Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system

In this paper, a magneto-rheological (MR) damper-based semi-active controller for vehicle suspension is developed. This system consists of a linear quadratic Gauss (LQG) controller as the system controller and an adaptive neuro-fuzzy inference system (ANFIS) inverse model as the damper controller. First, a modified Bouc–Wen model is proposed to characterise the forward dynamic characteristics of the MR damper based on the experimental data. Then, an inverse MR damper model is built using ANFIS technique to determine the input current so as to gain the desired damping force. Finally, a quarter-car suspension model together with the MR damper is set up, and a semi-active controller composed of the LQG controller and the ANFIS inverse model is designed. Simulation results demonstrate that the desired force can be accurately tracked using the ANFIS technique and the semi-active controller can achieve competitive performance as that of active suspension.     

Semi-active H∞ control of high-speed railway vehicle suspension with magnetorheological dampers

In this paper, semi-active H∞ control with magnetorheological (MR) dampers for railway vehicle suspension systems to improve the lateral ride quality is investigated. The proposed semi-active controller is composed of a H∞ controller as the system controller and an adaptive neuro-fuzzy inference system (ANFIS) inverse MR damper model as the damper controller. First, a 17-degree-of-freedom model for a full-scale railway vehicle is developed and the random track irregularities are modelled. Then a modified Bouc–Wen model is built to characterise the forward dynamic characteristics of the MR damper and an inverse MR damper model is built with the ANFIS technique. Furthermore, a H∞ controller composed of a yaw motion controller and a rolling pendulum motion (lateral motion+roll motion) controller is established. By integrating the H∞ controller with the ANFIS inverse model, a semi-active H∞ controller for the railway vehicle is finally proposed. Simulation results indicate that the proposed semi-active suspension system possesses better attenuation ability for the vibrations of the car body than the passive suspension system.     

A novel neuro-fuzzy controller to enhance the performance of vehicle semi-active suspension systems

This paper proposes a neuro-fuzzy (NF) strategy to implement semi-active suspension in passenger vehicles. The proposed method is composed of two parts: a NF controller (NFC), to establish an efficient controller strategy to improve ride comfort and road handling (RCH), and an inverse mapping to estimate the semi-active suspension current. To effectively estimate the current needed to control the semi-active damper, an inverse mapping based on neural network, modified back-propagation (MBP) is presented. The inverse mapping is incorporated into the FC to enhance RCH. Given the relative velocity between the mass and the base and also the absolute acceleration of the mass, the FC computes the optimum damping coefficient. The fuzzy logic rules are extracted based on expert knowledge encapsulated in skyhook and groundhook. A quarter-car model was adopted for the purpose of simulating and experimenting with the proposed NFC. To verify the performance of the FC, two sets of results are reported. First, an experimental analysis was performed to demonstrate the effectiveness of the FC in comparison with the benchmark skyhook and Rakheja–Sankar controllers. Furthermore, a random input was considered to examine the robustness of the NFC in comparison with the other adopted controllers. It was shown that the developed NFC control enhances the performance of the quarter-car system significantly, in terms of both ride comfort and handling characteristics. Second, four FCs with the same control strategies were implemented on a full-vehicle model to demonstrate the effectiveness of the proposed control strategy in reducing the propensity to rollover. It was concluded that the developed FC enhances the RHC and also has the potential to increase the stability of vehicles.     

State observer-based sliding mode control for semi-active hydro-pneumatic suspension

This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.     

考虑发动机与人椅系统的液压半主动悬架振动控制研究

在研究1/2车辆模糊控制半主动悬架的基础上,加入了发动机和人椅系统等因素,建立了"车椅人"1/4车体4自由度车辆动力学模型,设计了用于该车体的参数自整定的模糊PID控制器,并应用MATLAB/SIMULINK软件进行了仿真研究.结果表明,高频恒定的发动机激励对座椅加速度影响较小,模糊PID控制器比模糊控制器具有更强的自...     

