Estimation of road frictional force and wheel slip for effective antilock braking system (ABS) control

The introduction of electric braking via brake‐by‐wire systems in electric vehicles) has reduced the high transportation delays usually involved in conventional friction braking systems. This has facilitated the design of more efficient and advanced control schemes for antilock braking systems (ABSs). However, accurate estimation of the tire‐road friction coefficient, which cannot be measured directly, is required. This paper presents a review of existing estimation methods, focusing on sliding‐mode techniques, followed by the development of a novel friction estimation technique, which is used to design an efficient ABS control system. This is a novel slip‐based estimation method, which accommodates the coupling between the vehicle dynamics, wheel dynamics, and suspension dynamics in a cascaded structure. A higher‐order sliding‐mode observer–based scheme is designed, considering the nonlinear relationship between friction and slip. A first‐order sliding‐mode observer is also designed based on a purely linear relationship. A key feature of the proposed estimation schemes is the inclusion of road slope and the effective radius of the tire as an estimated state. These parameters impact significantly on the accuracy of slip and friction estimation. The performance of the proposed estimation schemes are validated and benchmarked against a Kalman filter (KF) by a series of simulation tests. It is demonstrated that the sliding‐mode observer paradigm is an important tool in developing the next generation ABS systems for electric vehicles.     

汽车转向/防抱死制动系统的非线性鲁棒协调控制

针对汽车转向系统和防抱死制动系统的协调控制问题,提出一种新的非线性鲁棒协调控制系统.该控制结构由转向控制器和制动控制器组成.为了改善整个系统的鲁棒性和协调性,根据汽车转向和制动非线性综合模型,基于Hamilton函数方法设计了汽车非线性鲁棒协调控制器.该控制器通过预置状态反馈完成系统的耗散Hamilton函数实现.设计了适用于复杂工况的制动力分配策略.仿真结果验证了所设计控制算法的稳定性和有效性.     

防抱制动系统滑模状态观测和控制系统仿真

该文在考虑不平路面随机激励作用下车辆垂向振动的基础上 ,首先建立了四分之一车辆制动模型 ,而后充分运用滑移模式变结构的分析和设计方法 ,提出了车轮最佳滑移率的滑模实时在线辨识滑模优化算法 ,在对系统可观测性论证的基础上 ,设计了非线性滑模状态观测器 ,给出了单通道防抱制动系统基于滑移率的滑模控制算法 ,通过计算机仿真 ,验证了该控制算法的可行性和有效性 ,为设计具有高鲁棒性的防抱制动系统做了一定的理论探索和仿真工作     

Nonlinear vehicle side-slip estimation with friction adaptation

A nonlinear observer for estimation of the longitudinal velocity, lateral velocity, and yaw rate of a vehicle, designed for the purpose of vehicle side-slip estimation, is modified and extended in order to work for different road surface conditions. The observer relies on a road-tire friction model and is therefore sensitive to changes in the adhesion characteristics of the road surface. The friction model is parametrized with a single friction parameter, and an update law is designed. The adaptive observer is proven to be uniformly globally asymptotically stable and uniformly locally exponentially stable under a persistency-of-excitation condition and a set of technical assumptions, using results related to Matrosov's theorem. The observer is tested on recorded data from two test vehicles and shows good results on a range of road surfaces.     

含有摩擦补偿的全方位移动机器人自抗扰控制

本文针对全方位移动机器人轨迹追踪中的摩擦补偿问题,提出了一种改进的非线性自抗扰控制器.首先建立了含有经典静态摩擦模型的全方位移动机器人动力学模型.其次,基于该模型设计非线性控制器和线性扩张状态观测器并给出了系统的稳定性分析.通过将模型已知项加入线性扩张状态观测器中得到摩擦力的估计值,并将估计值用于非线性控制器中摩擦补偿部分.为减小摩擦力对机器人低速运动轨迹追踪控制的影响,非线性控制器采用变增益控制器进行轨迹追踪控制.最后通过仿真结果验证本文提出控制器的有效性.     

