Genetic-based fuzzy control for half-car active suspension systems

In this paper, a fuzzy controller is designed for automotive active suspension systems. A half-car model is used in order to consider the pitch angle of the body and the coupling dynamics of front and rear wheels. It is assumed that the three measurements of body acceleration, front suspension deflection and rear suspension deflection are available. The fuzzy control rules are separately designed for each measurement. After the fuzzy control rules are determined, a genetic algorithm is applied to tune the membership functions of these control rules. To measure the performance of the designed genetic-based fuzzy active suspension system, three road disturbance models are designed to simulate actual road conditions. The performance of the designed system is evaluated with respect to these disturbance models, and it is shown that the designed active suspension system provides good performance in improving ride quality and maintaining vehicle maneuvrability. It is also shown that the designed active suspension system shows robust performance with system model uncertainties.     

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.      

Sliding mode neural network inference fuzzy logic control foractive suspension systems

In the automotive industry, suspension systems are designed to provide desirable vehicle ride and handling properties. This paper presents the development of a robust intelligent nonlinear controller for active suspension systems based on a comprehensive and realistic nonlinear model. The inherent complex nonlinear system model's structure, and the presence of parameter uncertainties, have increased the difficulties of applying conventional linear and nonlinear control techniques. Recently, the combination of sliding mode, fuzzy logic, and neural network methodologies has emerged as a promising technique for dealing with complex uncertain systems. In this paper, a sliding mode neural network inference fuzzy logic controller is designed for automotive suspension systems in order to enhance the ride and comfort. Extensive simulations are performed on a quarter-car model, and the results show that the proposed controller outperforms existing conventional controllers with regard to body acceleration, suspension deflection, and tire deflection     

Optimal ride height and pitch control for championship race cars

Car performance in championship auto racing is strongly influenced by aerodynamics, particularly ground effects aerodynamics. Vehicles employing this technology require careful control of ride height and unsprung mass pitch in order to be stable, perform properly and achieve maximum success on the racetrack. In the past, attempts for controlling these vehicle variables centred around employment of very stiff “suspension systems” so as to prevent aerodynamic load buildup, which occurs at high race velocities, from causing excessive suspension travel. Control of these variables, however, may require use of an active suspension system, coupled with a controller which can adjust the suspension system in such a way as to mask road surface disturbance and aerodynamic noise. In the present work, a controller is developed for such a vehicle/suspension combination using linear quadratic stochastic regulator theory. Vehicle road inputs are modelled as Gaussian white noise, and are nearly completely rejected by the controller. In addition, representative aerodynamic inputs are also well controlled so that vehicle outputs of unsprung mass pitch angle and centre of gravity height are held constant.     

Suspension system performance optimization with discrete design variables

Suspension systems on commercial vehicles have become an important feature meeting the requirements from costumers and legislation. The performance of the suspension system is often limited by available catalogue components. Additionally the suspension performance is restricted by the travel speed which highly influences the ride comfort. In this article a suspension system for an articulated dump truck is optimized in sense of reducing elapsed time for two specified duty cycles without violating a certain comfort threshold level. The comfort threshold level is here defined as a whole-body vibration level calculated by ISO 2631-1. A three-dimensional multibody dynamics simulation model is applied to evaluate the suspension performance. A non-gradient optimization routine is used to find the best possible combination of continuous and discrete design variables including the optimum operational speed without violating a set of side constraints. The result shows that the comfort level converges to the comfort threshold level. Thus it is shown that the operational speed and hence the operator input influences the ride comfort level. Three catalogue components are identified by the optimization routine together with a set of continuous design variables and two operational speeds one for each load case. Thus the work demonstrates handling of human factors in optimization of a mechanical system with discrete and continuous design variables.     

基于Backstepping 方法的全车液压主动悬挂最优控制设计

设计先进的悬挂系统是提高车辆性能的重要途径之一.本文针对并联式液压主动悬挂系统建立了较为详细的7自由度全车非线性模型,并根据其结构特点提出了线性二次型最优控制与Backstepping方法相结合的控制策略.仿真结果证明,利用该控制策略,主动悬挂系统既可以满足悬挂行程约束,又可以有效的提高乘坐舒适性;而且,与相同条件下的被动悬挂相比,车辆性能有明显改善.     

