基于MATLAB的主动悬架的最优控制分析

本文通过建立二自由度车辆悬架模型,应用了最优控制理论设计了主动悬架控制器,并在MATLAB/SIMULINK中建立了系统模型并进行了仿真。研究结果表明主动悬架比被动悬架的控制效果要好。     

车载视觉感知预瞄下的主动悬架控制分析与实车应用(四)

<正>（接上期）1/4车辆2自由度的主动悬架系统数学模型如图34所示。以上给出的车辆各被动、主动或半主动悬架系统模型均为线性悬架系统的振动模型，悬架和车轮弹簧刚度是定值，悬架的阻尼系数也是常数。然而，事实上车辆悬架中的弹性元件和阻尼元件均存在不同程度的非线性，并且由于车辆悬架材料的变形老化以及使用环境等不确定因素影响，使得实际的车辆悬架系统是一个复杂的非线性不确定系统。主动悬架系统的非线性控制主要由其所采用的控制策略来体现。依据控制策略不同所采用的控制理论也不同。通过对主动悬架系统施加一定的控制规则或策略，     

改进的模糊PID控制器对4自由度主动悬架振动控制的研究

建立了4自由度1／2车体力学模型,针对车辆悬架为一非线性、时滞、不确定系统,设计了一种改进的主动悬架模糊PID控制器。以SANTANA2000实车悬架为仿真参数,以阶跃信号激励为路面输入,在Matlab中进行了时域仿真。结果表明,改进的模糊PID控制的主动悬架对车身垂直加速度、悬架动挠度、轮胎动载荷等平顺性指标改善明显．响应达到稳定状态的时间也有了显著的缩短,车辆乘坐的舒适性和操纵稳定性优于被动悬架和单纯的模糊控制的主动悬架,对车辆主动悬架控制的开发具有参考价值。     

汽车主动悬架的原理及发展简述

现代社会对车辆性能及行驶速度越来越高的要求,电液控制理论和计算机技术越来越快的发展,以及传感器、微处理器等电液控制元件越来越精的制造技术,共同催生了汽车主动悬架。所谓汽车主动悬架,即能够根据车辆行驶的路面、工况和载荷等情况来控制自身工作状态,使车辆的整体行驶性     

An Investigation into Vehicle Active Suspension with Electromagnetic Actuator

应用电磁感应的基本原理,设计了一种响应快、出力大和动行程长的车辆主动悬架用作动器.建立了该作动器的集总元件的动力学模型并进行仿真;同时对制作的样机进行了斜坡电压输入和方波电压输入的电磁力测试,测试与仿真结果很好吻合,验证了模型的准确性.最后,结合最优控制理论和矢量控制方法,对包含作动器动力学模型的车辆主动悬架系统进行了正弦路面激励下的仿真分析,结果表明,与被动悬架系统相比,主动悬架系统能明显提高车辆的平顺性.     

电磁主动悬架的设计及仿真研究

基于电磁学原理,利用电磁铁作为主动悬架的作动器,构造出电磁作动器的一般结构。在1/4汽车悬架的基础上,建立了电磁主动悬架的非线性模型,并应用现代控制理论设计了该模型的次优控制器,对该模型进行分析、仿真。模拟结果表明,电磁悬架能够实现一般主动悬架的功能,满足车辆平顺性的要求,可以适用于汽车的悬架系统。     

基于硬件在环与远程参数控制技术的半主动悬架车辆道路模拟试验

针对半主动悬架车辆减振器存在宽泛阻尼特性区间而难以进行道路模拟试验的问题,提出了一种基于硬件在环(HIL)与远程参数控制(RPC)技术的半主动悬架车辆道路模拟试验方法,由RPC系统提供CAN报文动态信号,HIL系统仿真CAN报文静态信号,并整合CAN报文,发送给悬架电子控制单元(ECU),悬架ECU为主动减振器提供控制指令,控制减振器特性状态,RPC系统对车辆与台架系统进行频响函数求解、迭代,驱动台架系统运行,从而实现了对半主动悬架车辆的道路模拟试验。     

汽车半车主动悬架的最优控制研究

本文运用车辆动力学理论,建立了半车四自由度主动悬架系统的动力学模型。同时依据最优控制理论设计了主动悬架最优控制器并进行了Matlb+simulink仿真。研究结果表明采用最优控制的主动悬架比被动悬架具有更好的平顺性。     

基于MATLAB/Simulink车辆主动悬架时频响应研究

为了研究车辆主动悬架时频响应特性,以主动悬架1/4车辆模型为研究对象,依据车辆系统动力学理论建立了1/4车辆主动悬架动力学模型,利用Simulink对悬架和车身加速度进行仿真,对不同车速下的路面高程曲线的频谱和车辆固有频率进行分析。研究结果表明,仿真车辆在B级公路以60km/h车速行驶时,路面激励引发车辆共振。     