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

Vehicle velocity estimation using nonlinear observers

Nonlinear observers for estimation of lateral and longitudinal velocity of automotive vehicles are proposed. The observers are based on a sensor suite that is standard in many new cars, consisting of acceleration and yaw rate measurements in addition to wheel speed and steering angle measurements. Two approaches are considered: first, a modular approach where the estimated longitudinal velocity is used as input to the observer for lateral velocity, and second, a combined approach where all states are estimated in the same observer. Both approaches use a tire-road friction model, which is assumed to be known. It is also assumed that the road is flat. Stability of the observers is proven in the form of input-to-state stability of the observer error dynamics, under a structural assumption on the friction model. The assumption on the friction model is discussed in detail, and the observers are validated on experimental data from cars.     

电动汽车动力学控制研究进展

近年来随着全球资源、环境问题日益严峻,节能、环保的电动汽车得到快速发展。电动汽车采用电机驱动系统,具有转矩快速响应、易于精确测量、可实现动力分散控制、可实现制动能量回收等优点。充分挖掘并利用这些优点可显著提升车辆动力学控制性能。文中从电动汽车动力学控制运行参数的识别、动力学控制结构与方法两个角度综述了十多年来的研究成果,重点介绍了轮胎-路面接触条件识别方法、驱动防滑控制方法等。对车辆横向动力学控制,包括电子差速控制、直接横摆控制、底盘集成控制等研究现状也做了总结。最后对未来电动车辆动力学控制的发展方向作了几点展望。     

汽车转向/防抱死制动系统的无模型协同控制

汽车制动系统和转向系统相互之间存在着复杂的耦合关系,会对汽车行驶安全性和操纵稳定性造成极大的影响。为了动态补偿这种干扰影响,以无模型控制方法设计汽车整车防抱死制动控制器、整车前轮主动转向控制器及转向系统和制动系统的协同控制器,从理论上证明了设计的无模型控制系统的稳定性。最后,在MATLAB/Simulink平台上搭建了车辆模型和控制器,进行汽车转向制动控制的动态性能仿真。仿真结果表明其解决了汽车两个系统的耦合干扰,提高了汽车制动效能和转向稳定性。     

考虑非线性因素的飞机防滑刹车系统控制

飞机的刹车过程存在较强的非线性,目前广泛应用的速度差加压力偏调式(PBM)控制律难以实现对飞机刹车的高性能控制.本文提出了一种考虑飞机刹车过程中非线性因素的滑模控制律.首先建立考虑轮胎跑道非线性和刹车盘摩擦系数非线性的的飞机防滑刹车系统非线性模型,然后设计了滑模观测器对飞机速度进行估计,并在此基础上设计了一种滑模变结构控制律,最后基于模糊理论对滑模控制律进行优化,从而抑制控制器的抖振.仿真结果表明,基于模糊指数趋近律的滑模变结构控制律控制效果优于传统“PD+PBM”控制律,抑制控制器输出抖振效果良好,能够很好的适应刹车过程中的复杂非线性因素,刹车效率高,控制方法合理有效.     

基于Uni-Tire轮胎模型的车辆质心侧偏角估计

针对车辆质心侧偏角估计的准确性和实时性能问题,提出了车辆质心侧偏角估计的非线性全维观测器设计方法.首先基于车辆动力学模型及纵滑-侧偏联合工况下的Uni-Tire轮胎模型,利用车载传感器测量车辆状态;观测器利用这些状态估计出车辆的纵向速度、侧向速度及横摆角速度,并由此得到车辆的质心侧偏角估计.其次利用输入-状态稳定(input-to-state stability,ISS)理论对观测器的稳定性进行了分析.最后采用红旗CA7180A3E型轿车的车辆参数使用车辆仿真软件veDYNA对极限工况下的估计结果进行了离线仿真研究,并利用xPC-Target仿真环境和dSPACE实时仿真系统搭建仿真平台,对非线性全维观测器的实时性进行验证.仿真结果表明,非线性估计方法估计精度较高,实时性较好,可以满足工程应用的要求.     

