A control method for congested traffic in the coupled map car-following model

Based on the pioneer work of Konishi et al, a new control method is presented to suppress the traffic congestion in the coupled map （CM） car-following model under an open boundary. A control signal concluding the velocity differences of the two vehicles in front is put forward. The condition under which the traffic jam can be contained is analyzed. The results axe compared with that presented by Konishi et al [Phys. Rev. 1999 E 60 4000-4007]. The simulation results show that the temporal behavior obtained by our method is better than that by the Konishi＇s et al. method, although both the methods could suppress the traffic jam. The simulation results are consistent with the theoretical analysis.

Feedback control scheme of traffic jams based on the coupled map car-following model

Based on the pioneering work of Konishi et al. [Phys. Rev. E （1999） 60 4000], a new feedback control scheme is presented to suppress traffic jams based on the coupled map car-following model under the open boundary condition. The effect of the safe headway on the traffic system is considered. According to the control theory, the condition under which traffic jams can be suppressed is analyzed. The results are compared with the previous results concerning congestion control. The simulations show that the suppression performance of our scheme on traffic jams is better than those of the previous schemes, although all the schemes can suppress traffic jams. The simulation results are consistent with theoretical analyses.

An improved car-following model with consideration of the lateral effect and its feedback control research

A car-following model is presented, in which the effects of non-motor vehicles on adjacent lanes are taken into ac- count. A control signal including the velocity differences between the following vehicle and the target vehicle is introduced according to the feedback control theory. The stability condition for the new model is derived. Numerical simulation is used to demonstrate the advantage of the new model including the control signal; the results are consistent with the analytical ones

Design of Model Following Variable Structure Controller for Three-axle Vehicle

An optimal control procedure is developed for the front and rear wheels of a three-axle vehicle moving on a complex typical road based on model following variable structure control strategy. The actual vehicle may be considered as an uncertain system. Cornering stiffness of front and rear wheels and external disturbances are varied in a limited range. The model-following variable structure control method is used to control both front and rear wheels steering operations of the vehicle, so that steering responses of the vehicle follow from those of the reference model. By numerical results obtained from computer simulation, it is demonstrated that the control system model can cope with the effects of parameter perturbations and outside disturbances.

Path following control of underactuated ships based on nonswitch analytic model predictive control

A path following controller is developed for underactuated ships with only surge force and yaw moment available to follow a predefined path.The proposed controller is based on nonswitch analytic model predictive control.It is shown that the optimal control law for a nonlinear path following system with ill-defined relative degree is continuous and nonsingular.The problem of ill-defined relative degree is solved.The path-following ability of the nonlinear system is guaranteed.Numerical simulations are provided to demonstrate the effectiveness of the proposed control law.

State Predictive Model Following Control System for Linear Time Delays

In this paper, we propose a new state predictive model following control system （MFCS）. The considered system has linear time delays. With the MFCS method, we obtain a simple input control law. The bounded property of the internal states for the control is given and the utility of this control design is guaranteed. Finally, an example is given to illustrate the effectiveness of the proposed method.

Modelling and Simulation for Train Movement Control Using Car-Following Strategy

基于最佳的速度汽车追随者模型，在这份报纸，我们为描述火车运动控制的进程建议一个新铁路交通模型。在建议模型，我们给最佳的速度功能 Vopt 的一种改进形式，它在不同控制条件下面为火车运动控制被看作需要的速度功能。以便测试建议模型，我们模仿并且分析火车运动的轨道，而且，讨论在许可的速度和目的地点详细削尖的火车之间的关系曲线。分析结果显示建议模型罐头很好捕获火车运动控制的某现实主义的期货。

A control method applied to mixed traffic flow for the coupled-map car-following model

In light of previous work [Phys. Rev. E 60 4000 （1999）], a modified coupled-map car-following model is proposed by considering the headways of two successive vehicles in front of a considered vehicle described by the optimal velocity function. The non-jam conditions are given on the basis of control theory. Through simulation, we find that our model can exhibit a better effect as p = 0.65, which is a parameter in the optimal velocity function. The control scheme, which was proposed by Zhao and Gao, is introduced into the modified model and the feedback gain range is determined. In addition, a modified control method is applied to a mixed traffic system that consists of two types of vehicle. The range of gains is also obtained by theoretical analysis. Comparisons between our method and that of Zhao and Gao are carried out, and the corresponding numerical simulation results demonstrate that the temporal behavior of traffic flow obtained using our method is better than that proposed by Zhao and Gao in mixed traffic systems.

FUZZY MODEL-FOLLOWING ADAPTIVE CONTROL DESIGN FOR ROBOT MANIPULATORS

The increasing demand on robotic system performance leads to the use of advanced con- trol strategies. This paper proposes a method of nonlinear feedback control introducing fuzzy infer- ence into model-following adaptive control for the nonlinear robot manipulator systems. The fuzzy inference is introduced to treat the nonlinearities of the control systems. Furthermore, the stability of the system is discussed by the fuzzy stability theory based on the Lyapunov's direct method. In the closed loop, the robotic system asymptotically converge to the reference trajectory with a pre- scribed transient response.