基于磁流变阻尼器的半主动车辆座椅悬架模糊控制研究

设计基于磁流变阻尼器的半主动车辆座椅悬架系统的模糊控制器。用ADAMS对系统建立三维多刚体动力学模型,用MATLAB设计系统模糊控制器,并联合两者对整个系统进行仿真。仿真和台架试验结果表明,模糊控制策略能使该系统较好抑制垂直振动加速度,提高乘坐的舒适性。     

汽车半主动悬架的模型参考自适应控制

在1／4车辆动力学模型的基础上，基于李雅普诺夫稳定性理论，以天棚阻尼半主动悬架为参考模型，设计了半主动悬架模型参考自适应控制器。自适应控制器包括可调前置控制器和状态反馈控制器两个部分。推导了自适应控制律与相应的约束条件。仿真结果表明：该控制器对于模型参数的不确定性具有良好的鲁棒特性。自适应控制器不仅明显降低了车身加速度，提高了平顺性，同时也使汽车的行驶安全性获得了改善，悬架动变形稍有增大。     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

DSP-based self-organising fuzzy controller for active suspension systems

This study proposed a self-organising fuzzy controller (SOFC) for controlling an active suspension system to evaluate its control performance. During the control process, the SOFC continually updated the learning strategy in the form of fuzzy rules. The fuzzy rule table of this SOFC could be initially set to zero. This not only overcame the difficulty in finding appropriate membership functions and control rules for designing a fuzzy controller, but also solved the database problem where the fuzzy rules of a fuzzy controller, once determined, remained fixed and could not suitably regulate them in real time to optimise the dynamic response of the system required to gain the desired control performance. To demonstrate the applicability of the proposed SOFC for active suspension systems, a quarter-car hydraulic-servo suspension system was designed and constructed to evaluate the feasibility of active suspension control. Additionally, to conform to real-time application requirements in the vehicular industry, the SOFC was implemented with a digital signal processor to control the hydraulic-servo suspension system so that the control performance could be determined. The SOFC has shown a better control performance in suppressing the vibration amplitude of the vehicle body for enhancing the structural safety of the vehicle and increasing the life of the suspension system. It also effectively suppressed the amplitude of the vehicle body acceleration and reduced the tire deflection for improving the ride and the handling quality of a vehicle better than a passive control, as verified in experimental results.     

基于虚拟样机技术的空气悬架客车平顺性仿真研究

针对某中型客车，利用ADAMS软件建立了空气悬架客车动力学仿真模型，并进行了随机路面输入及三角凸台路面输入的平顺性仿真分析。仿真结果与试验数据对比表明，在测量点处的最大加速度、自功率谱密度及其对应的频率点比较接近，说明所建立的仿真模型是准确的。对影响客车平顺性的2个参数在ADAMS中进行了优化。     

Generalized magnetorheological (MR) damper model and its application in semi-active control of vehicle suspension system

In this paper, analytical characterization of the magneto-rheological (MR) damper is done using a new modified algebraic model. Algebraic model is also more preferable because of its low computational expenses compared to differential Bouc-Wen’s model which is highly computationally demanding. This model along with the obtained model parameters is used as a semi-active suspension device in a quarter car model and the stationary response of the vehicle traversing on a rough road is obtained. The control part consists of two nested controllers. One of them is the system controller which generates the desired damping force and the other is the damper controller which adjusts the voltage level to MR damper so as to track the desired damping force. For the system controller a model reference skyhook Sliding Mode Controller (SMC) is used and for the damper controller a continuous state algorithm is built to determine the input voltage so as to gain the desired damping force. The analytical model is subsequently used in the quarter car vehicle model and the vehicular responses are studied. A simulation study is performed to prove the effectiveness and robustness of the semi-active control approach. Results show that the semi-active controller can achieve compatible performance as that of active suspension controller except for a little deterioration.     

Development of Preview Active Suspension Control System and Performance Limit Analysis by Trajectory Optimization

The main role of the suspension system is to achieve ride comfort by reducing vibrations generated by the road roughness. The active damper is getting much attention due to its reduced cost and ability to enhance ride comfort especially when the road ahead is measurable by an environment sensor. In this study a preview active suspension control system was developed in order to improve ride comfort when the vehicle is passing over a speed bump. The control system consists of a feedback controller based on the skyhook logic and a feedforward controller for canceling out the road disturbance. The performance limit for the active suspension control system was computed via trajectory optimization to provide a measure against which to compare and validate the performance of the developed controller. The simulation results indicated that the controller of this study could enhance ride comfort significantly over the active suspension control system employing only the skyhook feedback control logic. Also the developed controller, by displaying similar control pattern as the trajectory optimization during significant time portions, proved that its control policy is legitimate.     

