Finite Frequency Fuzzy H∞Control for Uncertain Active Suspension Systems With Sensor Failure

This paper investigates the problem of finite frequency fuzzy H_∞ control for uncertain active vehicle suspension systems, in which sensor failure is taken into account. TakagiSugeno(T-S) fuzzy model is established for considered suspension systems. In order to describe the sensor fault effectively, a corresponding model is introduced. A vital performance index,H_∞ performance, is utilized to measure the drive comfort. In the framework of Kalman-Yakubovich-Popov theory, the H_∞ norm from external perturbation to controlled output is optimized effectively in the frequency domain of 4 Hz-8 Hz to enhance ride comfort level. Meanwhile, three suspension constrained requirements, i.e., ride comfort level, manipulation stability,suspension deflection are also guaranteed. Furthermore, sufficient conditions are developed to design a fuzzy controller to guarantee the desired performance of active suspension systems. Finally, the proposed control scheme is applied to a quarter-vehicle active suspension, and simulation results are given to illustrate the effectiveness of the proposed approach.

Fuzzy Control of Model Travel Tracking for Vehicle Semi-Active Suspension

The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is designed, in which the sus pension travel output of the adaptive LQG control system is taken as the tracking objective. The simulation results prove that the suspension travel and vertical acceleration can be tracked simultaneously with the simple fuzzy controller, and the tracking effect of fuzzy control is better than that of the PID controller.

Active suspension with optimal control based on a full vehicle model

The 7-DOF model of a full vehicle with an active suspension is developed in this paper.The model is written into the state equation style.Actuator forces are treated as inputs in the state equations.Based on the basic optimal control theory,the optimal gains for the control system are figured out.So an optimal controller is developed and implemented using Matlab/Simulink,where the Riccati equation with coupling terms is deduced using the Hamilton equation.The all state feedback is chosen for the controller.The gains for all vehicle variables are traded off so that majority of indexes were up to optimal.The active suspension with optimal control is simulated in frequency domain and time domain separately,and compared with a passive suspension.Throughout all the simulation results,the optimal controller developed in this paper works well in the majority of instances.In all,the comfort and ride performance of the vehicle are improved under the active suspension with optimal control.

A Study of Electric Vehicle Suspension Control System Based on an Improved Half-vehicle Model

An improved half-vehicle model has been proposed for active suspension control systems, in contrast to existing models, it allows to explore the nature of the effect of vehicle speed changes by introducing a state vector of vehicle pitch angle. Three control strategies of linear quadratic control （LQ）, improved LQ （ILQ） and wheelbase preview LQ （WLQ） have been implemented into the proposed model. ILQ has integrated an additional control parameter into LQ by concerning the correlation between acceleration values and their corresponding pitch angles. Simulation results have showed the effectiveness of the proposed model in terms of LQ, ILQ and WLQ control strategies.

Research on Dynamic Model's Building of Active Magnetic Suspension Systems

An experimental method is introduced in this paper to build the dynamics of AMSS (the active magnetic suspension system), which doesn’t depend on system’s physical parameters. The rotor can be reliably suspended under the unit feedback control system designed with the primary dynamic model obtained. Online identification in frequency domain is processed to give the precise model. Comparisons show that the experimental method is much closer to the precise model than the theoretic method based on magnetic circuit law. So this experimental method is a good choice to build the primary dynamic model of AMSS.

Computer simulation of active suspension based on the full-vehicle model

Abstract: The current method to solve the problem of active suspension control for a vehicle is often dealt with a quarter-car or half-car model. But it is not enough to use this kind of model for practical applications. In this paper, based on considering the influence of factors such as, seat and passengers, a MDOF(multi-degree-of-freedom) model describing the vehicle motion is set up. The MODF model, which is 8DOF of four independent suspensions and four wheel tracks, is more applicable by comparison of its analysis result with some conventional vehicle models. Therefore, it is more suitable to use the 8DOF full-car model than a conventional 4DOF half-car model in the active control design for car vibration. Based on the derived 8DOF model, a controller is designed by using LQ (linear quadratic ) control theory, and the appropriate control scheme is selected by testing various performance indexes. Computer simulation is carried out for a passenger car running on a road with step disturbance and random road disturbance expressed by Power Spectral Density (PSD). Vibrations corresponding to ride comfort are derived under the foregoing road disturbances. The response results for uncontrolled and controlled system are compared. The response of vehicle vibration is greatly suppressed and quickly damped, which testifies the effect of the active suspension. The results achieved for various controllers are compared to investigate the influence of different control schemes on the control effect.

