自适应巡航控制新方法

为提高汽车高速行驶的交通安全 ,提出一种新的基于目标安全车距的自适应巡航控制(ACC)方法 .它仅通过调节辅助节气门开度和驱动轮制动力矩即可实现 .论述了测距传感器的选择 ,目标安全车距、目标减速度的确定和实现 ,给出了ACC逻辑框图 ,进行了仿真分析 .探讨了误报现象及其排除方案 .仿真结果表明 ,这种控制方法是简单可行的 ,易于和ABS/ASR形成ABS/ASR/ACC集成化系统     

New Method for Confirming the Desired Safety Headway Distance and Desired Deceleration in ACC System

A new method of confirming the desired safety headway distance and desired deceleration is put forward according to the detected static or moving target and its simulation results in Matlab are also presented.The validity of the algorithm to calculate the reference speeds of both the ACC vehicle and the targeted car according to the vector quadrangle composed of the relative distance, the relative azimuth angle, the relative speeds of the vehicles has also been demonstrated through numerical example in Matlab. New laws to obtain the desired deceleration by estimating the braking force according to the vehicle analyses force equation are established too.     

Combined Control Allocation and Sliding Mode Control in the Dynamic Control of a Vehicle with Eight In-Wheel Motors

An eight wheel independently driving steering (8WIDBS) electric vehicle is studied in this paper. The vehicle is equipped with eight in-wheel motors and a steer-by-wire system. A hierarchically coordinated vehicle dynamic control (HCVDC) system, including a high-level vehicle motion controller, a control allocation, an inverse tire model and a lower-level slip/slip angle controller, is proposed for the over-actuated vehicle system. The high-level sliding mode vehicle motion controller is designed to produce desired total forces and yaw moment, distributed to longitudinal and lateral forces of each tire by an advanced control allocation method. And the slip controller is designed to use a sliding mode control method to follow the desired slip ratios by manipulating the corresponding in-wheel motor torques. Evaluation of the overall system is accomplished by sine maneuver simulation. Simulation results confirm that the proposed control system can coordinate among the redundant and constrained actuators to achieve the vehicle dynamic control task and improve the vehicle stability.     

考虑驾驶员行驶特性的双模式自适应 巡航控制设计

为了设计一个能够模拟驾驶员行驶行为的汽车自适应巡航控制(ACC)系统,通过分析驾驶员的日常行驶特性,在模型预测控制的框架基础上提出一个双模式的自适应巡航控制策略：当远离前车时,ACC系统采取快速接近模式,在满足安全舒适的前提下以尽量短的时间减小两车间距;一旦车间距调整至期望值附近时,ACC系统切换到平稳跟车模式,使车辆安全、平稳、舒适地对前车进行跟车;为使2种模式切换时能平滑过渡,利用模糊理论设计了2个模式的切换规则来模拟驾驶员的决策过程.通过仿真试验,证实了该双模式ACC控制策略在满足行驶过程中的安全性以及舒适性的同时,有效地反映了驾驶员的日常行驶习惯,更易于被驾驶员接受,有利于提高ACC系统的使用率.     

汽车自适应巡航跟车多目标鲁棒控制算法设计

为满足自适应巡航系统跟车模式下的舒适性需求并且兼顾车辆安全性,基于模型预测控制原理提出一种多目标鲁棒跟车控制算法.建立考虑前车加速度干扰的自适应巡航系统车间纵向运动学模型,该模型可全面反映系统的动态演化规律,提高模型的精度和可靠性;针对自适应巡航系统需求进行目标分析,设计一种考虑舒适性和安全性的多目标模型预测控制算法;针对模型预测控制算法鲁棒性较差的问题,引入修正项反馈,提高控制系统鲁棒性,采用向量约束管理法解决模型预测控制算法硬约束造成的控制系统无优化解问题.仿真结果表明:该算法使跟车时车辆加速度及冲击度保持在舒适性范围,同时车间距始终大于最小安全距离,兼顾了舒适性和安全性要求,实现了自适应巡航控制系统跟车目的.     

Research on Directly Adaptive Fuzzy Algorithm Based ACC Controller

A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the traditional fuzzy membership. Adaptive law of the adjustable parameters θ is also determined. The directly adaptive fuzzy ACC controller is designed based on Matlab fuzzy toolbox. Matlab-Simulink is adopted to test the function of the adaptive fuzzy ACC controller. The control system is established using a 7 DOF vehicle dynamics model. Simulation results indicate that the principle of the method is correct and it performs well both in cruise and distance keeping.     