主动悬架控制技术研究

根据主动悬架控制理论,本文在MATLAB/Simulink上建立1/4主动悬架模型,设计LQG控制与模糊逻辑控制的主动悬架,并进行仿真研究。仿真结果表明,经过LQG控制和模糊控制的主动悬架相对于被动悬架,车辆的平顺性、乘坐舒适性有较大的改善,使主动悬架具有良好的综合性能。     

VIA(Virtual Interface Architecture)上的软件DSM系统实现和性能

在由高性能PC搭建的Linux机群系统上，传统的网络接口体系结构引入了巨大的软件处理开销，无法满足虚拟共享存储并行应用对通信带宽、延迟和进程间同步的需求．用户级网络接口标准——虚拟接口体系结构(Vilxual Interface Architecture，VIA)与传统的网络接口体系结构相比，在软件协议开销、通信关键路径上操作系统的干预程度、通信和计算的重叠程度以及实现零拷贝等方面，具有明显的优势．通过在传统网络通信接口和VIA通信接口上虚拟共享存储系统的性能对比，采用VIA网络接口体系结构可有效地提高虚拟共享存储系统的性能和可扩展性．     

基于遗传算法的磁浮列车悬浮控制参数优化

悬浮系统本质上是不稳定的,要通过设计控制器使得闭环系统稳定。对单铁悬浮控制模型,采用基于磁通反馈的间隙PID控制算法,通过合理选取控制参数可以达到良好的控制效果。为使悬浮控制器具有良好的跟踪特性同时保证磁浮列车的乘坐舒适性,需要限定悬浮系统闭环带宽。应用遗传算法进行控制参数优化设计,对基于ITAE的适应度函数进行改进,对不满足闭环系统带宽要求的个体进行惩罚,设计基于遗传算法的悬浮控制控制参数优化算法,并通过实例计算验证了算法的有效性。     

A New SSUKF Observer for Sliding Mode Force Tracking H∞ Control of Electrohydraulic Active Suspension

Compared to passive and semi‐active suspensions, active suspensions have the capacity to overcome the tradeoff design of vehicle ride comfort and handling performance. In this paper, a new control system with modified spherical simplex UKF (SSUKF) observer and sliding mode force tracker is proposed for electrohydraulic active suspensions. The estimated states obtained from the SSUKF observer are used to derive the mode energy of body motion and design the target demanded forces for suspension actuators. A sliding mode controller is presented to drive electrohydraulic actuators to track the demanded forces. Based on a robust H∞ control method, a new control strategy depending on body mode energy is proposed to restrict body motion. The performance comparisons between passive and active suspensions under three typical excitations are presented, and the obtained results indicate that the proposed control system can significantly depress body motion and decrease the mode energy to improve ride comfort and also effectively enhance the road hold abilities.     

非线性主动悬架系统自适应最优控制

针对非线性主动悬架系统多性能指标综合优化问题,提出一类自适应最优控制方法.首先,通过引入一阶低通滤波操作,利用系统输入输出构建结构简单且调节参数少的一类未知非线性动态估计器,在线估计系统未知非线性动态;其次,构建包含乘驾舒适度、悬架行程空间及输入能耗的性能指标函数,采用单层神经网络对最优性能指标函数进行在线逼近,并得到新的哈密尔顿函数;为实现在线求解,构建一类新的基于参数估计误差信息的自适应律,在线更新神经网络权值并计算最优控制律;最后,理论分析闭环系统稳定性和收敛性,并通过专业软件Carsim与Matlab/Simulink搭建的联合仿真平台给出的对比仿真结果,验证所提出方法可有效解决主动悬架系统多目标性能优化控制问题,提升主动悬架系统综合性能.     

Preview-based techniques for vehicle suspension control: a state-of-the-art review

Automotive suspension systems are key to ride comfort and handling performance enhancement. In the last decades semi-active and active suspension configurations have been the focus of intensive automotive engineering research, and have been implemented by the industry. The recent advances in road profile measurement and estimation systems make road-preview-based suspension control a viable solution for production vehicles. Despite the availability of a significant body of papers on the topic, the literature lacks a comprehensive and up-to-date survey on the variety of proposed techniques for suspension control with road preview, and the comparison of their effectiveness. To cover the gap, this literature review deals with the research conducted over the past decades on the topic of semi-active and active suspension controllers with road preview. The main formulations are reported for each control category, and the respective features are critically analysed, together with the most relevant performance indicators. The paper also discusses the effect of the road preview time on the resulting system performance, and identifies control development trends.     

