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。     

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.     

汽车主动悬架的自校正控制

主动悬系统能使车辆的乘坐舒适性和操纵稳定性同时得到改善，其中执行机构和控制算法的优劣决定了该系统的性能。     

基于LQR控制的现代客车自适应空气悬架

长期在不良工况的道路上驾驶会降低驾驶员的乘坐舒适性。随着人们对乘坐舒适性需求不断提升,空气弹簧的优势尤为明显。文章提出了一种基于LQR控制策略的自适应空气悬架系统的创新设计方案,提出的LQR控制器采用粒子群算法进行优化。以客车空气悬架为研究对象,采用MATLAB软件对空气悬架系统的被动和自适应动力学模型进行了设计和仿真。仿真结果表明,自适应空气悬架系统在保证车辆稳定性的同时,降低了车辆在随机道路上的最大位移幅值,从而提高了车辆的平顺性。     

基于改进粒子群优化算法的多目标自适应巡航控制

跟驰过程中,在保证安全性的前提下为了提升自适应巡航控制(ACC)系统的舒适性和燃油经济性,研究了多目标自适应巡航控制算法.在建立车间纵向运动学模型的基础上,根据模型预测控制理论,设计综合考虑安全性、舒适性、燃油经济性以及车辆自身限制等因素的目标函数和约束条件,并引入松弛因子向量软化硬约束边界解决无可行解问题.进一步在滚...     

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。     

Novel stability control strategy for distributed drive electric vehicle based on driver operation intention

In this paper, a novel direct yaw control method based on driver operation intention for stability control of a distributed drive electric vehicle is proposed. It was discovered that the vehicle loses its stability easily under an emergency steering alignment (EA) problem. An emergent control algorithm is proposed to improve vehicle stability under such a condition. A driver operation intention recognition module is developed to identify the driving conditions. When the vehicle enters into an EA condition, the module can quickly identify it and transfer the control method from normal direct yaw control to emergency control. Two control algorithms are designed. The emergency control algorithm is applied to an EA condition while the adaptive control algorithm is applied to other conditions except the EA condition. Both simulation results and real vehicle results show that: The driver module can accurately identify driving conditions based on driver operation intention. When the vehicle enters into EA condition, the emergent control algorithm can intervene quickly, and it has proven to outperform normal direct yaw control for better stabilization of vehicles.     

基于ILMI算法的车辆半主动悬架静态输出反馈控制

针对采用磁流变阻尼器的1/4汽车半主动悬架模型进行振动控制分析。利用迭代线性矩阵不等式(ILMI)算法在输出反馈控制中的求解优势,提出基于ILMI算法的半主动悬架静态输出反馈控制方法。仿真结果表明,结合合适的控制算法,采用磁流变阻尼器的半主动悬架系统有效地改善了汽车驾驶平顺性和乘坐舒适性。     

Control Algorithms for Active Cab Suspensions on Agricultural Tractors

This paper describes active agricultural tractor cab suspensions based on optimal control theory. Control algorithms based on time invariant state feedback and on adaptive control are developed and studied. The influence of different observers and measurement noise levels on the vibration damping capacity are studied as well as the power consumption for the suspensions.

The principle for the adaptive algorithm is based on the parameters in the penalty matrices being varied so that the resulting controller always strives to make optimum use of available travel space. The feedback and observer gains are also changed depending on the characteristics of the vehicle's frame movements.

The results show that it is possible to design an effective active suspension, but that the choice of feedback gains must be dependent on the surface characteristics to reach satisfactory vibration damping performance.     

一种引入行驶状态识别的半主动悬架PID控制修正算法

基于车辆不同行驶状态（路面不平度和车速）下悬挂质量垂向加速度和悬架动挠度响应不相同的客观事实,针对半主动悬架PID控制器无自适应能力的局限,以悬挂质量垂向加速度和悬架动挠度响应作为车辆行驶状态的识别判据．建立起一种引入行驶状态识别的半主动悬架PID控制修正算法,进而以某型轿车为对象,采用MATLAB／Simulink建立起半主动悬架PID控制的仿真模型,针对不同行驶状态计算出PID控制算法修正前、后的车辆平顺性响应并加以对比,表明所提出的PID控制修正算法是有效的。     

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).     

Active control strategy for the running attitude of high-speed train under strong crosswind condition

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host–target computer technology provided by Matlab/Simulink.     

