Review:Advances in the control of mechatronic suspension systems

The suspension system is a key element in motor vehicles. Advancements in electronics and microprocessor technology have led to the realization of mechatronic suspensions. Since its introduction in some production motorcars in the 1980 s, it has remained an area which sees active research and development, and this will likely continue for many years to come. With the aim of identifying current trends and future focus areas, this paper presents a review on the state-of-the-art of mechatronic suspensions. First, some commonly used classifications of mechatronic suspensions are presented. This is followed by a discussion on some of the actuating mechanisms used to provide control action. A survey is then reported on the many types of control approaches, including look-ahead preview, predictive, fuzzy logic, proportional–integral–derivative(PID), optimal, robust, adaptive, robust adaptive,and switching control. In conclusion, hydraulic actuators are most commonly used, but they impose high power requirements, limiting practical realizations of active suspensions. Electromagnetic actuators are seen to hold the promise of lower power requirements, and rigorous research and development should be conducted to make them commercially usable. Current focus on control methods that are robust to suspension parameter variations also seems to produce limited performance improvements, and future control approaches should be adaptive to the changeable driving conditions.     

Nonlinear state estimation for suspension control applications: a Takagi-Sugeno Kalman filtering approach

A new nonlinear state estimation approach, which combines classical Kalman filter theory and Takagi-Sugeno (TS) modeling, is proposed in this paper. To ensure convergence of the TS observer, conditions are derived that explicitly account for the TS model's confined region of validity. Thereby, the secured domain of attraction (DA) of the TS error dynamics is maximized within given bounds. The TS Kalman filtering concept is then applied to a hybrid vehicle suspension configuration, whose nonlinear dynamics are exactly represented by a continuous-time TS system. The benefit of the novel estimation technique is analyzed in comparison with the well-known EKF and UKF variants in simulations and experiments of a passive and an actively controlled suspension configuration in a quarter-car set-up. Employing a real road profile as disturbance input, the TS Kalman filter shows the highest estimation quality of the concepts studied. Moreover, as its computational complexity adds up to only one third of the one involved with the classical methods, the new approach operates remarkably efficient.     

最优控制理论在人车路磁流变半主动悬架中的应用

基于半主动悬架车辆的1/4动力学模型,论述了磁流变液特性及磁流变减振器的工作原理,推导了在随机最优控制理论下可调阻尼力和状态变量之间的关系,应用matlab/simulink编制了人车路模型的仿真程序,并以简化模型为例,考察了在磁流变阻尼器控制下的人车路平顺性问题.计算结果表明,与没有磁流变减振器的被动悬架相比较,该减振器的应用能够较好的改善汽车的平顺性,对提高人体的舒适性以及进一步深入研究该系统的振动,改善道路的振动特性有一定的指导意义.     

基于Backstepping 方法的全车液压主动悬挂最优控制设计

设计先进的悬挂系统是提高车辆性能的重要途径之一.本文针对并联式液压主动悬挂系统建立了较为详细的7自由度全车非线性模型,并根据其结构特点提出了线性二次型最优控制与Backstepping方法相结合的控制策略.仿真结果证明,利用该控制策略,主动悬挂系统既可以满足悬挂行程约束,又可以有效的提高乘坐舒适性;而且,与相同条件下的被动悬挂相比,车辆性能有明显改善.     

Vehicle state estimation for anti-lock control with nonlinear observer

Vehicle state estimation during anti-lock braking is considered. A novel nonlinear observer based on a vehicle dynamics model and a simplified Pacejka tire model is introduced in order to provide estimates of longitudinal and lateral vehicle velocities and the tire-road friction coefficient for vehicle safety control systems, specifically anti-lock braking control. The approach differs from previous work on vehicle state estimation in two main respects. The first is the introduction of a switched nonlinear observer in order to deal with the fact that in some driving situations the information provided by the sensor is not sufficient to carry out state estimation (i.e., not all states are observable). This is shown through an observability analysis. The second contribution is the introduction of tire-road friction estimation depending on vehicle longitudinal motion. Stability properties of the observer are analyzed using a Lyapunov function based method. Practical applicability of the proposed nonlinear observer is shown by means of experimental results.     

基于扩张状态观测器的车辆横摆稳定模型预测控制器设计

针对车辆横摆稳定性控制问题,本文提出一种基于扩张状态观测器的线性模型预测控制器设计方法.首先,将非线性车辆模型线性化,建立带有模型误差干扰项的线性模型,其中线性化导致的模型误差采用扩张状态观测器估计得到,并证明了观测器的稳定性.然后基于此模型设计线性预测控制器,近似实现了非线性预测控制器的控制效果,同时降低了计算量.最后,通过不同路况下的仿真实验结果,验证了所提方法的计算性能和控制效果.     