Robust Active Suspension Design Subject to Vehicle Inertial Parameter Variations

This paper presents an approach in designing a robust controller for vehicle suspensions considering changes in vehicle inertial properties. A four-degree-of-freedom half-car model with active suspension is studied in this paper, and three main performance requirements are considered. Among these requirements, the ride comfort performance is optimized by minimizing the Ho~ norm of the transfer function from the road disturbance to the sprung mass acceleration, while the road holding performance and the suspension deflection limitation are guaranteed by constraining the generalized H2 （GH2） norms of the transfer functions from the road disturbance to the dynamic tyre load and the suspension deflection to be less than their hard limits, respectively. At the same time, the controller saturation problem is considered by constraining its peak response output to be less than a given limit using the GH2 norm as well. By solving the finite number of linear matrix inequalities （LMIs） with the minimization optimization procedure, the controller gains, which are dependent on the time-varying inertial parameters, can be obtained. Numerical simulations on both frequency and bump responses show that the designed parameter-dependent controller can achieve better active suspension performance compared with the passive suspension in spite of the variations of inertial parameters.

A study of active suspension based on full DOF vehicle model

This paper presents a MDOF (multi-degree-of-freedom) model to describe the vehicle motion, considering influences of factors such as, seat and passengers. The model is four-independent-suspension and four-wheel-track with 8DOF, and has proved more appropriate compared with some conventional vehicle models. Based on the derived 8DOF model, a controller for this model is designed by the use of H∞ control theory, Furthermore the appropriate control scheme is selected by testing various performance indexes. The study shows that satisfying results can be obtained by using an appropriate vehicle model, even if a low order controller and a general control strategy are adopted.

Semi-active model predictive control for 3rd generation benchmark problem using smart dampers

A semi-active strategy for model predictive control （MPC）, in which magneto-rheological dampers are used as an actuator, is presented for use in reducing the nonlinear seismic response of high-rise buildings. A multi-step predictive model is developed to estimate the seismic performance of high-rise buildings, taking into account of the effects of nonlinearity, time-variability, model mismatching, and disturbances and uncertainty of controlled system parameters by the predicted error feedback in the multi-step predictive model. Based on the predictive model, a Kalman-Bucy observer suitable for semi-active strategy is proposed to estimate the state vector from the acceleration and semi-active control force feedback. The main advantage of the proposed strategy is its inherent stability, simplicity, on-line real-time operation, and the ability to handle nonlinearity, uncertainty, and time-variability properties of structures. Numerical simulation of the nonlinear seismic responses of a controlled 20-story benchmark building is carried out, and the simulation results are compared to those of other control systems. The results show that the developed semi-active strategy can efficiently reduce the nonlinear seismic response of high-rise buildings.

基于超螺旋二阶滑膜的汽车主动悬架控制方法研究

汽车悬架的控制效果直接影响汽车的稳定性和舒适性,针对一阶滑模控制在主动悬架控制中存在的抖振和控制精度问题,基于汽车二自由度1/4主动悬架模型,提出了一种基于超螺旋二阶滑模控制的汽车主动悬架控制方法。在控制器前端串联一个负加速度反馈回路来调节悬架性能,并使用扩展的超螺旋观测器实时补偿系统的未知内部动态。为了验证控制方法的可行性,通过仿真进行对比分析。仿真结果表明,相比于一阶滑膜控制,该方法解决了悬架未知非线性动态的多目标控制问题,能更有效地改善汽车稳定性和舒适性。

