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.     

Sliding-mode control for the roll-angle tracking of an unmanned bicycle

This study investigates the roll-angle tracking control of an unmanned bicycle using a sliding-mode controller (SMC). The roll angle is controlled at a specific speed via a simple proportional, derivative (PD) controller to generate input–output data including steering torque as well as roll and steering angles. The collected data are then used to identify a one-input two-output linear model by a prediction-error identification method using parameterisation in a canonical state-space form derived as a Whipple model. Once the linear model is obtained, the SMC can be designed to control the bicycle. Simulations and comparisons with a proportional, integral, derivative (PID) controller show that this SMC is robust against changes and variations in speed as well as external disturbances.     

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。     

基于变传动比的全轮线控转向车辆可拓H∞控制方法研究

为了解决传统固定转向传动比以及鲁棒H_∞控制方法无法很好地改善车辆稳定性的问题,提出全轮线控转向车辆的变传动比和可拓H_∞控制策略。首先,建立八自由度车辆动力学模型和轮胎模型。其次,以车辆方向盘转角和车速为输入信息,基于模糊控制方法设计全轮线控转向车辆的转向传动比,并计算出全轮线控转向车辆的前轮转角。然后,以横摆角速度偏差和偏差微分为特征值,基于可拓控制理论将车辆状态划分为3个区域：经典域、可拓域和非域;在经典域中,采用基于横摆角速度反馈的鲁棒H_∞控制方法,实时获取全轮线控转向车辆的后轮转角;在可拓域和非域中,结合可拓控制和H_∞控制策略,动态调整H_∞控制器的输出信号,在保证控制系统鲁棒性的前提下改善车辆的操纵稳定性。最后,基于MATLAB/Simulink仿真平台和自主研制的全轮线控转向特种消防救援车辆,通过正弦转向、单移线、阶跃转向、双移线等典型工况对所提控制方法进行验证,并以平均绝对误差和均方根误差为评价指标,与无控制和H_∞控制方法进行对比分析。仿真和试验测试结果表明：①变传动比控制方法不仅可以提高车辆低速时的转向灵敏度,也能改善车辆高速时的稳定性;②相比传统鲁棒H_∞控制,可拓H_∞控制策略提高了全轮线控转向车辆的操纵稳定性,改善了车辆全轮线控转向控制系统的鲁棒性。     

极限工况下主动前轮转向汽车稳定性控制

轮胎对汽车稳定性有重要影响,研究和利用轮胎的非线性特性有助于扩展汽车的稳定域。本文基于非线性轮胎模型,提出一种改进型线性时变模型预测控制(LTV-MPC)方法。该方法能扩展主动前轮转向汽车的稳定范围,提高极限工况下主动前轮转向汽车的稳定性。仿真结果表明,该方法比传统的LTV-MPC方法具有更好的稳定性控制效果。     

智能汽车自动紧急转向避撞的跟踪控制方法对比研究

为了提高智能汽车的主动安全性,提出3种不同的自动紧急转向避撞跟踪控制方法。首先建立汽车避撞简化模型,对制动、转向及两者相结合的3种不同避撞方式进行对比分析。其次,为深入研究汽车避撞过程中的实际响应,建立包含转向、制动及悬架3个子系统耦合特性的底盘18自由度统一动力学模型,并进行相关试验验证。随后构建智能汽车自动紧急转向避撞控制框架,对五次多项式参考路径和七次多项式参考路径的横摆角速度和横摆角加速度进行对比分析。接着以线性2自由度转向动力学模型为参考对象,对最优控制四轮转向、最优控制前轮转向、前馈与反馈控制相结合的前轮转向3种不同的跟踪控制系统分别进行设计。最后,以汽车底盘18自由度统一动力学模型为研究对象,对上述3种避撞控制系统进行仿真试验对比分析。研究结果表明：与制动避撞相比而言,转向避撞所需的纵向距离有较大降低,随着车速的增加和路面附着系数的越低,效果越明显;七次多项式参考路径比五次多项式参考路径的避撞过渡过程更为平缓,当实际车速与控制器所用车速不一致时,前者避撞性能表现更优;最优四轮转向控制系统在高、低2种不同附着路面都具有较好的避撞效果,最优前轮转向控制系统次之,而前馈与反馈相结合的前轮转向控制系统在低附着路面上则表现出严重的失稳。     

6×6无人地面车辆差速转向分析与优化

差速转向越来越多的被应用于无人地面车辆，介绍了差速转向相比于传统转向轮转向的一些优势，并对差速转向进行了简单的运动学分析。差速转向消耗的功率大，提出通过调整悬架装置改善转向效率，并对车辆悬架调整前后的模型进行静力学分析。     

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.     