前馈神经网络在汽车悬架设计中的应用*

提出采用GABP贝叶斯算法来建立悬架运动学分析近似模型。该算法是一种新型前馈神经网络训练算法,它以提高网络的泛化性能为主旨,其训练目标在于获取对应于后验分布最大值的权值向量。以双横臂式前独立悬架为例,采用GABP贝叶斯算法建立了以车轮接地点侧向最大滑移量为输出的运动学分析近似模型,并与LMBP算法、多项式回归和广义回归神经网络这三种方法进行了比较。结果表明,基于GABP贝叶斯算法的近似模型的预测精度明显高于其他几种模型,并且受随机因素的影响很小。     

Constrained optimal control: an application to semiactive suspension systems

This article applies three different control techniques to the design of a quarter-car semiactive suspension system. The three techniques, originally developed to solve a constrained optimal control problem, are optimal gain switching, discontinuous variable structure control and explicit model predictive control. All of them divide the state space into convex regions and assign a linear or affine state feedback controller to each region. The partition of the state space is computed off-line. During the on-line phase, the controller switches between the subcontrollers according to the current state. All the above techniques gave satisfactory results when applied to the design of semiactive suspension systems. A detailed comparison in terms of computational complexity, performance and simplicity of the design is proposed in the article.     

提高车辆安全性的输出反馈自适应控制

研究含有时变参数的车辆动力学模型的输出跟踪控制问题.控制目标是使车辆的横摆角速度和质心侧偏角分别跟踪理想的设定值,通过反推方法设计输出反馈自适应控制器.控制器的输出为主动横摆力矩,通过控制主动横摆力矩来控制车辆的输出响应跟踪理想的输出信号,从而提高车辆的安全性.仿真结果表明,该控制器能更好地适应车速和路况的变化,鲁棒性强.     

惯性信息状态观测器在车辆稳定系统中的应用

针对车辆安全稳定系统的算法设计中诸如车身质心侧偏角等惯性信息难以估量的问题,研究了状态观测器在系统中的应用方法。建立了车辆二自由度单车道数学模型,设计了质心侧偏角状态观测器的流程,并对此流程中的估算条件和影响因素进行了计算分析。通过数值计算类软件Matlab和动力学仿真类软件Adams的联合仿真,验证了所设计的状态观测器的精度能够满足车辆安全稳定系统的算法设计中的要求。     

A position controlled disc valve in vehicle semi-active suspension systems

The paper deals with an electromagnetic hydraulic disc valve with a position feedback designed for vehicle semi-active suspension systems. The features of this design are of a simple structure, few critical dimensions, low manufacturing cost, and compact valve size. Although the valve is designed for a vehicle suspension system, it can be used as a two-port proportional control valve for other industrial hydraulic control applications. The paper is concerned with the theoretical model of the valve, including its static and dynamic characteristics with the disc position control, together with the experimental results.     

PDC控制器在车辆半主动悬架上的应用研究

讨论了整车八自由度模型并行分布补偿(PDC)控制器的设计,并求取了公共矩阵P及其对控制器稳定性的影响.基于自适应神经网络的神经网络模糊推理系统ANFIS的自学习和非线性逼近能力,提取模糊控制规则,增强了控制器对于不同路面的适应能力.在整车悬架T-S模糊动态模型的基础上,进行了Matlab软件仿真.仿真实验表明,该控制器对于悬架整体性能有所改善.     

固定翼无人机的自抗扰反步控制

针对固定翼无人机姿态和速度控制中系统存在模型不确定性和外界扰动的情况,本文设计了基于扩张状态观测器的反步控制器抑制系统扰动以提高无人机的控制性能.首先建立无人机速度误差模型和姿态误差模型,其中姿态误差模型采用四元数作为变量以避免欧拉角在描述姿态时存在的奇点问题和复杂三角运算;进而设计扩张状态观测器对系统中存在的扰动进行估计,并将扰动估计值与控制器设计相结合,分别设计出姿态控制器和速度控制器来抑制扰动的影响且使无人机姿态和速度收敛到期望值.最后基于李雅普诺夫理论证明系统的稳定性.仿真结果表明,本文所设计方法能够抑制系统中存在的扰动.     

基于模糊控制策略的车辆主动悬架研究

建立了车辆整车7自由度模型的主动悬架控制的系统状态方程模型,设计了两种模糊控制策略,方法一针对整车模型,采用一种控制方法,方法二针对整车模型的运动方式,设计不同的模糊控制器,垂直振动模糊控制器,俯仰振动模糊控制器,侧倾振动模糊控制器和逻辑控制器,仿真结果表明,所设计的模糊控制器对提高车辆的舒适性与操纵稳定性有较好的效果.     