基于数据驱动的鲁棒反步自适应巡航控制

为了实现高精度的鲁棒自适应巡航控制（ACC）,提出基于数据驱动的鲁棒反步自适应巡航控制算法. 利用反步技术设计虚拟控制器,将车辆间距控制转化为速度控制,避免速度相关型间距策略带来的间距与速度控制耦合;构建基于数据的耦合滑模面并设计状态观测器,补偿车辆复杂的非线性动力学特性、离散误差及外部干扰,提升控制算法的鲁棒性;利用反馈控制及鲁棒控制技术设计数据驱动的ACC鲁棒控制算法;分别选取固定时间间距、变时间间距策略,利用所提ACC算法及基于比例积分（PI）的ACC算法进行车辆自适应巡航控制对比仿真验证. 对比实验结果表明,所提算法在控制精度、鲁棒性方面具有优越性.     

基于非线性反步法的欠驱动AUV地形跟踪控制

为实现欠驱动水下机器人(autonomous underwater vehicle,AUV)的精确地形跟踪控制,设计了一种基于Lyapunov稳定性理论的非线性反步(backstepping)法控制器.基于虚拟向导的方法,结合AUV艇体的动力学特性,建立AUV垂直面地形跟踪误差方程,采用backstepping法设计地形跟踪控制器,利用Lyapunov稳定性理论分析了整个系统的稳定性.仿真实验中选择海底斜坡地形进行跟踪实验,且要求AUV相对地形保持一个恒定的高度偏差,结果表明该控制方法可实现对斜坡地形的精确跟踪.     

固定翼无人机自适应滑模控制

针对固定翼无人机的姿态和速度控制中存在不确定和外部扰动的问题,设计自适应超螺旋滑模干扰观测器和控制器,实现了固定翼无人机对速度指令和姿态指令的有限时间精确跟踪.首先建立固定翼无人机速度模型和基于四元数的姿态误差模型;进而在该模型的基础上针对无人机飞行过程中的外部扰动和不确定问题,采用自适应超螺旋滑模算法设计干扰观测器对干扰和不确定进行快速估计,并在此基础上设计多变量超螺旋控制器使固定翼无人机快速、精确地跟踪期望的速度和姿态指令;最后基于Lyapunov理论证明了该系统的稳定性.仿真结果表明:所提出的综合控制策略可以实现固定翼无人机速度与姿态的快速精确跟踪并具有良好的鲁棒自适应能力,而且针对无人机不同的飞行指令,使用该控制策略都能使无人机快速稳定的达到预期目标.     

Nonlinear Derivative and Integral Sliding Control for Tracked Vehicle Steering with Hydrostatic Drive

在静液驱动履带车辆转向过程中,车辆的运动状态总是不确定的,且阻力存在非线性、大范围的变化。因此,提高静液驱动履带车辆的转向稳定性,满足未来战场的需要具有重要意义。本文提出了一种滑模控制算法,并将其应用于保证期望横摆角速度的控制。首先通过运动学和动力学分析,建立了速度控制器和横摆角速度控制器。其次设计了非线性微分积分滑模控制算法,通过积分控制项降低积分饱和,有效地抑制不光滑路面的扰动,通过非线性微分控制项提高了系统的反应速度,减小了控制量的抖振。在RecurDyn中对静液驱动履带车辆进行建模,在控制软件MATLAB/Simulink中对转向控制策略模块进行建模。整个模型的联合仿真表明,该控制策略能够提高车辆的转向响应速度,平滑控制输出,且抖振小,具有较强的鲁棒性。     

基于视觉的自动寻迹智能车系统设计与实现

以全国大学生智能汽车比赛为背景,设计一种在专门赛道上自动行驶的智能车控制系统,能够在遵守大赛的一系列规则下,最短时间内跑完全程并不脱离跑道。本系统以飞思卡尔公司的16位单片机MC9S12XS128为控制核心,提出一种基于模糊预瞄跟踪控制算法。以模拟人类驾车的方式,根据不同赛道情况,通过模糊预瞄器在线调节预瞄距离,并通过判断预瞄点位置来调节速度和转向角度。该方法使智能车系统达到要求的稳定性及快速性。实际运行结果表明,该系统具有较好的稳定性和鲁棒性.     

Integrated energy-oriented lateral stability control of a four-wheel-independent-drive electric vehicle

Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel independent-drive EV(4 WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs.In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator(LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor(SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral(PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally,double-lane change(DLC) simulations are conducted using Car Sim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by5.23% and 2.95% compared with the rule-based control strategy for high-and low-friction DLC maneuvers, respectively.     

无级变速汽车动力传动系统控制策略研究

针对汽车行驶工况复杂多变,且其传动系统输入输出具有强耦合的特点,传统的控制算法很难满足要求,为此提出了油门——速比协调控制的综合模糊控制策略,设计了油门自组织模糊控制器和速比参数自调整模糊控制器,并对典型运行工况进行了仿真和分析,仿真结果表明综合模糊控制器与常规PD控制器相比前者具有良好的控制效果,通过整车道路试验进一步验证了所建模型的正确性,所提出的控制算法是可行和有效的,解决了动态过程中无级变速汽车动力性和经济性相协调的问题.     