基于模糊自适应PID的客车电控空气悬架车高调节控制策略研究

电控空气悬架能够根据客车行驶工况进行车身高度自适应调节,从而能够显著提升客车行驶稳定性以及燃油经济性,车高调节控制设计具有重要意义。文章利用模糊PID控制算法对车身高度调节进行控制策略设计,有效缓解了客车电控空气悬架车高调节过程中存在的空气弹簧的“过充”“过放”及“振荡”等问题,分析客车电控空气悬架车高调节具体过程,建立包括车身、储气罐、电磁阀以及空气弹簧等在内的车高调节系统数学模型,最后完成了客车电控空气悬架车高调节模糊自适应PID控制策略设计及性能仿真验证。研究结果表明,所运用的模糊自适应PID控制策略能够完成客车电控空气悬架车身高度的准确调节。     

Discrete Adaptive Active Suspension for Hardware Implementation

This paper presents a discrete adaptive control approach for an active suspension. The study involves formulation of an active suspension as a digital controller problem involving the time delays. A nonlinear time varying (NTV), single input single output (SISO) suspension model is considered for the analysis. A discrete model reference adaptive control (DMRAC) approach with recursive least square (RLS) estimation is used to form the controller. The controller is designed to maintain the static equilibrium irrespective of dynamic load variations as a disturbance force on the model. Simulation results for deterministic and stochastic inputs are presented to substantiate the approach. Results indicate good performance of adaptive controller even for large dynamic variations of the model and has the potential for a successful hardware implementation.     

基于AI选型的汽车悬架系统参数化设计流程构造

建立了用于汽车悬架系统选型的多层前馈型人工神经网络模型,它采用自适应调整的BP算法。选型推理的依据有：轴距、前轮距、后轮距、整备质量、驱动形式、最高车速、制动形式、发动机最大功率和发动机排量。推理结果为前、后悬架的具体型式。经测试,其与实际情况的吻合率,对前悬架达到了100％,对后悬架达到了70％。进而开发出典型悬架型式的三维参数化设计模板,并集成相关技术环节,构造出基于AI选型的悬架系统参数化设计的一般流程。     

An adaptive integrated algorithm for active front steering and direct yaw moment control based on direct Lyapunov method

In this article, an adaptive integrated control algorithm based on active front steering and direct yaw moment control using direct Lyapunov method is proposed. Variation of cornering stiffness is considered through adaptation laws in the algorithm to ensure robustness of the integrated controller. A simple two degrees of freedom (DOF) vehicle model is used to develop the control algorithm. To evaluate the control algorithm developed here, a nonlinear eight-DOF vehicle model along with a combined-slip tyre model and a single-point preview driver model are used. Control commands are executed through correction steering angle on front wheels and braking torque applied on one of the four wheels. Simulation of a double lane change manoeuvre using Matlab^®/Simulink is used for evaluation of the control algorithm. Simulation results show that the integrated control algorithm can significantly enhance vehicle stability during emergency evasive manoeuvres on various road conditions ranging from dry asphalt to very slippery packed snow road surfaces.     

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。     

The Development and Implementation of Adaptive Semi-Active Suspension Control*

Using adjustable shock absorbers within vehicle suspension systems, it is possible to improve ride comfort significantly when a control strategy is applied based on the so-called skyhook principle. However, the drawback is a poorly damped wheel-hop mode which makes the road holding ability worse. Using adaptive semi-active suspension control based on the tire load variations as introduced in this paper, the trade-off between road holding and ride comfort can be relaxed. Implementation of adaptive skyhook control requires the determination of a number of important and difficult to measure states of the vehicle. This can either be accomplished by several sensors and filters or by a state estimator in combination with less sensors and an internal model of the vehicle. Both methods are discussed. Finally some preliminary test results are discussed.     

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.     

基于免疫算法的汽车主动悬架控制研究

应用免疫算法理论,以车身垂直加速度、悬架动行程和车轮动载为控制目标,设计了基于汽车1/4模型的主动悬架控制策略。该算法利用信息熵作为评价抗体亲和力的指标,具有多样识别能力、强鲁棒性和免疫记忆功能。仿真结果表明,基于免疫控制器的主动悬架对汽车的平顺性和操纵稳定性有较明显的改善。