Nonlinear cascade strategy for longitudinal control in automated vehicle guidance

This paper deals with automatic control design for automotive driving with a special focus on the longitudinal control. The automotive vehicle is a complex system characterised by highly nonlinear longitudinal and lateral coupled dynamics. Consequently, the control design for automated driving should deal with both of these dynamic couplings. Indeed, the longitudinal control plays an important role in the automated guidance to ensure safety and comfort of automotive passengers. In this work, a nonlinear cascade longitudinal control based on inner and outer-loops design is proposed. The lateral control is handled following a model predictive approach ensuring the automated steering of the vehicle. Finally, the nonlinear longitudinal control is integrated with the lateral control in a whole architecture to perform a coupled longitudinal and lateral control. The effectiveness of the automated driving strategy is highlighted through simulation results.     

并联新能源汽车最优效率实时控制

为了提高并联混合动力汽车驱动系统的实时效率,降低燃油消耗,本文提出一种基于效率最优的协调控制策略.根据不同驱动模式下电池的充放电状态,建立了充放电状态下驱动系统的等效燃油消耗模型,在分析电池效率和发动机效率的基础上,得到驱动系统效率的统一表达式,进而通过建立不同功率需求不同荷电状态下系统最优效率的功率分配系数图谱,设计了系统效率最优的协调控制策略,协调控制策略根据优化的功率分配系数在发动机和电机间进行力矩分配,协调控制策略可以离线计算并实时执行.两种工况循环下的仿真结果表明效率最优控制策略能有效地提高混合动力系统实时效率和燃油经济性.     

非线性车辆悬架系统的滞后分岔及多稳态控制

考虑一类单自由度1/4非线性车辆悬架系统,根据Floquet理论得到周期运动的Floquet乘子用于判定其稳定性;并得到Lyapunov指数用于刻画混沌运动的性质.揭示了系统中一种新的滞后分岔：滞后环由一条稳定的周期轨道、一条不稳定周期轨道和一条周期轨道的倍化序列构成.其中周期轨道的倍化序列在滞后环的边界已经形成混沌轨道;因此随参数改变在该滞后环边界将产生一条稳定周期轨道与一条混沌轨道之间的跳跃现象.并且,若周期倍化序列形成的混沌轨道在滞后环边界处与不稳定周期轨道接触,混沌轨道将产生边界激变而突然消失,并跳跃至另一条稳定的周期轨道.根据线性增益控制法,实现了滞后环内部的多稳态控制,包括从大振幅周期3轨道控制到小振幅周期1轨道,以及周期1轨道控制到混沌轨道.本文研究结果可为车辆悬架的动力学设计提供理论参考.     

Application of a neuro-fuzzy system to control a mobile vehicle

We describe a fuzzy control based on a neural network, which is obtained by merging the advantages of a neural network, a competitive algorithm, and fuzzy control. This adaptive fuzzy control system can deal with data sampled by a neural network. From such training data, it can produce more reasonable fuzzy rules by a competitive (clustering) algorithm, and finally control the object by the optimized fuzzy rules. This is not a simple combination of the three methods, but a merger into one control system. Some experiments and future considerations are also given.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

兼顾平顺性与车高调节的重型车空气悬架控制

空气悬架由于质量轻、刚度以及高度可调等优点在重型车中得到了广泛的应用.空气悬架可以实现重型车的两项重要功能:平顺性保证以及车身高度调节,但是空气悬架的平顺性以及车身高度调节均通过空气弹簧气压腔的气压改变来实现,因此二者是彼此制约和冲突的.然而,目前对空气悬架车高调节的研究追求控制的精确性与稳定性而忽略了平顺性,而对平顺性的研究又几乎不考虑车高变化造成的影响.基于上述动机,本文提出了兼顾平顺性的空气悬架重型车车高调节鲁棒控制方法,实现了平顺性保障下的车高调节曲线精确跟踪控制,提升了重型车空气悬架系统的整体性能.实车参数仿真验证了所提出方法在平顺性与车高调节两项指标中的优越性.     

带有干扰观测器的高超声速飞行器滑模控制

针对高超声速飞行器非线性和易受干扰影响的特点,提出了带有扩张状态干扰观测器的连续滑模控制方法.在对飞行器非线性模型做线性化处理的基础上,设计了一种连续时间滑模控制器.该控制器在对不确定性和未知动态保持鲁棒性的基础上,消除了传统滑模中存在的抖振现象.对系统中存在的外加干扰,设计了扩张状态干扰观测器.将外加干扰作为系统的一个状态变量被估计出来,再将估计值用作滑模控制器的补偿量,进而达到消除外干扰的目的.在高超声速飞行器巡航飞行状态的基础上进行了仿真.仿真结果表明,所提出的方案能够满足控制要求.