汽车半主动悬架的自适应LQG控制

本文根据汽车半主动悬轲的基本结构，通过力学分析建立了其数学模型，为了克服实际的悬架控制系统动态行的不确定性，采用了自适应ＬＱＧ控制策略。     

汽车主动悬架系统的自适应模糊控制方法

本文提出了一种汽车主动悬架系统的自适应模糊控制方法，该模糊控制方法可以有线自适应调整模糊控制的有关参数。1/4车辆模型作为系统仿真对象，模糊逻辑控制器可以显著发减小车辆的振动及干扰，提高车辆受路面激励时车辆的舒适性。仿真结果清楚地表明该模糊控制方法的有效性。另外，当主动悬架系统模型参数发生变化时该模糊控制器表现出良好的鲁棒性。     

Adaptive Control of Vehicle Suspension

SUMMARY

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

Adaptive Control of Vehicle Suspension

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

Power Requirements for Vehicle Suspension Systems

This paper attempts to analyze the power requirements of a vehicle due solely to its suspension system, neglecting the important powers associated with air and rolling resistance. Power requirements for active and passive suspensions are compared using the simplest possible mathematical model. A mass in a gravity field moves at constant velocity over a surface and is supported by a point contact on the surface by a massless but otherwise arbitrary suspension system. It is shown that the average propulsive power required is equal to the average power lost in the suspension. In the limit cases of very stiff or very soft suspensions this power vanishes. Passive suspensions require no other power, but active suspensions may require significant extra power from the prime mover to generate the suspension forces.     

汽车非线性悬架的混沌研究

采用基于实测数据建立的非线性悬架模型,分析了汽车悬架中的非线性弹簧力和阻尼力,对非线性悬架系统的混沌运动进行了研究.在单频正弦路面、拟周期路面以及随机路面激励情况下,仿真计算得到了系统的响应.分析各激励下系统的相轨迹、庞加莱(Poincaré)截面、时间历程曲线、功率谱图及李亚谱诺夫(Lyapunov)指数图,结果表明非线性悬架系统中存在混沌现象.     

State Observer Design for an Adaptive Vehicle Suspension

This paper presents a state observer design for an adaptive vehicle suspension. Based on simulations, two main issues are investigated, (a) the selection of measurement signals in relation to estimation accuracy and sensing needs and (b) the effects of variations in both road inputs and vehicle parameters on estimation accuracy. Meanwhile, the system stabilities are also examined concerning the effects of using different combination of measurement states and the system parameter variations in practical, possible ranges.     

Design of Robust Controllers for Active Vehicle Suspension Using the Mixed µ Synthesis

Summary The mixed µ synthesis for active suspension problems is proposed. Applying this method the real parametric uncertainties can be taken into consideration, which is more realistic than the traditional approaches, and the design process yields a less conservative compensator than other robust control design methods. The concept of the active suspension design using full-car models to handle the uncertain components is presented. The result of the mixed µ method is compared with the complex µ synthesis, and the passive system.     

Design of Nonlinear Controllers for Active Vehicle Suspensions Using Parameter-Varying Control Synthesis

Nonlinear suspension controllers have the potential to achieve superior performance compared to their linear counterparts. A nonlinear controller can focus on maximizing passenger comfort when the suspension deflection is small compared to its structural limit. As the deflection limit is approached, the controller can shift focus to prevent the suspension deflection from exceeding this limit. This results in superior ride quality over the range of road surfaces, as well as reduced wear of suspension components. This paper presents a novel approach to the design of such nonlinear controllers, based on linear parameter-varying control techniques. Parameter-dependent weighting functions are used to design active suspensions that stiffen as the suspension limits are reached. The controllers use only suspension deflection as a feedback signal. The proposed framework easily extends to the more general case where all the three main performance metrics, i.e., passenger comfort, suspension travel and road holding are considered, and to the design of road adaptive suspensions.     

Design of Nonlinear Controllers for Active Vehicle Suspensions Using Parameter-Varying Control Synthesis

Nonlinear suspension controllers have the potential to achieve superior performance compared to their linear counterparts. A nonlinear controller can focus on maximizing passenger comfort when the suspension deflection is small compared to its structural limit. As the deflection limit is approached, the controller can shift focus to prevent the suspension deflection from exceeding this limit. This results in superior ride quality over the range of road surfaces, as well as reduced wear of suspension components. This paper presents a novel approach to the design of such nonlinear controllers, based on linear parameter-varying control techniques. Parameter-dependent weighting functions are used to design active suspensions that stiffen as the suspension limits are reached. The controllers use only suspension deflection as a feedback signal. The proposed framework easily extends to the more general case where all the three main performance metrics, i.e., passenger comfort, suspension travel and road holding are considered, and to the design of road adaptive suspensions.     

