线控转向系统故障检测及容错控制协同设计

为解决线控转向系统故障可能导致车辆失控的问题,提出一种故障检测及容错控制协同设计方法。首先,建立了包含线控转向系统加性故障的车辆动力学模型;其次,联合车辆动力学模型及故障检测/容错控制器,建立跟踪误差闭环控制系统;然后,求解满足闭环系统H∞性能的线性矩阵不等式,得到故障检测/容错控制器参数;最后,基于dSPACE Full-Size HIL进行硬件在环仿真测试。结果表明,该方法可快速检测出转向系统故障,同时实现了车辆的容错控制。     

Reconfigurable fault-tolerant controller synthesis for a steer-by-wire vehicle using independently driven wheels

In this paper, a synthesis method for a reconfigurable fault-tolerant control system for use in a steer-by-wire vehicle is proposed. The vehicle considered in this paper is also assumed to have independently driven wheels. The control objective in this work is to enable the vehicle yaw rate to track the reference signal even when the steering actuator breaks down. Since the vehicle yaw rate can be controlled with either the front wheel turn angle or the yaw moment generated by the independently driven wheels, this system has actuator redundancy. We attempt to design a control system that manages this actuator redundancy so that the performance degradation due to the actuator failure is minimised. We utilise a control allocator based on on-line optimisation for managing the actuator redundancy. The fault-tolerant control system with a control allocator has several excellent properties. For example, the method can handle various failure situations. Also, since the control allocation problem is reduced to a convex quadratic programming problem, the on-line computational effort is relatively little. However, so far, it has been unclear whether the stability of the control system with the control allocator is guaranteed when the actuator failure occurs. Therefore, we propose a design method of a fault-tolerant controller based on on-line optimisation that guarantees the stability of the overall system. The effectiveness of the method is established through numerical examples.     

基于单神经元的汽车方向自适应PID控制

针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应PID控制算法。该算法利用了神经网络的自学习和自适应能力，实现了方向PID控制器的参数在线自整定，从而避免了传统的自适应PID控制必须在线辨识被控系统的参考模型参数而带来的计算工作量大的问题。仿真计算和场地试验验证表明该控制算法可有效地控制汽车按照预期给定的轨迹行驶，且保证了汽车方向闭环控制系统具有较强的适应性和鲁棒性。     

车速控制系统自适应油门控制器设计

在分析非线性车辆纵向动力学模型及简化模型基础上，采用一种简化非线件模型设计自适应油门控制器，并应用李亚谱诺夫理论证明了传动系统存在动态过程时控制系统的稳定性。通过对基于简化线性和非线性模燃的自适应控制器的仿真研究，结果表明后者具有更好的收敛性。试验结果也进一步表明，基于非线性模型的自适应控制器可以通过自适应调节减小参数不确定造成的干扰，当传动系统存在动态过程时可以保证车速跟踪误差有界。     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

基于神经网络的半主动悬架自适应模糊控制

提出了基于神经网络的自适应模糊控制策略。模糊控制主要用来对付系统的非线性；神经网络根据振动响应的方差递推结果来辨识车体的振动情况实时调节模糊控制器的量化因子，使模糊控制器对路面的变化具有自适应的能力。在半主动悬挂1／4车非线性模型的基础上进行了仿真研究。     

Fault-tolerant braking control with integerated EMBs and regenerative in-wheel motors

This paper presents a fault-tolerant brake torque controller for four-wheel-distributed braking systems with in-wheel motors and Electro-Mechanical Brakes (EMB). Mechanical and electrical faults can degrade the performance of the EMB actuators and, thus, their effects need to be compensated in vehicle dynamics level. In this study, the faults are identified as performance degradation and expressed by the gains of each actuator. Assuming the brake force distribution and the regenerative braking ratios, the over-actuated braking system is simplified into a two-input system. A sliding mode controller is designed to track the driver’s braking and steering commands, even if there exist faults in EMBs. In addition, adaptive schemes are constructed to achieve the fault-tolerant control in braking. The proposed controller and strategies are verified in the EMB HILS (Hardware-in-loop-simulation) unit for various conditions.     

An Optimal Self-Tuning Controller for an Active Suspension

An optimal self-tuning control algorithm is presented for vehicle suspension design. The controller, incorporating a weighting controller, state observer and parameter estimator, is designed according to linear optimal control (LQG) theory. Based on the updated estimates of vehicle parameters and states, and the adapted weighting parameters, the LQG controller provides the optimal set of gains over different operating conditions. The feasibility and effectiveness of the proposed self-tuning system was investigated and proved by simulation studies.     

Fault-tolerant yaw moment control with steer — and brake-by-wire devices

This paper presents an fault-tolerant yaw moment control for a vehicle with steer-by-wire (SBW) and brake-by-wire (BBW) devices. SBWs and BBWs can give active front steering (AFS) and electronic stability control (ESC) functions, respectively. Due to motor-driven devices, actuator and sensor faults are inherent in SBW and BBW, and can cause a critical damage to a vehicle. Simple direct yaw moment control is adopted to design a vehicle stability controller. To cope with actuator failure, weighted pseudo-inverse based control allocation (WPCA) with variable weights is proposed in yaw moment distribution procedure. Simulations on vehicle simulation software, CarSim®, show the proposed method is effective for fail safety.     

