多自由度车辆模型主动悬架及鲁棒控制

考虑发动机、座椅和乘客等多种因素影响，建立了一个多自由度车辆模型；用H∞方法设计了低自由度控制器。并比较了H∞控制器和LQ控制器在该系统中的表现。     

汽车四轮转向系统的H2/H∞混合控制

为使汽车四轮转向系统具有良好的鲁棒性和干扰抑制性能，针对外界干扰，对汽车四轮转向系统模型进行了分析，并将其转化为H2／H∞控制问题，运用Matlab的LMI控制工具箱设计了H2／H∞混合最优控制器。仿真结果表明，设计的最优控制器具有良好控制效果。     

增强电动转向系统助力跟踪性能的H∞控制

建立了电动转向系统数学模型，将H∞控制理论应用于电动转向系统跟踪性能的研究，采用线性矩阵不等式处理方法设计了最优H∞控制器，应用Matlab软件进行了计算机仿真，仿真和台架试验结果表明，所设计的电动转向控制系统具有良好的助力跟踪性能。     

汽车防抱死制动系统H_∞控制与PID控制的比较研究

控制方法是汽车防抱死制动系统的核心技术。为了提高ABS系统的鲁棒性能,在建立汽车防抱死制动系统数学模型的基础上,设计了H∞控制器,在Matlab/Simulink平台上对基于H∞控制器的ABS系统进行了动态仿真,并与基于传统PID控制器的ABS系统进行对比。通过对仿真结果进行比较发现,PID控制和H∞控制都能使ABS系统获得较好的制动性能;H∞控制响应迅速、具有优秀的稳定性和鲁棒性,总体控制效果优于PID控制。     

气体燃料发动机空燃比的H_∞控制

在充分考虑外部干扰和系统模型不确定性的情况下,将混合灵敏度H∞设计引入多点喷射燃气发动机空燃比控制中,将发动机空燃比控制转化为H∞标准设计。仿真结果表明,H∞控制器具有良好的跟踪性、鲁棒稳定性和抗干扰能力。     

H_∞鲁棒控制理论应用于CNG发动机怠速控制

针对CNG发动机的不确定性,将H∞鲁棒控制理论应用于CNG发动机的怠速控制,阐述了H∞加权混合灵敏度设计问题模型,建立了CNG发动机动力学模型,分析了发动机的不确定性.应用Matlab鲁棒控制工具箱,设计出基于H∞理论的CNG发动机的怠速控制器,并进行了仿真分析和试验.结果表明,H∞控制具有很好的鲁棒性,提高了CNG发动机怠速工况的稳定性.     

基于频率加权左互质分解的汽车悬架H∞控制器降阶研究

建立了7自由度汽车整车悬架模型,考虑人体对垂直和旋转方向振动的敏感频率范围,设计频率加权的H∞控制器。进而在选取特定加权矩阵保证降阶闭环系统稳定前提下,应用基于频率加权左互质分解的控制器降阶方法,对所设计的高阶H∞控制器进行降阶。仿真结果表明,控制器的阶数能够被较大程度地降低,而闭环控制效果损失很小,证明了频率加权左互质分解控制器降阶方法的有效性。     

汽车电动助力转向系统的H∞控制研究

在对汽车电动助力转向系统(EPS)进行分析的基础上，构建出系统模型，设计出鲁棒性好的H∞控制器，并在多种环境下进行了仿真研究。仿真结果表明，基于H∞控制的EPS具有较强的鲁棒性，在改善转向系统操纵性的同时，可保证驾驶员能获得较满意的路感，从而获得较好的转向特性。     

电液主动悬架的H∞控制研究

对用流量伺服阀构成的电液主动悬架进行了系统分析，并将其简化为Ｈ∞标准问题，设计了基于干扰抑制指标的Ｈ∞控制器。仿真和实验结果表明，设计出的Ｈ∞最优控制器有良好的控制效果，同时可以对系统总体性能进行优化，是一种适合主动悬架控制多 目标特点的控制器。     

基于4自由度车辆模型的电液主动悬架H∞控制

对带有电液主动悬架的车辆进行了力学分析，建立了4自由度车辆状态空间模型。在路面干扰激励下，为了改善汽车的行驶平顺性，基于二次型干扰抑制指标，对此多输入多输出(MIMO)系统设计出了H∞控制器。并且用MATLAB6．1进行了数值仿真，仿真结果表明带H∞控制器的主动悬架有效降低了车身垂直加速度和俯仰角加速度。     

Decoupled robust control of vehicular platoon with identical controller and rigid information flow

Platoon driving has potential to significantly benefit road traffic. This study presents a decoupled robust control strategy for a vehicular platoon with identical feedback controller and rigid information topology. The node dynamics of vehicle with a lower-level controller is assumed to be covered by a multiplicative uncertainty model. The vehicular platoon control system is skillfully decomposed into an uncertain part and a diagonal system by applying linear transformation and eigenvalue decomposition on information flow graph. Then the requirements of robust stability and distance tracking error are equivalent to the H-infinity norm of decoupled sub-systems. Comparative simulations with a non-robust controller and different communication topologies are conducted to demonstrate the robust stability and distance tracking performances of the proposed method.     