A closed‐loop nonlinear control and sliding mode estimation strategy for fluid flow regulation

Novel sliding mode observer (SMO) and robust nonlinear control methods are presented, which are shown to achieve finite‐time state estimation and asymptotic regulation of a fluid flow system. To facilitate the design and analysis of the closed‐loop active flow control (AFC) system, proper orthogonal decomposition–based model order reduction is utilized to express the Navier‐Stokes partial differential equations as a set of nonlinear ordinary differential equations. The resulting reduced‐order model contains a measurement equation that is in a nonstandard mathematical form. This challenge is mitigated through the detailed design and analysis of an SMO. The observer is shown to achieve finite‐time estimation of the unmeasurable states of the reduced‐order model using direct sensor measurements of the flow field velocity. The estimated states are utilized as feedback measurements in a closed‐loop AFC system. To address the practical challenge of actuator bandwidth limitations, the control law is designed to be continuous. A rigorous Lyapunov‐based stability analysis is presented to prove that the closed‐loop flow estimation and control method achieves asymptotic regulation of a fluid flow field to a prescribed state. Numerical simulation results are also provided to demonstrate the performance of the proposed closed‐loop AFC system, comparing 2 different designs for the SMO.     

Coupled nonlinear vehicle control: Flatness-based setting with algebraic estimation techniques

A combined nonlinear longitudinal and lateral vehicle control is investigated. Flatness-based nonlinear control and new algebraic estimation techniques for noise removal and numerical differentiation are the main theoretical tools. An accurate automatic path-tracking via vehicle steering angle and driving/braking wheel torque is thus ensured. It combines the control of the lateral and longitudinal motions in order to track straight or curved trajectories and to perform a combined lane-keeping and steering control during critical driving situations such as obstacle avoidance, stop-and-go control, lane-change maneuvers or any other maneuvers. Promising results have been obtained with noisy experimental data, which were acquired by a laboratory vehicle with high dynamic loads and high lateral accelerations.     

Nonlinear decoupling control of four-wheel-steering vehicles with an observer

This paper studies the input-output decoupling control for the nonlinear vehicle model consisting of three degrees of freedom. The technique of quasi-linearization is used to simplify the vehicle model, which preserves inherent coupling effects between longitudinal acceleration/braking force, steering angles and the vehicle states. By choosing the combined control inputs, the input-output map of the vehicle dynamical system is reconstructed. Based on the model, the input-output decoupling controller is proposed. Furthermore, an asymptotically stable observer is presented. A modified form of mean value theorem is used to design the observer for the nonlinear vehicle system with bounded Jacobian. The observer gain can be obtained by solving linear matrix inequalities (LMIs). Several simulations are carried out to show the improvements in vehicle handling and stability due to the inputoutput decoupling control.     

基于路面识别实时控制车轮滑移率的ABS系统

汽车防抱死制动系统(ABS)是一种很重要的汽车主动安全技术。并针对路面具体情况,对车辆防抱制动系统的滑移率实时控制进行研究。该文在MATLAB/Simulink仿真环境下,建立车辆动力学模型,实现了对路面状况识别,同时对基于滑移率控制的防抱制动系统的计算机仿真。仿真结果表明,该系统能真实地反映汽车ABS系统的实际工作过程,达到了满意的控制效果。     

Application of LQ-based semi-active suspension control in a vehicle

A linear quadratic (LQ) based controller and observer concept for a semi-active full-car model is implemented and compared to a skyhook controller using a real vehicle in this paper. Especially an observer including a new modified road model is presented, which reliably filters low frequency disturbances induced by ascending or descending steep hills. Furthermore, methods for the parametrization of the quadratic cost function are presented and it is shown in experiments for different vehicle masses that ride comfort and road holding can be significantly improved by using semi-active suspension control. In order to take nonlinear component characteristics or suspension friction into account a parametrized nonlinear full-car model is presented, which is used for the determination of the controller cost function weights. The performance evaluation is done using a 4-poster test rig as well as measurements conducted on a real road.     