Car-following models of vehicular traffic

The Car-following model is a kind of microscopic simulation model for vehicular traffic, which describe the one-by-one following behaviors of vehides in the same traffic lane. As a common traffic phenomenon, following behavior is of great importance in the micro-study of intelligent traffic control.Compared with other traffic-flow models, car-following model embodies the human factors and feflects the real traffic sit-uation in a better way. This paper gives a systematic review of the development and actuality of car-following models by introducing and analyzing in detail the advantages and disavantages of GHR model, OV model,CA model and fuzzy-logic model. In addition, local stability and asymptotic stability of car-following models are discussed in this paper.

A time-optimal aircraft-following model based on Pontryagin's minimum principle

A time-optimal aircraft-following model is introduced to address air traffic flow interference by velocity reduction. The objective function is set up as minimizing the recovery time during which the separation minima are not infringed and the separation of the air traffic flow returns to the initial separation at the terminal time. Pontryagin＇s minimum principle is used to solve the optimum aircraft-following velocity control law. An analytical minimum safe following separation is also provided under the time-optimal control law. The simulation results show that the precision first-order tracking accuracy is achieved without losing the separation.

Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

Considering Backward Effect in Coupled Map Car-Following Model

Based on the pioneer work of Konishi et al,a new control method is proposed to suppress the trafficcongestion in the coupled map (CM) car-following model under open boundary condition.The influence of the followingcar to the system has been considered.Our method and that presented by Konishi et al.[Phys.Rev.E 60 (1999) 4000]are compared.Although both the methods could suppress the traffic jam,the simulation results show that the temporalbehavior obtained by ours is better than that proposed by the Konishi's et al.The simulation results are consistent withthe theoretical analysis.

A Switching Method for a Model Reference Robust Control with Unknown High Frequency Gain Sign

The problem of controlling a single-input-single-output plant without prior knowledge of high frequency gain sign is addressed by using the model reference robust control approach.A switching method is proposed based on a monitoring function so that after a finite number of swi- tchings the tracking error converges to zero exponentially.Furthermore,it is shown that if some initial states of the closed-loop system are zero,only one switching is needed.

虚拟编组下基于跟驰模型的列车群运行控制方法研究

高速铁路移动闭塞方式下运输能力与运输需求之间依然存在缺口,虚拟编组是未来提高运输能力的新方式。本文基于虚拟编组概念,受道路交通跟驰模型启发,引入列车动力学和运动学理论,根据相邻两列车之间的速度和距离关系,提出一种新的追踪列车加速度调整策略,建立相应的列车群虚拟编组加速度控制模型,当实现列车群的虚拟编组时,列车群中所有列车的速度相等,任意相邻列车之间的间距等于期望间距,同时,能够确保列车安全与乘客舒适度。本文以CRH380A动车组为背景验证模型,算例仿真结果表明,本文提出的加速度调整策略能有效实现列车群的虚拟编组;与移动闭塞方式相比,采取虚拟编组方式达到列车协同的时间减少9.7%,列车间距缩小10.1%,效率更高;将列车群视为一个整体时,实现虚拟编组的时间比将整个列车群分为多组时更短。

基于多模型自适应方法的智能汽车路径跟踪控制

路径跟踪控制是智能汽车的一项核心技术,跟踪效果的精确性和在各种路面附着条件下的鲁棒性是该技术的两大关键要素。但汽车动力学模型的不确定性,尤其是轮胎侧偏刚度的摄动使这两者难以同时得到满足。针对这一问题,将多模型自适应理论引入到智能汽车运动控制中处理不确定性系统的控制。首先,推导了多模型自适应控制律,提出了凸包构架下各个顶点的子模型对真实模型的自适应逼近律,并通过李雅普诺夫函数证明了所提出自适应律的收敛能力。在此基础上建立了汽车动力学模型和车辆-路径联合模型,并由多个顶点子模型构建可覆盖汽车轮胎侧偏刚度摄动范围的凸多面体,利用汽车动力学模型求解自适应率,通过车辆-路径联合模型,基于线性二次型方法(linear quadratic regulator,LQR)求解各个顶点的子模型处的反馈控制律,并通过所得出的自适应权重进行加权。基于Carsim/Simulink的联合仿真结果表明,所提出的多模型自适应路径跟踪控制器在保证鲁棒性的同时克服了传统鲁棒控制方法的保守性问题,与基于名义模型的LQR控制器和鲁棒保性能控制器相比,在高附着路面和低附着路面上都可以取得更好的控制效果,很好地解决了路径跟踪控制中精确性与鲁棒性之间的两难问题。最后,通过快速原型测试平台对算法进行了进一步的实验验证。结果表明,所提出的多模型自适应算法实时性良好,具有较好的工程应用潜力。