基于ADAMS/CAR二次开发模块研究汽车平顺性

以ADAMS／CAR二次开发模块为平台，建立了国产某小型客车虚拟样机的多体系统动力学仿真模型。按照国家有关整车平顺性的试验评价方法和标准，进行了整车平顺性脉冲输入和随机输入行驶仿真试验分析。对比实车测试结果，主要评价指标加权振级的最大仿真误差小于5％，即仿真结果具有较高的可信度，说明在车辆设计阶段，利用此二次开发模块可对其平顺性进行有效的分析和评估。     

铰接式自卸车悬架系统动力学建模与仿真

建立了一个铰接式自卸车9自由度线性动力学模型，并用Matlab语言编写了基于Simpson算法的仿真程序，来仿真它对路面随机输入的响应，用以计算数种工况下座椅总加权加速度均方根值。仿真结果表明，所建模型能较好地吻合座椅的实际振动，不仅可以正确评估系统的平顺性性能，还可为新型铰接车辆悬架系统、橡胶弹簧的优化设计提供理论和方法支持。     

基于磁流变阻尼器的发动机振动模糊PID控制

在对发动机激振力及动力学模型分析的基础上,提出一种模糊PID控制方法,设计出了基于磁流变阻尼器的发动机振动控制的半主动模糊PID控制器,并运用MATLAB/Simulink对隔振控制系统进行了对比仿真.仿真结果显示,与橡胶隔振垫和PID控制相比,采用模糊PID控制的磁流变阻尼器的发动机有更明显的隔振效果,表明了磁流变阻尼器在汽车发动机上运用的可行性.     

Structured H2 Optimization of Vehicle Suspensions Based on Multi-Wheel Models

Summary Various control techniques, especially LQG optimal control, have been applied to the design of active and semi-active vehicle suspensions over the past several decades. However passive suspensions remain dominant in the automotive marketplace because they are simple, reliable, and inexpensive. The force generated by a passive suspension at a given wheel can depend only on the relative displacement and velocity at that wheel, and the suspension parameters for the left and right wheels are usually required to be equal. Therefore, a passive vehicle suspension can be viewed as a decentralized feedback controller with constraints to guarantee suspension symmetry. In this paper, we cast the optimization of passive vehicle suspensions as structure-constrained LQG/H2 optimal control problems. Correlated road random excitations are taken as the disturbance inputs; ride comfort, road handling, suspension travel, and vehicle-body attitude are included in the cost outputs. We derive a set of necessary conditions for optimality and then develop a gradient-based method to efficiently solve the structure-constrained H2 optimization problem. An eight-DOF four-wheel-vehicle model is studied as an example to illustrate application of the procedure, which is useful for design of both passive suspensions and active suspensions with controller-structure constraints.     

汽车磁流变半主动悬架的控制研究

为了改善汽车的乘坐舒适性和行驶安全性,提出了一种汽车磁流变半主动悬架的控制策略。首先,设计了磁流变减振器的工作模式,通过试验获得了其速度特性和力学特性,建立了磁流变减振器的数学模型;其次,建立了带磁流变减振器的二自由度车辆简化模型及其参数表;最后,基于双环控制理论,设计了一种控制系统,其外环产生理想的结构阻尼力,内环调节电流驱动器的电流,以使磁流变减振器实时地产生控制阻尼力。仿真结果表明:以磁流变减振器为基础,通过半主动控制技术,悬架系统的振动动态性能得到了有效的控制。     

Nonlinear adaptive sliding mode control for vehicle handling improvement via steer-by-wire

This paper proposes a nonlinear adaptive sliding mode control that aims to improve vehicle handling through a Steer-By-Wire system. The designed sliding mode control, which is insensitive to system uncertainties, offers an adaptive sliding gain to eliminate the precise determination of the bound of uncertainties. The sliding gain value is calculated using a simple adaptation algorithm that does not require extensive computational load. Achieving the improved handling characteristics requires both accurate state estimation and well-controlled steering inputs from the Steer-By-Wire system. A second order sliding mode observer provides accurate estimation of lateral and longitudinal velocities while the driver steering angle and yaw rate are available from the automotive sensors. A complete stability analysis based on Lyapunov theory has been presented to guarantee closed loop stability. The simulation results confirmed that the proposed adaptive robust controller not only improves vehicle handling performance but also reduces the chattering problem in the presence of uncertainties in tire cornering stiffness.     

重型牵引车平顺性建模与仿真分析

利用模板化建模技术,在MSC.ADAMS/Car软件中建立了重型牵引车整车动力学仿真模型,除轮胎外的全部原始数据均由Pro/E中导入,提高了建模精度。在通过试车场的路面脉冲输入试验对整车数字模型进行验证的基础上,进行整车随机输入平顺性仿真分析,其结果与样车道路试验基本相符,实现了在汽车工程设计阶段对其平顺性进行预测和控制的目标。