基于EGA优化的农用UTV半主动悬架最优控制

针对UTV在恶劣路面行驶引起的车辆振动,以某款农用UTV悬架系统为对象,建立包含俯仰的四自由度(4-DOF)半车半主动悬架动力学模型,并提出一种EGA-LQR复合控制策略,设计满足物理约束的悬架系统自适应最优控制器。利用EGA算法的全局寻优与快速收敛特性,对LQR最优控制器的权重矩阵寻优,输出悬架系统最优控制阻尼力。在Matlab/Simulink中搭建UTV的路面与悬架模型进行时域仿真,仿真分析结果表明,EGA-LQR控制显著减小了车体质心垂向振动加速度、车体俯仰角加速度、前后轮动位移以及前后悬架动行程的均方根值,有效保证了UTV在农田路面下行驶的舒适性与安全性。

有源缓冲型逆变器功率解耦技术研究

为实现单级单相升压逆变并能有效抑制直流侧二次纹波电流,提出一种带有源缓冲的电流型逆变器电路拓扑,研究该逆变器的6种电路模态并提出其两模态调制策略和三模态调制策略,设计2种调制策略下的模型预测控制策略,提供主电路参数设计准则。从储能电感电流的最大脉动量与二次纹波含量两方面对2种调制策略进行对比分析,得出了三模态调制策略具有更好纹波抑制效果的结论。对2种调制策略下的逆变器进行仿真分析,仿真结果表明,三模态调制下电路的输出电压总谐波失真率、电感电流相对脉动量与二倍频含量均低于两模态调制下的数据。设计并搭建500VA 48VDC/220V50HzAC有源缓冲型单级单相升压逆变器实验装置,给出了三模态调制下基于模型预测控制的逆变器实验波形,进一步证实了所提研究方案在实现单级升压逆变的同时具有二次纹波抑制能力。

机载悬臂体结构的主被动联合抑振

为解决机载悬臂体结构在长悬臂梁挂载状态下的全频域减振问题,提出了一种基于耦合级联的主被动联合抑振模型及控制优化方法。通过在远端头体连接处加装机械手进行抑振。机械手采用主动抑振减小低频正弦振动,其上串联的被动减振器降低高频随机振动。在对头体连接处进行负载振动等效的基础上,提出了基于减振因子和总均方根加速度的主被动综合减振率的计算方法,并根据高低频切换频率(10 Hz)和综合减振率(40%)等指标得到机械手主被动减振参数。通过耦合级联的方法解决了机械手在主动抑振过程中悬臂体、机械手及其被动减振器的串联耦合问题,从而构建串联耦合作用下的机械手全伺服系统模型。最后采用伺服优化、抑振前馈和极点配置等综合优化算法提升机械手的动态性能。根据仿真结果,机械手的主动抑振带宽和综合减振率均满足抑振需求,为全频域环境载荷作用下机载挂载的减振问题提供了一种新的方法。

主动悬架识别路面扰动反馈最优控制策略研究

针对现有主动悬架在应用最优控制时缺乏路面扰动识别内容的问题,提出一种识别路面扰动反馈的最优控制器。该控制器在传统系统状态反馈最优控制的基础上引入扰动反馈项,并通过粒子群算法优化加权系数,同时采用直线电机作为作动器。考虑到路面不平度与系统状态响应获取存在先后顺序,采用开环带有外部输入的非线性自回归(Nonlinear Auto-regressive Model with Exogenous Inputs,NARX)神经网络预测与逆模型相结合的方法来识别路面不平度。神经网络离线训练在线识别,识别模块实时将结果传输给控制器。在整车模型上对控制策略进行仿真。结果表明,粒子群优化使平顺性指标显著改善;采用的路面识别方法可有效提高识别的精确性;与不识别扰动控制相比,本策略可有效降低悬架动挠度的恶化,并改善整体控制效果。

膝-踝-趾动力型假肢解耦控制研究

针对膝-踝-趾动力型假肢系统的强耦合性,导致系统控制效果不理想等问题,本文设计控制法则分解法解耦器对系统进行解耦,降低耦合度,提高控制效果。利用拉格朗日方程建立了膝-踝-趾动力型假肢系统支撑末期的动力学模型,此模型的耦合度为1.22,耦合性较强,需要进行解耦;基于控制法则分解法设计模型解耦器,以此简化假肢系统,将耦合度强的系统简化为膝、踝、趾独立控制的模型;基于自适应迭代学习设计控制器,对解耦前后三自由度假肢系统的各关节进行控制。结果表明:此解耦器可以将假肢模型简化为3个单输入、单输出的系统,同时降低关节间的耦合度,加快系统的收敛速度,与解耦前的控制效果相比,解耦后系统收敛误差明显减小。本文为多关节假肢系统提供了模型简化方法,为实物样机控制提供理论验证。