主动悬架系统控制策略研究

文章设计一种主动悬架控制策略,通过建立四分之一车辆主动悬架系统模型,设计模糊滑模控制策略对主动悬架系统进行控制,并使用Matlab/Simulink软件对所建立的模型进行仿真分析。通过仿真结果验证了所建模型和控制策略的准确性,同时也改善了悬架系统的性能。     

一种用于1／2汽车主动悬架的可调模糊控制器

本文对用于1／2汽车主动悬架系统的模糊控制器进行了研究。在设计模糊控制器时，引入模糊控制规则调整因子，使得控制策略灵活，适应性强，并以模拟路面时间历程为输入对汽车1／2主动悬架模型进行计算机仿真，结果表明用这种可调模糊控制器控制的主动悬架，汽车的适性和操纵稳定性都得到了明显改善。     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.     

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.     

联合线性和模糊逻辑控制的4自由度主动悬架

文中提出了联合线性和模糊逻辑控制的4自由度汽车主动悬架。该主动悬架以线性控制为主，模糊逻辑控制为辅，前者以车身加速度作为控制量，后者以车身的垂直速度与俯仰速度的线性组合和车身位移作为模糊控制规则的输入变量。最后用Simulink进行仿真，并把所得结果与被动的结果进行比较，说明该系统对提高汽车的平顺性是非常有效的。     

基于串联型模糊神经网络的汽车半主动悬架的研究

本文建立了五自由度汽车半主动悬架系统模型，提出一种用于汽车悬 半主动振动控制系统的模糊神经网络方法，对半主动悬架 计算机仿真和结果分析，并通过与被动悬架相比较，证明半主动悬架系统在减少振动，提高汽车平一方面要优于被动悬架。     

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.     

Stability and optimised H∞ control of tripped and untripped vehicle rollover

Vehicle rollover is a serious traffic accident. In order to accurately evaluate the possibility of untripped and some special tripped vehicle rollovers, and to prevent vehicle rollover under unpredictable variations of parameters and harsh driving conditions, a new rollover index and an anti-roll control strategy are proposed in this paper. Taking deflections of steering and suspension induced by the roll at the axles into consideration, a six degrees of freedom dynamic model is established, including lateral, yaw, roll, and vertical motions of sprung and unsprung masses. From the vehicle dynamics theory, a new rollover index is developed to predict vehicle rollover risk under both untripped and special tripped situations. This new rollover index is validated by Carsim simulations. In addition, an H-infinity controller with electro hydraulic brake system is optimised by genetic algorithm to improve the anti-rollover performance of the vehicle. The stability and robustness of the active rollover prevention control system are analysed by some numerical simulations. The results show that the control system can improve the critical speed of vehicle rollover obviously, and has a good robustness for variations in the number of passengers and longitude position of the centre of gravity.     

Vehicle dynamics control using an active third-axle system

This paper introduces the active third-axle system as an innovative vehicle dynamic control method. This method can be applicable for different kinds of three-axle vehicles such as buses, trucks, or even three-axle passenger cars. In this system, an actuator on the middle axle actively applies an independent force on the suspension to improve the handling characteristics, and hence, its technology is similar to slow-active suspension systems. This system can change the inherent vehicle dynamic characteristics, such as under/over steering behaviour, in the linear handling region, as well as vehicle stability in the nonlinear, limit handling region. In this paper, our main focus is to show the potential capabilities of this method in enhancing vehicle dynamic performance. For this purpose, as the first step, the proposed method in both linear and nonlinear vehicle handling regions is studied mathematically. Next, a comprehensive, nonlinear, 10 degrees of freedom vehicle model with a fuzzy control strategy is used to evaluate the effectiveness of this system. The dynamic behaviour of a vehicle, when either uncontrolled or equipped with the active third axle is then compared. Simulation results show that this active system can be considered as an innovative method for vehicle dynamic control.     

Linear Quadratic Gaussian Control of a Quarter-Car Suspension

This paper presents a method for designing linear multivariable controllers in the frequency-domain for an intelligent controlled suspension system for a quarter-car model. The design methodology uses singular value inequalities and optimal control theory. The vehicle system is augmented with additional dynamics in the form of an integrator to affect the loop shapes of the system. The measurements are assumed to be obtained in a noisy state, and the optimal control gain and the Kalman filter gain are derived using system dynamics and noise statistics. A combination of singular value analysis, eigenvalue analysis, time response, and power spectral densities of random response is used to describe the performance of the active suspension systems.