capabilities of an automotive vehicle equipped with four-wheel steering. We first demonstrate that the lateral dynamics of a wide range of vehicles can be emulated, either with little or with no modification on the test vehicle. Then we discuss a sliding mode controller for active front and rear wheel steering, in order to track some given yaw rate and side-slip angle. Analytically, it is shown that the proposed controller is robust to plant parameter variations by±10%, and is invariant to unmeasurable wind disturbance. The performance of the sliding mode controller is evaluated via computer simulations to verify its robustness to vehicle parameter variations and delay in the loop, and its insensitivity to wind disturbance. Finally, the emulation of a bus, a van, and two commercially available passenger vehicles is demonstrated in an advanced nonlinear simulator.     

Disturbance Observer-Based Sideslip Angle Control for Improving Cornering Characteristics of In-Wheel Motor Electric Vehicles

In this paper, a robust sideslip angle controller based on the direct yaw moment control (DYC) is proposed for in-wheel motor electric vehicles. Many studies have demonstrated that the DYC is one of the effective methods to improve vehicle maneuverability and stability. Previous approaches to achieve the DYC used differential braking and active steering system. Not only that, the conventional control systems were commonly dependent on the feedback of the yaw rate. In contrast to the traditional control schemes, however, this paper proposes a novel approach based on sideslip angle feedback without controlling the yaw rate. This is mainly because if the vehicle sideslip angle is controlled properly, the intended sideslip angle helps the vehicle to pass through the corner even at high speed. On the other hand, the vehicle may become unstable because of the too large sideslip caused by unexpected yaw disturbances and model uncertainties of time-varying parameters. From this aspect, disturbance observer (DOB) is employed to assure robust performance of the controller. The proposed controller was realized in CarSim model described actual electric vehicle and verified through computer simulations.     

Nonlinear adaptive sliding mode control for vehicle handling improvement via steer-by-wire

This paper proposes a nonlinear adaptive sliding mode control that aims to improve vehicle handling through a Steer-By-Wire system. The designed sliding mode control, which is insensitive to system uncertainties, offers an adaptive sliding gain to eliminate the precise determination of the bound of uncertainties. The sliding gain value is calculated using a simple adaptation algorithm that does not require extensive computational load. Achieving the improved handling characteristics requires both accurate state estimation and well-controlled steering inputs from the Steer-By-Wire system. A second order sliding mode observer provides accurate estimation of lateral and longitudinal velocities while the driver steering angle and yaw rate are available from the automotive sensors. A complete stability analysis based on Lyapunov theory has been presented to guarantee closed loop stability. The simulation results confirmed that the proposed adaptive robust controller not only improves vehicle handling performance but also reduces the chattering problem in the presence of uncertainties in tire cornering stiffness.