车道线保持自校正滑模控制

为实现复杂工况下的车道线保持控制,建立了包含转向机构动态的车辆横向动力学模型,在此基础上研究了车辆在直道与弯道工况下的车道保持控制问题并提出一种自校正滑模控制方法.该方法引入sigmoid函数代替滑模控制中的符号函数并根据Lyapunov稳定性理论设计了自校正律,在自校正律的作用下sigmoid函数的边界层厚度以及切换...     

汽车转向控制

本文研究侧偏角有约束条件下，汽车四轮转向控制系统的设计问题。根据汽车转向动力学的特点，建立了具有不确定的汽车转向模型，给出了车体质心处侧偏角有约束条件下，二自由度鲁棒四轮转向控制器的设计方法，最后基于ＬＭＩＴｏｏｌ给出了控制器的迭代算法，并给出了仿真计算实例。     

Robust control for 4WS vehicles considering a varying tire-road friction coefficient

A µ-synthesis for four-wheel steering (4WS) problems is proposed. Applying this method, model uncertainties can be taken into consideration, and a µ-synthesis robust controller is designed with optimized weighting functions to attenuate the external disturbances. In addition, an optimal controller is designed using the well-known optimal control theory. Two different versions of control laws are considered here. In evaluations of vehicle performance with the robust controller, the proposed controller performs adequately with different maneuvers (i.e., J-turn and Fishhook) and on different road conditions (i.e., icy, wet, and dry). The numerical simulation shows that the designed µ-synthesis robust controller can improve the performance of a closed-loop 4WS vehicle, and this controller has good maneuverability, sufficiently robust stability, and good performance robustness against serious disturbances.     

Handling stability improvement through robust active front steering and active differential control

The design of the integrated active front steering and active differential control for handling improvement of road vehicles is undertaken. The controller design algorithm is based on the solution of a set of linear matrix inequalities that guarantee robustness against a number of vehicle parameters such as speed, cornering and braking stiffnesses. Vehicle plane dynamics are first expressed in the generic linear parameter-varying form, where the above-stated parameters are treated as interval uncertainties. Then, static-state feedback controllers ensuring robust performance against changing road conditions are designed. In a first series of simulations, the performance of the integrated controller is evaluated for a fishhook manoeuvre for different values of road adhesion coefficient. Then, the controller is tested for an emergency braking manoeuvre executed on a split-μ road. In all cases, it is shown that static-state feedback controllers designed by the proposed method can achieve remarkable road handling performance compared with uncontrolled vehicles.     

一种减轻装有EPS汽车转向扭矩的控制策略

本文提出了一种新的电动助力转向系统的控制策略,以减小车辆静止时改变方向所需的转向力。以前尝试通过减少不良的转向振动来减少转向扭矩失败的原因是因为高辅助增益往往会产生震荡或增加噪声敏感性。为了消除此种振动,开发出一种基于控制齿轮角速度的控制策略,它是在简化的转向模型的基础上开发出来的。这个实验获得了很好的齿轮角速度的估计值,这样就有可能消除方向盘所有旋转速度下的振动。实验证明在方向盘大转速变换下,转向扭矩显著降低,无振动传输给司机。所提出的控制策略使用一个辅助来获得超过原来的三倍以上的增益。此外,所提出的控制策略不需要补充传感器。     