基于模糊—PID控制的对开路面汽车制动稳定性研究

提出了利用横摆力矩控制汽车在对开路面制动稳定性的方法.根据建立的动力学模型确立了相关的控制策略和控制模式,设计了参数自整定的模糊PID控制器,仿真与道路试验结果表明,利用汽车制动稳定性横摆力矩模糊-PID控制方法,能减少汽车在对开路面制动时的跑偏或激转等危险,且使汽车在制动偏驶后能快速恢复正确行驶车道,而将模糊-PID控制与模糊控制,PID控制得到的仿真结果进行对比也证明模糊-PID控制能更好的满足控制要求,从而验证了参数自整定模糊-PID控制方法对于提高汽车制动稳定性和行驶安全性的可行性.     

道路交叉口信号的模糊神经网络控制

应用模糊神经网络对交通系统进行控制是一种新的尝试，它可以充分发挥模糊逻辑和神经网络的优势，实现更为有效的控制。提出了一种基于模糊神经网络的道路交叉口交通信号控制方法，根据两相位的关键车流信息来决定绿灯延长时间，形成控制策略。仿真结果表明，与传统的定时控制方法相比，所提出的神经网络控制方法在车辆平均延误时间和排队长度方面都有较大改进，该方法有效、可行。     

Study on Steering Control Strategy for High-Speed Tracked Vehicle with Hydrostatic Drive

Steering control strategy for high-speed tracked vehicle with hydrostatic drive is designed based on analyzing the fundamental steering theories of the hydrostatic drive tracked vehicle. The strategy is completed by the cooperation between integrated steering control unit and pump & motor displacement controller. The steering simulation is conducted by using Simulink of Matlab. It is indicated that this steering control strategy can reduce the average vehicle speed automatically to achieve the drivers expected steering radius exactly in the case of ensuring not exceeding the system pressure threshold and no sideslip.     

Adaptive Fuzzy Control for CVT Vehicle

On the simple continuously variable transmission （CVT） driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.     

海流干扰下的欠驱动AUV三维路径跟踪控制

为解决存在海流干扰和模型不确定性情况下欠驱动自主水下航行器(AUV)的三维路径跟踪控制问题,首先在Serret-Frenet坐标系下,基于虚拟向导建立了跟踪误差模型.然后,在运动学控制器中基于李雅普诺夫(Lyapunov)理论和反步法设计具有自适应律的虚拟向导和一种改进的积分视线法(ILOS)导引律,克服了海流的干扰并减少了超调.应用反步自适应滑模控制(BASMC)理论设计动力学控制器,保证了系统的稳定性和鲁棒性.最后,应用非线性级联理论证明了整个控制系统的闭环稳定性.仿真结果表明:基于AUV与流体的相对速度来实现的控制律,便于工程应用.该控制器能够有效克服海流和模型不确定的影响,实现对三维路径的跟踪.     

汽车侧向避撞系统的模糊-PID控制仿真

汽车在高速行驶过程中进行超车或两车并列行驶时容易出现侧向碰撞。提出利用主动转向技术,根据两车并行时侧向距离的变化控制两车侧向距离满足安全要求,减小汽车发生侧向碰撞的可能。建立了基于两车侧向距离及其变化率的模糊-PID控制模型,确立了相应的控制策略和控制算法,设计了模糊-PID控制器,进行了复杂工况下的仿真试验,并将仿真结果与利用PID控制方法得到的仿真结果进行了对比。结果表明利用主动转向模糊-PID控制技术,能减少汽车在超车时发生侧向碰撞的危险,使汽车在高速行驶过程中具有更好的安全性。     

移动机器人模糊控制系统的设计

针对移动机器人在原控制器控制下自主运动时出现的不稳定状况,将模糊控制策略引入移动机器人运动控制系统中.通过分析比较不同的控制方法,设计了由速度误差率和速度误差变化率为控制系统的输入,移动机器人电机输出功率为控制系统的输出的双输入单输出的模糊逻辑控制器.通过仿真对比不同控制器所产生的移动机器人速度变化曲线,当移动机器人系统受到外界干扰时,对于原始控制器,PID控制器和模糊逻辑控制器速度变化的幅度分别为 26%, 13%, 4%.模糊逻辑控制器在处理外界干扰时在快速性和灵敏性上明显优于PID控制器和原始控制器,采用这种控制方法对移动机器人的驱动电机输出参数实现了模糊控制,达到了预期的工作性能要求.