空气悬架SIMPACK与MATLAB联合仿真研究

利用虚拟样机技术建立了基于多体动力学软件SIMPACK的空气悬架客车模型,并基于神经元自适应控制理论在MATLAB中设计了神经元自适应控制器。通过SIMPACK中的路面编辑器建立了脉冲输入以及随机输入两种路面模型,进行了SIMPACK动力学模型与MATLAB控制策略的联合仿真研究。仿真结果表明,由车辆虚拟样机模型和神经元自适应控制策略组成的空气悬架系统,相比于被动悬架系统,有效降低了车身垂直振动加速度响应,抑制了车身姿态变化,改善了客车的行驶平顺性和乘坐舒适性。     

车辆主动悬架自适应LQG控制策略研究

针对车辆主动悬架的结构原理,建立了其动力学模型。在分析车辆主动悬架状态方程具有时变性的基础上,提出了自适应LQG主动悬架控制策略,通过自适应控制模型能够实现对车辆悬架时变参数和扰动输入参数的辨识。结合LQG控制性能指标函数,在确立簧载质量垂直加速度、悬架动行程和轮胎动行程的加权系数后,通过采用扩展自回归滑动平均模型进行悬架时变参数辨识,实现了主动悬架的自适应LQG控制。仿真结果表明自适应LQG控制策略优于LQG控制,较好地改善了车辆的平顺性。     

多变量主动悬架系统的一种自适应神经元控制策略

研究了车辆主动悬架这个多变量不确定系统的自适应控制问题。提出了一种新型的单神经元多变量控制器。给出一种综合误差的概念,将综合误差与传统的单神经元控制器相结合,得到一种基于综合误差理论的单神经元控制器,它可以同时直接调控被控对象的多输出变量。将该控制方法应用于1/4主动悬架系统,采用二次型性能指标对控制器参数进行了优化设计。研究了在不同的悬架参数及随机路面输入情况下控制器的自适应性能,并与被动悬架及传统神经元控制的主动悬架进行了性能对比。仿真结果表明,所提出的控制器可使车辆获得更为优良的综合减振性能,可显著改善平顺性,是一种简单有效且鲁棒性较好的自适应控制器。该控制方法为主动悬架及类似的多变量不确定系统的控制提供了一种可能的简捷有效的新途径。     

汽车主动悬架的自适应控制研究

主要对汽车主动悬架自适应系统进行研究。根据悬架系统的模型,参数往往不确定,路面激励未知且可变,对主动悬架的非线性性能特点进行研究。采用增益调度控制、模型参考自适应控制和自校正控制等几类自适应控制策略应用于主动悬架的主动控制系统。通过自校正控制自适应系统,按照路面行驶工况进行最优控制,通过计算机对电液系统的阻尼、弹力和水平位置等进行调节,使悬架系统对不同运行工况具有最大程度的适应能力。确保主动悬架性能满足车辆行驶稳定性能与乘坐舒适性,实现对悬架的自我优化控制。     

基于模糊控制的车辆主动悬架仿真研究

以二自由度车辆主动悬架模型为研究对象,基于车辆动力学理论,建立主动悬架系统的动力学方程和路面输入模型方程,并以悬架动挠度为控制目标设计模糊控制器。在Matlab/Simulink里建立二自由度主动悬架系统模型和随机路面激励模型,结合模糊控制器进行仿真分析。结果表明,相对被动悬架而言采用以悬架动挠度为控制目标的模糊控制策略的主动悬架能有效地抑制车辆振动,提高车辆的乘坐舒适性和安全性。     

车辆主动悬架控制器的仿真设计

建立了基于1/4车辆动力学和单轮路面输入模型,应用最优控制理论进行车辆主动悬架的线性二次型最优(LQC)控制器的设计,并运用MATLAB/SIMULINK软件进行路面输入和1/4车辆仿真分析。仿真结果表明采用LQG控制方法的主动悬架可以较好地改善车辆的行驶平顺性和乘坐舒适性。     

车辆主动悬架自适应模糊滑模控制研究

针对主动悬架系统具有的非线性和不确定性,结合滑模控制的鲁棒性和模糊控制的优势,建立自适应模糊滑模控制策略。确定滑模切换面参数,应用切换控制方法和函数逼近技术改善滑模运动的动态品质,并利用模糊语言达到控制悬架振动的效果。以车辆1/4主动悬架动力学模型为对象进行仿真,结果显示,与传统的模糊控制相比,自适应模糊滑模控制能有效地改善路面变化对悬架的影响。     

一种用于1/2汽车半主动悬架的模糊PID控制器

设计了一种用于1/2车体四自由度的液压半主动悬架的参数自整定模糊PID控制器,利用模糊控制规则对PID参数进行在线修改.应用MATLAB/Simulink控制系统仿真软件,以正弦信号路面、脉冲信号路面和C级路面三种典型路面作为输入信号对该半主动悬架模型进行计算机仿真,仿真结果表明具有模糊PID控制器的半主动悬架在提高车辆乘坐的舒适性方面明显优于被动悬架和单纯的模糊控制悬架,具有较好的自适应能力.     