基于变权重系数的分布式驱动无人车轨迹跟踪

为了提高分布式无人车轨迹跟踪的精度，提出了基于自主与差动协调转向控制的轨迹跟踪方法。首先，在车辆三自由度模型基础上，基于模型预测控制（MPC）实时计算前轮转角以控制车辆进行自主转向轨迹跟踪。在此过程中，为了提高自主转向下车辆的轨迹跟踪精度与行驶的稳定性，考虑多种因素，利用经验公式及神经网络控制对MPC的预瞄步数和预瞄步长进行多参数调整，实现预瞄时间的自适应控制。其次，在恒转矩需求的情况下，以轨迹偏差为PID控制器的输入及左右轮毂电机转矩为输出进行差动转向控制，实现了差动转向下的轨迹跟踪控制。然后，通过设置权重系数的方法将自主与差动转向相结合。考虑到车辆横纵向动力学因素，采用模糊控制及经验公式对权重系数进行了调整，从而在提高车辆转向灵活性与轨迹跟踪效果的同时保证车辆行驶的稳定性。CarSim与Simulink联合仿真以及实车试验结果表明：与自主转向轨迹跟踪相比，采用变权重系数的协调控制可以在不同的工况下提高车辆的转向灵活性与轨迹跟踪的精度，轨迹跟踪偏差的均方根值改善率达到了11%。所提出的协调转向控制方法可为分布式驱动车辆转向灵活性的提高及轨迹跟踪精度的改善提供一种新的思路。     

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.     

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.     

智能车辆转向变结构控制方法的研究

从车辆的转向动力学和预瞄运动学特性出发，结合转向系统的系统辨识，建立了车辆转向系统的线性模型。运用变结构滑模控制理论和多模型切换，使车辆转向控制具有良好的跟踪性能和鲁棒性。     

无人驾驶汽车路径跟踪控制方法拟人程度研究

无人驾驶汽车路径跟踪控制是无人驾驶汽车运动控制的核心所在,目前常用的路径跟踪模型主要以路径跟踪精度为主要控制目标,在很大程度上忽略了无人驾驶汽车的乘坐舒适性和控制的拟人程度。为了研究无人驾驶汽车路径跟踪控制算法的拟人程度并提高乘坐舒适性,基于转向几何学、汽车运动学和汽车动力学理论建立实车中常用的4种路径跟踪模型,提出以路径跟踪过程中的最大横向加速度a_ymax和方向盘转角平方和δ_w²共同表征路径跟踪模型的拟人程度和横向乘坐舒适性。基于驾驶人实车换道试验数据,建立多项式拟人换道参考路径,搭建CarSim/Simulink联合仿真模型,并对其进行不同车速下的车辆换道试验。研究结果表明：路径跟踪模型的横向循迹偏差均会随着车速的提高而增加,但都能较好实现路径跟踪;带预瞄路径跟踪模型和动力学前馈最优LQR路径跟踪模型拟人程度较好;汽车运动学路径跟踪模型的乘坐舒适性最差,方向盘修正激烈;在100 km·h^-1,a_ymax>0.7 m·s^-2,δ_w²>2.7×10³时,拟人程度最差;不带预瞄路径跟踪模型循迹精度最高,且拟人程度最高,乘坐舒适性最好,120 km·h^-1时,a_ymax ≤ 0.5 m·s^-2。     

基于微分几何的四轮独立驱动车辆运动解耦控制研究

针对车辆在纵向运动和横摆运动时的强耦合关系给车辆动力学控制带来的困难，以四轮独立电驱动车辆作为研究对象，基于微分几何理论设计了车辆系统运动解耦控制方法，将非线性强耦合的四轮驱动车辆动力学系统解耦为纵向和横向两个相对独立运动控制子系统，并设计了鲁棒控制器，以提高抵抗车辆行驶时不确定外力如侧风的干扰能力。基于 Trucksim 软件建立四轮驱动车辆模型，并针对车辆解耦控制策略和抗干扰策略进行了仿真测试。结果表明，相比于无解耦控制的车辆，采用微分几何解耦控制的四轮独立驱动车辆纵向速度偏差降低了 82.1%，横摆角速度偏差降低了80.7%，且微风干扰下的抗干扰能力明显改善，车辆稳定性显著提升。为验证该运动解耦控制策略在实时系统中的控制效果，还进行了硬件在环试验，结果表明，硬件在环试验的结果与仿真结果一致。