液压主动悬架的非线性自适应控制

以车身垂直加速度和悬架动行程为控制目标，同时引入非线性高通滤波器和非线性低通滤波器，基于逆向递推(Backstepping)技术，并考虑液压系统的非线性特性及其参数不确定性，提出了一种主动悬架的非线性自适应控制方法。仿真结果表明，在不同的激励信号作用下，都取得了较好的控制效果。     

Advanced Ground Vehicle Suspension Systems - A Classified Bibliography

This bibliographical list classifies the extensive literature related to the dynamic analysis and control design aspects of advanced ground vehicle suspension systems. It is restricted to the design of advanced suspensions for ride quality and safety. Brief generalized notices and definitions are presented.     

Advanced Ground Vehicle Suspension Systems - A Classified Bibliography

SUMMARY

This bibliographical list classifies the extensive literature related to the dynamic analysis and control design aspects of advanced ground vehicle suspension systems. It is restricted to the design of advanced suspensions for ride quality and safety. Brief generalized notices and definitions are presented.     

汽车主动悬架的单神经元自适应控制

在1/4汽车动力学模型的基础上,设计了汽车主动悬架的自适应神经元控制器。以车辆的行驶平顺性为主要控制目标,车身垂直加速度、悬架动挠度、车轮动位移为具体评价参数,研究了系统在随机路面激励条件下的时域响应,计算了振动响应的均方根值,考察了在变参数条件下控制器的鲁棒性。仿真结果表明,该控制器能有效改善车辆的综合性能,尤其是平顺性和舒适性,并且具有较好的鲁棒性,对模型参数的变化有一定的适应性。     

车辆主动悬架系统的LMS自适应控制

选择LMS自适应滤波算法，通过调整自适应滤波器的权系数使二次性能指标达最小，根据单个样本方差的负梯度来调节权系数；得到控制输出。针对简化的车辆模型，将空钩控制、广义自适应控制与LMS自适应控制相对比。仿真计算表明，主动悬架系统LMS自适应控制策略不仅计算简单，而且理论上在主动悬架系统中的应用是切实可行的，性能明显优于其它对比控制方法。     

基于神经网络的半主动悬架自适应模糊控制

提出了基于神经网络的自适应模糊控制策略。模糊控制主要用来对付系统的非线性；神经网络根据振动响应的方差递推结果来辨识车体的振动情况实时调节模糊控制器的量化因子，使模糊控制器对路面的变化具有自适应的能力。在半主动悬挂1／4车非线性模型的基础上进行了仿真研究。     

Design of Robust Controllers for Active Vehicle Suspension Using the Mixed µ Synthesis

Summary The mixed µ synthesis for active suspension problems is proposed. Applying this method the real parametric uncertainties can be taken into consideration, which is more realistic than the traditional approaches, and the design process yields a less conservative compensator than other robust control design methods. The concept of the active suspension design using full-car models to handle the uncertain components is presented. The result of the mixed µ method is compared with the complex µ synthesis, and the passive system.     

车辆半主动悬架神经网络自适应控制的研究

针对变刚度半主动悬架这种时变的、非线性复杂系统,提出将神经网络自适应控制策略用于该悬架的控制,研究中主要用车身垂直加速度作为主要控制目标,以提高车辆行驶的平顺性,同时在仿真控制研究中兼顾悬架动挠度和车轮动载荷的变化,以提高车辆行驶安全性和操纵稳定性,通过仿真计算和结果分析验证了其可行性和有效性。     

Active Damping in Road Vehicle Suspension Systems

Low order, linearized dynamic models of road vehicle suspension systems are analyzed to provide insight into the benefits of suspensions incorporating generalized velocity feedback compared with conventional passive suspensions. Damping forces from passive dampers are supplemented by forces generated by an active element requiring a power supply. A simple criterion is developed which indicates whether or not the introduction of activedamping forces will result in significant benefit for pneumatic tired vehicles.

An extended active suspension concept involving a high-gain load leveler as well as active damping is analyzed. The realization of active or semi-active damping forces through electrical or hydraulic means is briefly discussed.