车辆座椅悬架自适应模糊PID控制及仿真

为提高车辆座椅悬架减振性能,建立了简化的三自由度车辆座椅悬架模型,结合模糊控制与PID控制理论提出了座椅悬架自适应模糊PID控制方法。该方法中以座椅垂直振动速度的误差为控制参量设计了PID控制器,将座椅垂直振动速度误差及误差变化率作为模糊控制器的输入变量,利用模糊控制规则对PID控制器参数进行在线自调整。以C级路面白噪声随机信号为输入,利用MATLAB/Simulink对自适应模糊PID控制器进行了仿真。结果表明:相对于不加控制和PID控制的座椅悬架系统,自适应模糊PID控制方法可以明显改善座椅质心处的垂直振动加速度。     

交叉变轮距车辆磁流变悬架系统的优化设计

基于不同农作物种植行距不同以及生长高度不同而设计的高地隙交叉变轮距车辆底盘,对其悬架系统的设计与优化开展研究.首先,建立了磁流变阻尼器阻尼可控悬架系统的Bouc-wen 2自由度动力学模型,并分析了悬架系统对路面不平度输入的振动响应,得到了基于车辆平安性和悬架动挠度对路面不平度输入的振动响应均方值表达式;其次,以车身质量和路面激励为负载对刚性车架体进行疲劳分析,设计了柔性车架体;最后,分析了车身阻尼比、车身质量与车轮质量比、车轮刚度与悬架刚度比对车辆平安性的影响,确定了悬架系统的最优设计参数.在此基础上,建立磁流变阻尼器悬架系统PID模糊控制策略,通过仿真分析验证了参数设计的合理性和控制策略的有效性.     

履带车辆悬挂参数变化对悬挂特性影响分析

通过确定实际履带车辆的简化条件,建立了二自由度车辆悬挂系统模型,得出了车身加速度、悬挂动行程、负重轮相对动载荷对路面输入的幅频特性,分析了悬挂刚度、阻尼系数、负重轮胶圈刚度和非悬置质量等参数变化对悬挂传递特性的影响.结果表明,在进行车辆悬挂系统设计和振动控制时,必须考虑悬挂系统参数的匹配问题和参数变化对振动控制的影响.     

Optimization of suspension parameters to improve impact harshness of road vehicles

This paper illustrates the development and implementation of a parameter optimization methodology to improve impact harshness (IH) of road vehicles. A full ADAMS model of a small commercial vehicle is used as the IH test vehicle. The methodology involves the use of design of experiments methods together with response surface methodology. Significant design parameters affecting IH of the vehicle are first determined by the screening experiments. Once the critical parameters are identified, they are optimized to achieve improvement in the IH by constructing response surface. The optimization results indicate that the selected suspension parameters are capable of improving IH performance of the full vehicle ADAMS model by minimizing longitudinal and vertical acceleration responses. The results also show that considerable improvement can be obtained by using the proposed parameter optimization methodology.     

Adaptive backstepping-based tracking control design for nonlinear active suspension system with parameter uncertainties and safety constraints

This paper proposes a novel constraint adaptive backstepping based tracking controller for nonlinear active suspension system with parameter uncertainties and safety constraints. By introducing the virtual control input and reference trajectories, the adaptive control law is developed to stabilize both of the vertical and pitch motions of vehicle body using backstepping technique and Lyapunov stability theory, and further to track the predefined reference trajectories within a finite time, which not only ensure the safety performance requirements, but also achieve improvements in riding comfort and handling stability of vehicle active suspension system. Next, the stability analysis on zero dynamics error system is conducted to ensure that all the safety performance indicators are all bounded and the corresponding upper bounds are estimable. Finally, a numerical simulation is provided to verify the effectiveness of the proposed controller and to address the comparability between the classical Barrier–Lyapunov Function based adaptive tracking controller and the proposed controller.     

Adaptive control of nonlinear uncertain active suspension systems with prescribed performance

This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes.     

OPTIMIZING DESIGN OF MECHANICAL SELF-CENTERING DEVICE FOR SUSPENSION HEIGHT

Firstly, in view of the respective defects of existing self-centering devices for vehicle suspension height, the design scheme of the proposed mechanical self-centering device for suspension height is described. Taking the rear suspension of a certain light bus as a research example, the structures and parameters of the novel device are designed and ascertained. Then, the road excitation models, the performance evaluation indexes and the half-vehicle model are built, the simulation outputs of time and frequency domain are obtained with the road excitations of random and pulse by using MATLAB/Simulink software. So the main characteristics of the self-centering suspension are presented preliminarily. Finally, a multi-objective parameter design optimization model for the self-centering device is built by weighted sum approach, and optimal solution is obtained by adopting complex approach. The relevant choosing-type parameters for self-centering device components are deduced by using discrete variable optimal method, and the optimal results are verified and analyzed. So the performance potentials of the self-centering device are exerted fully in condition of ensuring overall suspension performances.     

基于单神经元PID的车辆主动悬架最优自适应控制

为克服路面一车辆系统中存在的动态行为不确定性，针对1/4车辆主动悬架系统，设计了一个基于单神经元PID的自适应控制器，并采用二次型性能指标对控制器参数进行了优化设计。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特性。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，且鲁棒性好，对模型参数的变化具有一定的适应性，便于实现和应用。