基于模型预测控制的智能车轨迹跟踪控制研究

为了完成智能车的轨迹跟踪,提出一种基于模型预测控制的轨迹跟踪方法,利用将运动学模型这个非线性系统线性化的方案,来获得必须的线性时变系统,采取模型预测控制的三要素来设计控制器。并且基于MPC在控制过程中能增加多种约束的优点,建立基于车辆运动学模型的约束做轨迹跟踪仿真实验,最后,基于山东理工大学智能车平台上GPS提供的定位信息,在校园中采集路线并对前提规划好的的轨迹进行实车验证。实验结果表明:基于MPC算法所设计的控制器能快速且稳定地跟踪期望轨迹。     

Adaptive Throttle Control for Speed Tracking

Electronic throttle control is an important part of every advanced vehicle control system. In this paper we design an adaptive control scheme for electronic throttle that achieves good tracking of arbitrary constant speed commands in the presence of unknown disturbances. The design is based on a simplified linear vehicle model which is derived from a validated nonlinear one. The designed control scheme is simulated using the validated full order nonlinear vehicle model and tested on an actual vehicle. The simulation and vehicle test results are included in this paper to show the performance of the controller. Due to the learning capability of the adaptive control scheme, changes in the vehicle dynamics do not affect the performance of the controller in any significant manner.     

四轮独立驱动电动车自适应巡航滑模控制

为实现四轮独立驱动电动汽车的自适应巡航功能,采用基于趋近律的滑模控制理论设计了自适应巡航控制系统.上位控制器以实际车距与期望车距的偏差作为输入,采用滑模控制律获得主车期望加速度,然后将期望加速度作为下位控制器的输入,计算出电机期望转矩,用于实现自适应巡航控制.在CarSim中建立电动汽车整车模型,并与Simulink进...     

Adaptive Throttle Control for Speed Tracking

SUMMARY

Electronic throttle control is an important part of every advanced vehicle control system. In this paper we design an adaptive control scheme for electronic throttle that achieves good tracking of arbitrary constant speed commands in the presence of unknown disturbances. The design is based on a simplified linear vehicle model which is derived from a validated nonlinear one. The designed control scheme is simulated using the validated full order nonlinear vehicle model and tested on an actual vehicle. The simulation and vehicle test results are included in this paper to show the performance of the controller. Due to the learning capability of the adaptive control scheme, changes in the vehicle dynamics do not affect the performance of the controller in any significant manner.     

Lateral controller design for an unmanned vehicle via Kalman filtering

This paper proposes a lateral control system for an unmanned vehicle that is designed to improve the responsiveness of the system with the use of a PD control. The vehicle heading error can be stabilized, and the transient response characteristics can be improved using the proposed controller. A mathematical model of the vehicle dynamics using two degrees of freedom was developed for the controller design. The waypoint tracking method for autonomous navigation was tested with incorporation of the Point-to-Point algorithm with position and heading measurements received from GPS receivers via Kalman filtering. The performance of the designed controller was verified through experiments with a real vehicle.     

智能汽车轨迹跟踪与横摆稳定性协同控制

为了提高四轮独立驱动智能电动汽车在变曲率弯道下的轨迹跟踪精度和横摆稳定性,提出了一种模型预测控制与直接横摆力矩控制协同的综合控制方法。建立了横纵向耦合的车辆动力学模型,采用2阶龙格库塔离散法保证了离散模型的精度,并基于简化的2自由度动力学模型推导了车辆横摆稳定性约束,设计了非线性模型预测控制器;利用直接横摆力矩控制能够改变车辆横摆角速度和航向角的特点,考虑模型预测控制器的预测状态、控制量以及跟踪误差,设计了协同控制规则。仿真结果表明,协同控制方法解决了考虑横摆稳定性约束的模型预测控制器中存在的稳定性约束与控制精度相矛盾的问题,并补偿了模型预测控制器没有可行解时对横摆稳定性的约束,同时提高了智能汽车的轨迹跟踪精度和横摆稳定性。     

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.     

Modified lateral control of an autonomous vehicle by look-ahead and look-down sensing

This paper presents a modified lateral control method for an autonomous vehicle with both look-ahead and look-down sensing systems. To cope with sensor noise and modeling uncertainty in the lateral control of the vehicle, a modified LMI-based H lateral controller was proposed, which uses the look-ahead information of the lateral offset error measured at the front of vehicle and the look-down information of the vehicle yaw angle error between the reference lane and the centerline of the vehicle. To verify the safety and the performance of the lateral control, a scaled-down vehicle was developed, and the positioning of the vehicle was estimated with USAT. The proposed controller, which uses both look-ahead and look-down information, was tested for lane changing and reference lane tracking with both simulation and experiment. The simulation and experimental results show that the proposed controller has better tracking and handling performance compared with a controller that uses only the look-ahead information of the target heading angle error.     

Hybrid state-feedback sliding-mode controller using fuzzy logic for four-wheel-steering vehicles

This paper presents a fuzzy controller for high-speed four-wheel-steering (4WS) vehicles based on the state-feedback and the sliding-mode control methods. In the proposed fuzzy controller, the consequent part of the fuzzy IF-THEN rules consists of either a sliding-mode controller or a state-feedback controller. Also, it will be proved that, if every fuzzy rule is stable in the sense of Lyapunov for a general Lyapunov function, defined for the whole system, then the whole system is stable in the sense of Lyapunov. The effectiveness of the proposed method for handling improvement of the 4WS systems will be demonstrated by simulations using a nonlinear vehicle model. The simulation results show that the proposed control method can enhance the dynamic response of the 4WS vehicles by reducing the transient response time and improving vehicle stability as compared to the sliding-mode and the fuzzy sliding-mode control methods.     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

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.