基于实时力值跟踪及RCP的半主动悬架试验系统

为开展半主动智能车辆悬架控制策略方面的验证研究,提出一种可实现减振器实时力值跟踪监测和快速控制原型(Rapid Control Prototype,RCP)的汽车悬架实验平台。基于建立的1/4悬架动力学控制方程和传递函数,分析了悬架的输出特性;为模拟真实车辆悬架的动态输出特性和实时监测执行器的控制力输出特性,开发了可实现实时力值跟踪监测的麦弗逊式1/4汽车悬架实验平台。该实验平台一方面可以依托快速控制原型技术开展半主动悬架最佳控制算法的研究,另一方面还可以基于平台特有的执行器输出力实时跟踪监测功能,开展执行器不确定性半主动控制策略及执行器状态观测器可靠性检验等方面的研究;通过定电流开环实验检验半主动汽车悬架系统的有效性和可控性,通过闭环控制实验分别对半主动悬架系统在半主动智能控制策略验证和悬架执行器阻尼力跟踪估计方面的有效性。

基于改进LADRC的构网型储能调频控制策略研究

为提升高比例风电渗透下电力系统的频率稳定性,同时解决风储联合系统调频过程中参数间相互影响难以兼顾导致系统调频控制性能不佳的问题,提出一种基于改进型线性自抗扰控制策略(linear active disturbance rejection control,LADRC)的构网型(grid-forming,GFM)储能调频控制策略。首先,在传统应用LADRC对角频率进行快速控制的基础上,引入有功差额补偿,加速有功指令响应速度,消除参数互耦。同时,针对构网型储能调频控制策略参数影响规律,分析了角频率和参考功率至输出功率的小信号模型,推导控制环节传递函数,实现对系统调频性能优化。最后在Matlab/Simulink仿真平台上搭建风储联合系统仿真模型,对不同控制策略在不同工况下电网频率和储能出力的变化情况进行对比分析。结果表明,所提控制策略有效提升复杂工况下风储联合系统对电网频率的支撑能力。

汽车主动悬架系统建模及其控制策略研究

介绍了一种主动悬架系统的建模 ,该系统是由液压作动器与一个普通弹簧串联后 ,再与被动阻尼器并联构成 ,其通常又被称作慢主动悬架。并应用SIMULINK语言仿真 。

基于ADAMS机械模型的车辆主动悬架控制策略与仿真

利用ADAMS软件建立了四分之一汽车主动悬架的机械模型,在机械模型的基础上生成车辆主动悬架系统的动力学方程,该方法解决了主动悬架数学模型建立的难题.使机械设计和控制设计共享同一虚拟车辆主动悬架模型,机械系统设计和控制系统设计协调一致.采用自适应模糊PID控制策略对悬架控制,实现了PID控制过程中参数的在线自整定,从而使系统的控制性能更加完善.利用ADAMS的Controls模块实现了ADAMS与MATLAB的联合仿真,仿真结果表明,采用自适应模糊PID控制策略是合理的、可行的,与被动悬架控制相比有效地降低了车身加速度、悬架动挠度和轮胎的相对动载荷,提高了汽车的乘坐舒适性和操纵稳定性.

基于模型预测的重型车辆侧翻主动控制

为解决重型车辆侧翻问题,提出基于模型预测的侧翻主动控制方法。通过车辆侧倾数学模型来预测车辆的侧翻趋势,从而实现对于车辆侧翻主动控制的实时性。以带有空气悬架的大型客车为例,结合空气弹簧的工作特性,设计主动控制策略,实现对车辆侧翻危险状态的主动控制。在车辆行驶速度80km/h、方向盘转角200°的情况下进行仿真试验,车辆左侧空气悬架的刚度上升了12.9%,右侧空气悬架的刚度下降了13.7%,车辆侧倾角稳定在3.9°。结果表明,基于模型预测的车辆侧翻主动控制系统能够及时调整左右空气悬架的刚度,提高重型车辆的侧翻控制能力,减少重型车辆侧翻事故的发生。