地形跟随中航迹跟踪模型预测控制方案设计

针对地形跟随飞行中的航迹跟踪问题,设计了航迹跟踪模型预测控制器,并讨论了模型预测控制中时域参数切换的自适应方案设计。首先,结合被控对象的特点,设计了用于实现全局稳定跟踪参考航迹的模型预测航迹控制器,并对控制器展开了稳定性分析。然后,充分发挥模型预测控制的预测能力,进行了航迹跟踪方法和综合误差评价策略设计。同时,通过分析不同航迹段的跟踪需求,设计了自适应调整模型预测控制中时域参数的优化方案。仿真验证结果表明,自适应方案相比固定时域方案航迹跟踪精度更高、飞行颠簸小、稳定性好,预设的评价指标函数能有效评估跟踪性能。

基于模型跟随自适应控制的电液位置伺服系统重构控制

航空机电系统中电液位置伺服系统(EHPSS)组件故障易引发连锁反应,对此,本文提出了一种基于模型跟随自适应控制的重构控制器。首先,根据电液位置伺服系统的组成结构、工作原理以及典型组件故障机理,分别建立其标称模型与故障模型;然后,结合模型跟随理论与Lyapunov稳定性理论,设计了模型跟随自适应重构控制器,该控制器不需要故障先验信息,仅根据故障系统的状态与参考模型状态之间的广义误差,在线调整自适应控制器参数,使得当时间趋向无穷大时,广义误差信号逐渐收敛于零,不仅可以保证系统的稳定性,还具有自适应速度快的优点;最后,通过多种故障情况下的位移跟踪试验,验证了该重构控制方法的重构控制能力和鲁棒性。本文所提出的建模与控制方法对于机电系统重构控制的未来研究具有参考价值。

车辆自适应巡航控制的内秉模态特性

为分析车辆自适应巡航控制下的跟驰状态对驾乘舒适性的影响,基于刺激-反应类线性跟驰模型,分别模拟跟驰车在微尺度避撞工况、微尺度扰动工况和全球统一轻型车辆测试循环(world light vehicle test cycle, WLTC)工况的速度-时间图像,采用经验模态分解(empirical mode decomposition, EMD)和快速傅里叶变换(fast Fourier transform, FFT)相结合的时频分析方法提取跟驰车的内秉模态特性,分析低频下不同驾驶工况对驾乘人员舒适性的影响。结果表明:不同驾驶工况的内秉模态频率不同,频率越小,车辆的振幅越大;相较于微尺度避撞工况和扰动工况,WLTC工况的内秉模态频率带宽分布较宽,幅值较高,波动能量较大;WLTC工况下,频率小于0.10 Hz的超低频区的内秉模态幅值较高,人体恶心程度较严重,对运动病的贡献较大。

基于横摆运动补偿的煤矿重载铰接车辆主动电液转向控制研究

煤矿重载铰接车辆采用折腰转向,横向刚度弱且所受扰动因素复杂,操控难度加大,极易引起安全事故。为改善煤矿重型铰接车辆在湿滑低附着路面环境中的安全驾驶操控性能、进一步提升煤矿辅助运输智能化水平,设计了一种具有横摆运动反馈补偿功能的泵控电液动力转向系统。建立了包含前车体纵向、侧向、横摆及后车体横摆运动在内的铰接车辆4自由度车体动力学模型以及泵控电液转向系统数学模型,在解耦动力学模型横摆角速度与横向加速度的基础上,设计了“转向操纵跟随−横摆稳定补偿”双通道铰接转向控制策略,其中,转向操纵跟随通道可实现前后车体铰接角对驾驶员的转向操控输入的实时跟踪,而横摆稳定补偿通道则通过主动调节车体铰接角以确保实际横摆角速度逼近理想横摆角速度。通过设置预滤波器和衰减积分器,设计了主动转向控制系统,该系统通过调整转向角度来提供纠正作用,以确保车辆能够遵循驾驶员意图保持路径跟随。基于dSPACE/DS1007半实物仿真平台,对铰接矿车低附着转向工况进行了仿真测试;模拟J型转弯工况,选择低摩擦因数路面条件中低速运行,验证了主动控制器对于铰接车辆跟踪期望路径的有效性。同时,基于冰雪覆盖路面等效低附着系数路面的实验条件,利用煤矿井下25 t级重型铰接式支架搬运车进行了实车转弯实验;结果表明:建立的铰接车辆车体动力学模型和泵控电液转向系统模型,通过横摆角速度与横向加速度进行解耦,能够比较真实的反应该类车辆的折腰运动状态;基于铰接车辆横摆稳定性控制分析,制定的“转向操纵跟随−横摆稳定补偿”双通道铰接转向控制策略,以及设计的主动控制系统,能够有效提高铰接车辆在低附着路面工况下的横摆稳定性,且该系统对于驾驶员的驾驶感觉没有改变,主动控制干预后能够及时、安全、平稳地将车辆的驾驶权交还给驾驶员。