机电作动器悬架硬件在环仿真测试平台研究

为了提高汽车的平顺性,提出一种机电作动器悬架,设计了机电作动器悬架硬件在环仿真测试平台。建立基于机电作动器的主动悬架数学模型与仿真模型,以嵌入式系统单片机为主处理器设计机电作动器悬架的控制器;在此基础上,以dSPACE为模型运行载体搭建机电作动器悬架硬件在环仿真测试平台;利用该测试平台进行了仿真试验。结果表明所研究的硬件在环仿真测试平台具备较好的硬件在环仿真功能,能够对机电作动器悬架性能、主动悬架控制算法进行验证与评价。     

Low-speed vehicle dynamics and ride quality using controlled D.C. electromagnets

The aim of this paper is to establish that attraction type systems, i.e. with controlled d.c. electromagnets, can be successfully employed for the suspension of urban transit vehicles, having speeds around 70 km/hr, without the aid of secondary suspension. The feasibility of the d.c. suspension systems is illustrated through the ride and track-clearance characteristics for a single-degree of freedom suspension system travelling along a ferromagnetic guideway with random roughness. Performance of the suspension system with active feedback of track-clearance, vertical velocity and vertical acceleration are discussed, and the analytical results are compared with experimental data obtained from a vibrating guideway test rig.     

Improved disturbance rejection with online adaptive pole-zero compensation on a Φ-shaped PZT active suspension

In feedback control systems, the anti-resonant zeros cannot be arbitrarily placed, hence degrading tracking performance as well as input disturbance and noise rejection capabilities due to reduced gain at the frequencies of the zeros. In this paper, an online adaptive inverse control with saturation (OAICS) algorithm is proposed for compensating the minimum phase resonant poles and anti-resonant zeros of a PZT active suspension using measured position error signal. Experimental results on a Φ-shaped PZT active suspension using laser Doppler vibrometer (LDV) shows the proposed OAICS is effective in cancelling the first two dominant minimum phase pole-zero pairs to achieve high servo bandwidth and low sensitivity servo system with small overshoot during set-point tracking.     

矿用自卸车主动油气悬架非线性控制方法研究

为了对矿用自卸车主动油气悬架进行有效控制,分析了其油气弹簧的刚度力与阻尼力的非线性特性,进而建立了两自由度油气悬架的非线性力学模型。应用微分几何线性化理论,经过恰当的坐标变换和反馈控制,实现非线性系统的精确线性化,而后对其设计使用线性PID控制研究;根据选定的控制目标及输出变量,通过制定相应的模糊控制规则表,设计模糊PID控制器,对悬架系统使用模糊PID控制研究。仿真结果表明,与被动悬架相比,精确线性化后的PID控制悬架以及模糊PID控制悬架均能显著提高车辆的平顺性和操稳性,使悬架的动态性能趋于稳定;另外,与模糊PID控制相比,线性化PID控制对于改善车辆行驶平顺性优势更加明显。     

汽车半主动悬架的ADAMS和MATLAB联合仿真

建立了基于模糊控制的汽车主动悬架模型，用ADAMS和MATLAB进行了联合仿真。结果表明主动悬架减小了车辆振动，提高了车辆的平顺性。联合仿真的方法避免了繁琐的动力学方程、控制系统传递函数推导，为复杂机械系统的控制仿真提供了新思路。     

A new model-free adaptive sliding controller for active suspension system

Active suspension systems are designed to provide better ride comfort and handling capability in the automotive industry. Since the active suspension system has nonlinear and time-varying characteristics, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, a functional approximation (FA) based adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The FA technique is employed to represent the unknown functions, which releases the model-based requirement of the sliding mode control. In addition, a fuzzy control scheme with online learning ability is employed to compensate for the modeling error of the FA with finite number of terms for reducing the implementation difficulty. To guarantee the control system stability, the update laws of the coefficients in the approximation function and the fuzzy tuning parameters are derived from the Lyapunov theorem. The proposed controller is employed on a quarter-car active suspension system. The simulation results and experimental results show that the proposed controller can suppress the oscillation amplitude of the sprung mass effectively. To evaluate the performance improvement of inducing a fuzzy compensator in this FA adaptive controller, the dynamic responses of the proposed hybrid controller are compared with those of FA-based adaptive sliding controller only.     

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 H∞ 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.     

基于电磁作动器的车辆座椅悬架最优控制研究

为了改善农用车、工程车等车辆座椅的减振性能,以电磁作动器为执行器,建立人体座椅—车辆两自由度的主动座椅悬架系统模型。通过对该系统的动力学模型进行线性化处理,并应用二次型最优控制理论,选取合适的加权系数,实现系统的最优控制。在Matlab/Simulink中以白噪声路面激励为系统输入,对主动控制和被动控制的座椅悬架系统仿真分析。结果表明：在不同的激励条件下,基于电磁作动器的主动座椅悬架系统减振效果显著,大幅降低了驾驶员所承受垂直振动加速度,提高了车辆的乘坐舒适性和操纵稳定性。