Integrated vehicle control through the coordination of longitudinal/lateral and vertical dynamics controllers: Flatness and LPV/‐based design

This paper deals with global chassis control of automotive vehicles. It focuses on the coordination of suspension and steering/braking vehicle controllers based on the interaction between the vertical and lateral behaviors of the vehicle. It is shown that the lateral acceleration and resulting roll motion of the car generate load transfers that considerably affect vehicle stability. A control law is designed in hierarchical way to improve the overall dynamics of the vehicle and cope with coupled driving maneuvers like obstacle avoidance using steering control and stop‐and‐go control using braking or driving wheel torque. This global control strategy includes two types of controllers. The first one is the longitudinal/lateral nonlinear flatness controller. Based on an appropriate choice of flat outputs, the flatness proof of a 3 DOF two‐wheel nonlinear vehicle model is established. Then, the combined longitudinal and lateral vehicle control is designed using algebraic estimation techniques to provide an accurate estimation of the derivatives and filtering of the reference flat outputs. The second part of the proposed strategy consists of a linear parameter‐varying/ suspension controller. This controller uses lateral acceleration as a varying parameter to account for load transfers that directly affect the suspension system. The coordination between the vehicle vertical and lateral dynamics is highlighted in this study, and the linear parameter‐varying/ framework ensures a specific collaborative coordination between the suspension and the steering/braking controllers, to achieve the desired performance. Simulations on a complex full vehicle model have been validated using experimental data obtained on‐board a real Renault Mégane Coupé. Copyright © 2017 John Wiley & Sons, Ltd.     

基于扩张状态观测器和反步法的非线性超空泡航行体纵向控制

考虑空泡记忆效应的超空泡航行体控制难度较大,主要体现在滑行力的强非线性、模型中的时延特性以及运动中的未知扰动.对于此类多输入多输出的复杂非线性系统,利用传统反步法控制器设计思想,将其改进以适用于超空泡航行体的纵向运动控制.为了对系统模型中存在的未知扰动进行观测补偿,本文设计了线性扩张状态观测器(LESO),将扰动估计值与控制器设计相结合,使用Lyapunov方法分析系统稳定性.最后在不同条件下进行仿真,结果验证了所设计的LESO估计未知扰动的准确性,以及所提控制方法对超空泡航行体纵向控制的有效性.     

利用ADAMS与MATLAB对ABS滑模变结构控制的仿真

为了减少车辆控制系统的开发时间和费用,联合仿真的方法受到越来越多的重视。将多体系统动力学与智能控制理论相结合,对汽车制动防抱死控制系统进行了研究。它结合了不同软件的优点,可以在设计阶段验证控制算法对车辆性能的影响。利用ADAMS/CAR建立了汽车整车多体动力学模型,利用MATLAB/Simulink建立了基于滑移率的滑模变结构防抱死控制系统,利用ADAMS/Controls接口进行模型的集成、系统仿真。结果证明联合仿真方法对ABS系统设计切实可行,该控制算法具有较强的实用性。     

基于模糊控制的汽车防抱制动系统仿真

汽车防抱制动系统(ABS)通过在制动过程中自动控制车轮的制动力矩从而防止了车轮抱死。这对于提高汽车制动时的方向稳定性和转向操纵性，改善汽车的制动效能，保证驾驶员和乘客的安全是十分重要的。文中通过对某轻型客车的防抱制动过程进行动力学分析，建立了该轻型客车ABS模糊控制系统的数学模型，并且在Matlab／simullnk仿真软件下进行了计算机仿真。仿真结果表明，模糊控制的防抱制动系统能取得较好的控制效果，具有一定的自适应能力。