最小均方自适应控制汽车主动悬架的仿真

根据汽车行驶平顺性和操纵稳定性的评价方法，确定簧上质量的加速度、车轮与地面间的动载荷以及簧上、簧下质量的动挠度为评价指标。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。针对简化的车辆模型，经过大量的仿真计算，确定主动悬架系统LMS自适应控制策略不仅计算简单，而且3项评价指标均得到显著的降低。结果分析表明，LMS自适应控制策略理论上在主动悬架系统中的应用是切实可行的。     

基于LMS自适应滤波的模糊控制主动悬架研究

以车辆操纵稳定性及行驶平顺性为控制目标，根据路面一车辆系统的特点，提出一种在线可调整的模糊控制算法，利用LMS自适应模块调整模糊控制器的自调整因子，改善单一模糊控制算法对专家先期经验的依赖。针对简化的车辆模型，以路面信号作为激励源，进行悬架系统的振动控制研究，结果表明提出的算法对车辆悬架系统的振动控制具有较好的适应性。     

发动机主动悬置3种控制方法的比较

应用LMS自适应前馈控制、LQR控制和模糊PID控制3种方法对发动机电磁式主动悬置进行研究.在MATLAB/Simulink环境下建立了主动悬置控制系统模型,并以车身垂向加速度为性能指标进行了仿真分析,对比了采用上述3种控制方法时主动悬置的隔振能力、鲁棒性和稳定性.仿真结果表明,在主动悬置的控制上模糊PID控制方法优于其他两种控制方法.     

制动工况下自适应前照灯系统调光的新方法

计算了因路面不平度和制动引发的车身俯仰角度变化,提出使用LMS自适应滤波器处理车身高度传感器信号,结合PID控制步进电机,动态实现制动时调整前照灯光轴的方法。同时采用Simulink仿真和实车测试验证该方法的有效性,扩展了现有自适应前照灯系统的调光功能。     

车辆主动悬架自适应模糊PID控制

针对车辆悬架系统的动态特性,将现代控制理论运用于主动悬架控制,提出一种新的控制策略———自适应模糊PID控制,并通过仿真验证了其可行性及有效性。这种新型智能控制策略为车辆主动悬架控制理论的研究提供了一条新思路。     

基于主动自适应悬架系统的道路友好性研究

为了减少车辆轮胎动载荷对道路路面的影响,提高车辆的道路友好性,设计了以主动悬架为控制对象的自适应模糊PID控制系统。该系统将模糊控制与常规PID控制有机融合,利用模糊隶属函数实时对PID控制参数进行调节。建立5自由度主动悬架友好路面仿真模型,以C级路面谱为路面输入信号,道路友好性评价指标采用动载荷系数、动态载荷应力因子及95百分位4次幂和力,对主动自适应悬架系统进行研究。研究结果表明:采用自适应模糊PID控制的主动悬架系统的道路友好性明显优于被动悬架和单一模糊控制的主动悬架;采用模糊PID控制的主动悬架系统可显著降低车辆对路面的动态载荷,提高道路的使用寿命,最终达到提高公路设计的质量和安全性的目的。     

汽车主动悬架自调整模糊控制试验

以汽车操纵稳定性及行驶平顺性为控制目标,提出一种在线可调整的模糊控制算法,其模糊控制规则表可以用解析的方法进行计算。针对简化的汽车模型,为控制悬架系统的振动设计了自调整模糊控制器。与自适应控制主动悬架系统相比较,在两自由度悬架系统试验台架上进行了对比试验研究,结果表明该算法对汽车的振动控制具有明显效果,进一步说明提出的算法对汽车悬架系统的振动控制具有较好的适应性。     

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。     

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。     

车辆悬架的最优自适应与自校正控制

本文研究了车辆主动悬架自适应与自校正控制的策略与算法。     

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.     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).     

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.     

Theoretical Limitations in Active Vehicle Suspensions

Vehicle suspensions in which forces are generated in response to feedback signals by active elements obviously offer increased design flexibility compared to conventional suspensions using passive elements such as springs and dampers. It is often assumed that if practical difficulties are neglected, active systems could in principle produce arbitrary ideal, behavior. It is shown, using a simple linear two degree-of-freedom suspension system, model that even using complete state feed back and in the case of in which the system is controllable in the control theory sense, there still are limitations to suspension performance in the fully active case. If the ideal suspension performance is defined based on low-pass filtering of roadway unevenness inputs, an active suspension may not offer much better performance than a partially active or adaptive passive suspension depending upon the values of certain vehicle parameters.     

Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation

This paper presents a novel active control approach for a hydraulic suspension system subject to road disturbances. A novel impedance model is used as a model reference in a particular robust adaptive control which is applied for the first time to the hydraulic suspension system. A scheme is introduced for selecting the impedance parameters. The impedance model prescribes a desired behaviour of the active suspension system in a wide range of different road conditions. Moreover, performance of the control system is improved by applying a particle swarm optimisation algorithm for optimising control design parameters. Design of the control system consists of two interior loops. The inner loop is a force control of the hydraulic actuator, while the outer loop is a robust model reference adaptive control (MRAC). This type of MRAC has been applied for uncertain linear systems. As another novelty, despite nonlinearity of the hydraulic actuator, the suspension system and the force loop together are presented as an uncertain linear system to the MRAC. The proposed control method is simulated on a quarter-car model. Simulation results show effectiveness of the method.     

Theoretical Limitations in Active Vehicle Suspensions

SUMMARY

Vehicle suspensions in which forces are generated in response to feedback signals by active elements obviously offer increased design flexibility compared to conventional suspensions using passive elements such as springs and dampers. It is often assumed that if practical difficulties are neglected, active systems could in principle produce arbitrary ideal, behavior. It is shown, using a simple linear two degree-of-freedom suspension system, model that even using complete state feed back and in the case of in which the system is controllable in the control theory sense, there still are limitations to suspension performance in the fully active case. If the ideal suspension performance is defined based on low-pass filtering of roadway unevenness inputs, an active suspension may not offer much better performance than a partially active or adaptive passive suspension depending upon the values of certain vehicle parameters.     

车内多通道自适应主动降噪的研究

在研究有源噪声控制算法和结构的基础上,提出了基于滤波-X LMS算法的多通道有源噪声控制模型,利用自适应离线建模方法建立了次级声通道模型,搭建了有源噪声控制的硬件实验系统,对客车车厢内的噪声进行控制试验,获得了较好的降噪效果。