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。     

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.     

Emergency steering control of autonomous vehicle for collision avoidance and stabilisation

ABSTRACT

Collision avoidance and stabilisation are two of the most crucial concerns when an autonomous vehicle finds itself in emergency situations, which usually occur in a short time horizon and require large actuator inputs, together with highly nonlinear tyre cornering response. In order to avoid collision while stabilising autonomous vehicle under dynamic driving situations at handling limits, this paper proposes a novel emergency steering control strategy based on hierarchical control architecture consisting of decision-making layer and motion control layer. In decision-making layer, a dynamic threat assessment model continuously evaluates the risk associated with collision and destabilisation, and a path planner based on kinematics and dynamics of vehicle system determines a collision-free path when it suddenly encounters emergency scenarios. In motion control layer, a lateral motion controller considering nonlinearity of tyre cornering response and unknown external disturbance is designed using tyre lateral force estimation-based backstepping sliding-mode control to track a collision-free path, and to ensure the robustness and stability of the closed-loop system. Both simulation and experiment results show that the proposed control scheme can effectively perform an emergency collision avoidance manoeuvre while maintaining the stability of autonomous vehicle in different running conditions.     

A driver-adaptive stability control strategy for sport utility vehicles

Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers’ driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to ‘drive’ the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.     

基于扰动观测的客车ESC自适应神经网络滑模控制

为了提高客车电子稳定性控制系统(ESC)的控制精度,针对实际车辆系统建模中存在各种非线性扰动项以及传统滑模控制(Sliding Mode Control,SMC)中抖振较大的问题,提出一种自适应神经网络滑模控制算法.基于2自由度车辆模型,首先设计一个二阶滑模(Second-order Sliding Mode,SOSM...     

Second-order sliding mode controller with model reference adaptation for automatic train operation

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.     

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.     

汽车AMT自动离合器的改进模糊滑模控制

提出改进的模糊滑模控制器(MFSMC)实现离合器的自动控制。MFSMC采用饱和函数和模糊自适应系统来缓解抖振现象并提高其鲁棒性;采用局部线性化技术减少MFSMC的模糊规则数满足自动离合器的实时性要求。模拟结果显示所提出的控制器具有快速跟踪预定轨迹、对参数时变和外部扰动具有鲁棒性等特点。     

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.     

汽车防抱死制动系统的自抗扰控制研究

汽车防抱死制动系统(Anti-lock Braking System,ABS)的作用是确保汽车制动时行驶方向的稳定性、可靠性,但是目前仍存在非线性、时变性以及参数不确定性等问题.为保证汽车制动行驶过程中的操纵稳定性和安全性,进一步实现各工况下防抱死制动系统的优化控制,以影响整车稳定的变量滑移率为研究对象,分析所设计策略...     

复合功率分流系统发动机起动H∞鲁棒优化控制

为改善复合功率分流混合动力系统纯电动至混合动力模式切换过程的车辆驾驶平顺性,同时确保在模型不确定和外部干扰条件下切换控制的鲁棒性,本文中提出了一种发动机起动H∞鲁棒控制策略。首先,建立复合功率分流混合动力系统动力学模型,并对纯电动至混合动力模式切换过程进行分析。其次,以车辆驾驶平顺性和发动机起动时间为优化指标,通过动态规划求解发动机最优拖转转速曲线。然后,考虑到输入轴阻尼参数摄动、驾驶员输入、道路负载、输出端转速的不确定性变化和发动机转速量测噪声的干扰,设计了发动机起动H∞鲁棒控制器。最后,通过离线仿真和台架试验对所提出的控制策略进行验证。结果表明,该策略能有效将冲击度降低至11.52 m/s^3以内,同时对模型不确定性和外部干扰有较强的抑制能力。     