Modeling and control of an anti-lock brake and steering system for cooperative control on split-mu surfaces

The brake and steering systems in vehicles are the most effective actuators that directly affect the vehicle dynamics. In general, the brake system affects the longitudinal dynamics and the steering system affects the lateral dynamics; however, their effects are coupled when the vehicle is braking on a non-homogenous surface, such as a split-mu road. The yaw moment compensation of the steering control on a split-mu road is one of the basic functions of integrated or coordinated chassis control systems and has been demonstrated by several chassis suppliers. However, the disturbance yaw moment is generally compensated for using the yaw rate feedback or using wheel brake pressure measurement. Access to the wheel brake pressure through physical sensors is not cost effective; therefore, we modeled the hydraulic brake system to avoid using physical sensors and to estimate the brake pressure. The steering angle controller was designed to mitigate the non-symmetric braking force effect and to stabilize the yaw rate dynamics of the vehicle. An H-infinity design synthesis was used to take the system model and the estimation errors into account, and the designed controller was evaluated using vehicle tests.     

Application of time-variant predictive control to modelling driver steering skill

The paper addresses the need for improved mathematical models of human steering control. A multiple-model structure for a driver's internal model of a nonlinear vehicle is proposed. The multiple-model structure potentially offers a straightforward way to represent a range of driver expertise. The internal model is combined with a model predictive steering controller. The controller generates a steering command through the minimisation of a cost function involving vehicle path error. A study of the controller performance during an aggressive, nonlinear steering manoeuvre is provided. Analysis of the controller performance reveals a reduction in the closed-loop controller bandwidth with increasing tyre saturation and fixed controller gains. A parameter study demonstrates that increasing the multiple-model density, increasing the weights on the path error, and increasing the controller knowledge range all improved the path following accuracy of the controller.     

基于MPC的独立驱动电动汽车稳定性集成控制

针对独立驱动电动汽车在高附着系数路面高速急转时易发生侧翻事故,在低附着系数路面急转易发生侧滑失稳事故,且单一控制器在不同附着系数路面适应性较差等问题,根据独立驱动电动汽车特点设计了基于分层式结构的稳定性集成控制器。建立了整车动力学模型,并进行了车辆状态参数估计;设计了稳定性集成控制器的控制策略,对车辆的侧倾、横向稳定性状态判定条件和协调策略的制定进行了研究,分别设计了侧倾稳定性控制器和横向稳定性控制器;设置了路面附着系数0.9到0.2的对接路面仿真工况,并在此工况下对所设计的控制器的控制性能进行了仿真测试。结果表明,所设计的稳定性集成控制器相比于单一控制器具有更好的适应性,可有效降低车辆高速行驶过程中的横向载荷转移系数、质心侧偏角等状态量,提高车辆行驶的稳定性和安全性。     

PID plus fuzzy logic method for torque control in traction control system

A Traction Control System (TCS) is used to control the driving force of an engine to prevent excessive slip when a vehicle starts suddenly or accelerates. The torque control strategy determines the driving performance of the vehicle under various drive-slip conditions. This paper presents a new torque control method for various drive-slip conditions involving abrupt changes in the road friction. This method is based on a PID plus fuzzy logic controller for driving torque regulation, which consists of a PID controller and a fuzzy logic controller. The PID controller is the fundamental component that calculates the elementary torque for traction control. In addition, the fuzzy logic controller is the compensating component that compensates for the abrupt change in the road friction. The simulation results and the experimental vehicle tests have validated that the proposed controller is effective and robust. Compared with conventional PID controllers, the driving performance under the proposed controller is greatly improved.     

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 direct yaw moment controller for in-wheel motor electric vehicles

A novel direct yaw moment controller is developed in this paper. A hierarchical control architecture is adopted in the controller design. In the upper controller, a driver model and a vehicle model are used to obtain the driver's intention and the vehicle states, respectively. The upper controller determines the desired yaw moment by means of sliding mode control. The lower controller distributes differential longitudinal forces according to the desired yaw moment. A nonlinear tyre model, ‘UniTire’, is utilised to develop the novel distribution strategy and the control boundary.     

Vehicle yaw stability control using active limited-slip differential via model predictive control methods

In this paper, the problem of vehicle yaw control using an active limited-slip differential (ALSD) applied on the rear axle is addressed. The controller objective is to minimise yaw-rate and body slip-angle errors, with respect to target values. A novel model predictive controller is designed, using a linear parameter-varying (LPV) vehicle model, which takes into account the ALSD dynamics and its constraints. The controller is simulated using a 10DOF Matlab/Simulink simulation model and a CarSim model. These simulations exemplify the controller yaw-rate and slip-angle tracking performances, under challenging manoeuvres and road conditions. The model predictive controller performances surpass those of a reference sliding mode controller, and can narrow the loss of performances due to the ALSD's inability to transfer torque regardless of driving conditions.     

Rule-based control of a semi-active suspension for minimal sprung mass acceleration: design and measurement

In this paper, a rule-based controller is developed for the control of a semi-active suspension to achieve minimal vertical acceleration. The rules are derived from the results obtained with a model predictive controller. It is shown that a rule-based controller can be derived that mimics the results of the model predictive controller and minimises vertical acceleration. Besides this, measurements on a test vehicle show that the developed rule-based controller achieves a real-world reduction of the vertical acceleration, which is in agreement with the simulations.