基于预测恒定车头时距策略的自适应巡航控制研究

为了进一步提高车辆跟车过程中的跟踪性、安全性、舒适性和燃油经济性，针对已有间距策略表现过于保守或反应过于激烈等不足之处，提出了一种预测恒定车头时距策略。该策略考虑了相对加速度，建立了一种预测型期望车间距模型，进而应用于模型预测控制的多目标自适应巡航控制系统中，能进一步提高模型预测控制对多个控制目标的综合协调能力。搭建上层控制器、下层PID控制器、油门制动切换、逆纵向动力学模型。在多工况下仿真，通过建立性能评判指标对多目标进行量化分析。结果表明，所提出的间距策略在保证安全性的前提下，提升了自适应巡航控制系统的综合性能。在不同驾驶风格的车头时距下，跟踪性、舒适性和燃油经济性均有良好表现。     

An adaptive fuzzy-sliding lateral control strategy of automated vehicles based on vision navigation

Lateral control is considered to be one of the toughest challenges in the development of automated vehicles due to their features of nonlinearities, parametric uncertainties and external disturbances. In order to overcome these difficulties, an adaptive fuzzy-sliding mode control strategy used for lateral control of vision-based automated vehicles is proposed in this paper. First, a vision algorithm is designed to provide accurate location information of vehicle relative to reference path. Then, an adaptive fuzzy-sliding mode lateral controller is proposed to counteract parametric uncertainties and strong nonlinearities, and the asymptotic stability of the closed-loop lateral control system is proven by the Lyapunov theory. Finally, experimental results indicate that the proposed algorithm can achieve favourable tracking performance, and it has strong robustness.     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。     

Model-independent self-tuning fault-tolerant control method for 4WID EV

To solve the problem of the existing fault-tolerant control system of four-wheel independent drive (4WID) electric vehicles (EV), which relies on fault diagnosis information and has limited response to failure modes, a modelindependent self-tuning fault-tolerant control method is proposed. The method applies model-independent adaptive control theory for the self-tuning active fault-tolerant control of a vehicle system. With the nonlinear properties of the adaptive control, the complex and nonlinear issues of a vehicle system model can be solved. Besides, using the online parameter identification properties, the requirement of accurate diagnosis information is relaxed. No detailed model is required for the controller, thereby simplifying the development of the controller. The system robustness is improved by the error based method, and the error convergence and input-output bounds are proved via stability analysis. The simulation and experimental results demonstrate that the proposed fault-tolerant control method can improve the vehicle safety and enhance the longitudinal and lateral tracking ability under different failure conditions.     

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。     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.     

Adaptive feedforward control of a steer-by-wire system by online parameter estimator

The tracking control of the steer-by-wire (SBW) system to achevie desired steering motion is the core issue for the design of algorithm. Most of model-based tracking control assumed the constant parameters without the consideration of dynamic characteristics. The external disturbances and model nonlinearities can bring uncertainties of the system parameters. To reduce the influence of parameter uncertainties, an online estimator by output error identification method is proposed to estimate the dynamic parameters of a SBW system. Meanwhile, the parameter gradient projection method is applied to eliminate the parameter drift, while a full order state observer is developed to weaken the effects of noise disturbance during the parameter identification. Since the sensitivity of parameter uncertainties for the feedforward control, the online estimator is incorporated into the control model and improve the controlled robustness. The proposed adaptive feedforward controller is conducted by the real-time experiments to show the tracking performance.     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).     

Comparing rear wheel steering and rear active differential approaches to vehicle yaw control

A comparison between two different approaches to vehicle stability control is carried out, employing a robust non-parametric technique in the controller design. In particular, an enhanced internal model control strategy, together with a feedforward action and a suitably generated reference map, is employed for the control of a vehicle equipped either with a rear wheel steering (RWS) system or with a rear active differential (RAD) device. The uncertainty arising from the wide range of operating conditions is described by an additive model set employed in the controller design. Extensive steady state and transient tests simulated with an accurate 14 degrees of freedom nonlinear model of the considered vehicle show that both systems are able to improve handling and safety in normal driving conditions. RAD devices can make the vehicle reach higher lateral acceleration values but they achieve only slight stability improvements against oversteer. On the other hand, 4WS systems can greatly improve both vehicle safety and manoeuvrability in all driving situations, making this device an interesting and powerful stability system.