基于PID神经元网络和内模控制的拥塞控制算法*

针对网络系统的大时滞和非线性特性,设计了一种新的拥塞控制算法,将PID神经元网络与内模控制相结合应用于主动队列管理中,并使用Lyapunov理论证明了此算法的稳定性。NS仿真结果表明,这种算法的稳态和瞬态性能都优于PID算法,并且在参数变化和负载扰动时具有很强的鲁棒性。     

基于智能预测控制的网络拥塞主动队列管理算法研究

路由队列管理是保证网络性能、避免网络拥塞的重要手段,目前采用的主要队列管理方法为被动式队列管理,同时主动式队列管理已经成为近来的主要研究热点. 随机早侦测(RED)作为最早提出的主动队列管理方法,更获得了普遍的关注. 使用严格的数学模型来描述由端系统和网关组成的系统,并进行队列管理性能分析. 提出一种采用快速广义预测控制的RED控制器( FGPC2RED控制器) ,进行网络拥塞控制的研究. 介绍了系统的结构及系统的辨识, 并通过仿真证明了FGPC算法在路由队列管理中应用的可行性,可以有效控制队列长度,避免路由拥塞及减小往返延迟.     

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management （AQM） algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.     

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management (AQM) algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.     

Anti-windup compensator for active queue management in TCP networks

In this paper, we apply a dynamic anti-windup scheme for improving the performance of a conventional proportional–integral (PI) controller for active queue management (AQM) supporting TCP flows. When a PI controller is used for AQM, the windup phenomenon of the integral action can cause performance degradation because the packet drop probability is limited between 0 and 1. Therefore we suggest a TCP/AQM model with a saturating actuator and apply a dynamic anti-windup method for improving the performance of the conventional PI AQM scheme. The proposed scheme not only provides graceful performance degradation, but also guarantees the stability of the overall system with the linearized TCP model. We verify the performance of the proposed scheme through ns-2 simulations. The simulation results show that our scheme outperforms the conventional PI controller when the traffic load is not stationary, which is always the case in real network environment.     

Analysis of a rate-based feedback control strategy for long haul data transport

Digital communication has become fast enough so that the speed of light has become a bottleneck. For example, the round trip transcontinental [USA] delay through a fiber link is approximately 0.04 s; at 150 Megabit/s, a source needs to transmit approximately 8,000,000 bits during one round trip time to utilize the bandwidth fully. As the service rates of queues get large, the time scales of congestion in those queues decrease relative to the round trip time, making the dual goals of keeping buffers small and utilizations high even more difficult to achieve. In this paper we analyze a class of delayed feedback schemes that achieve these goals despite propagation delays and regardless of network rates. We analyze the delayed feedback schemes as a system of delay-differential equations, in which we model the queue-length process and the rate at which a source transmits data as fluids. We assume that a stream of acknowledgements carries information about the state of a bottleneck queue back to the source, which adapts its transmission rate according to any monotone function of that state. We show stability for this class of schemes, in that their rate of transmission and queue length rapidly converge to a small neighborhood of the designed operating point. We identify the appropriate scaling of the model's parameters, as a function of network speed, for the system to perform optimally: with a deterministic service rate of μ at the bottleneck queue, the steady state utilization of the queue is and steady state delay is . We also describe the transient of behavior of the system as another source suddenly starts competing for the bandwidth resources at the bottleneck queue. This work directly applies to the adaptive control of Frame Relay and ATM networks, both of which provide feedback to users on congestion.     

预测PI时滞网络拥塞控制算法设计及性能分析

针对网络中存在的大时滞给主动队列管理算法性能带来的不利影响,将Sm ith预估器与Dahlin算法相结合,提出了一种预测PI拥塞控制算法,首先利用Sm ith预估器补偿时延滞后,克服了大时滞给系统性能带来的影响;然后按Dahlin算法设计控制器,把控制器参数和预估对象模型参数相结合,既减少了整定参数,也避免了参数整定时的相互影响.同时,利用经典控制理论方法分析了系统稳定性和存在链路容量干扰时瓶颈队列的暂态、稳态特性.仿真结果显示预测PI算法控制性能优于RED,PI算法及具有较强的鲁棒性.     

基于再励学习的主动队列管理算法

从最优决策的角度出发,将人工智能中的再励学习方法引入主动队列管理的研究中,提出了一种基于再励学习的主动队列管理算法RLGD(reinforcement learning gradient-descent).RLGD以速率匹配和队列稳定为优化目标,根据网络状态自适应地调节更新步长,使得队列长度能够很快收敛到目标值,并且抖动很小.此外,RLGD不需要知道源端的速率调整算法,因而具有很好的可扩展性.通过不同网络环境下的仿真显示,RLGD与REM,PI等AQM算法相比,具有更好的性能和鲁棒性.     

主动粘弹性控制抗冲击扰动

根据粘弹性材料耗能减振性能较好的特点,针对高频扰动、冲击扰动,本文提出了主动粘弹性控制的方法,定义了主动粘弹性控制技术的基本架构.根据粘弹性材料的耗能计算模型,提出了粘弹性控制律的选取原则.结合广义Maxwell模型,提出了3种粘弹性控制律(viscoelastic control law,VCL).并将粘弹性比例–微分(proportional derivative,PD)控制、粘弹性比例–积分–微分(proportional integral derivative,PID)控制、粘弹性自抗扰控制(active disturbance rejection control,ADRC)应用到常见的二阶系统中.研究结果表明,主动粘弹性控制技术抗高频扰动、抗冲击扰动的性能特别优异.由于主动控制的响应速度快,主动粘弹性控制的抗扰性能好,本文提出了主动控制与主动粘弹性控制相切换的控制方法,并对切换控制策略进行了研究.研究结果表明,切换控制可同时兼顾抗扰性能与响应速度.     

大时滞网络中的拥塞控制算法

主动队列管理(AQM)通过网络中间节点有目的的分组丢弃实现了较低的排队延时和较高的有效吞吐量,是近年来TCP端到端拥塞控制的一个研究热点.已有的大多数AQM算法在设计过程中都没有充分考虑到大时滞对算法性能的影响.首先通过仿真试验证实了已有的几种典型算法控制的队列在大时滞网络中无一例外地出现了剧烈的振荡,导致瓶颈链路利用率下降和延时抖动加剧.为此,在进行了适当模型拟合处理的基础上,应用控制理论中的内模补偿原理设计了鲁棒的延时补偿主动队列管理(delay compensation-active queue management,简称DC-AQM)算法,克服了大时滞给队列稳定性造成的不利影响.仿真实验结果表明,新算法在大时滞小期望队列长度的网络配置中表现出的综合性能明显优于已有的算法,链路利用率是其他算法的3～4倍.     

一种新的自适应RED算法

主动队列管理算法(RED)存在很多问题,如参数难以配置、对负载变化敏感等,为此采用控制理论的方法改进RED算法,提出一种基于比例控制的自适应RED算法,PRED。仿真结果表明该算法的稳定性好,队列的稳态值不受负载变化的影响。与已有的几种主动队列管理算法的性能比较表明,PRED算法的性能明显优于ARED,PI控制,DRED,SRED和REM几种算法。     

NOFC-VRTT:一种基于变RTT的非线性AQM算法

针对网络拥塞设计一种基于变往返时间的主动队列管理算法.给出了一种新的TCP窗口观测器,证明当丢包率取值范围在0～1之间时,TCP窗口观测值渐近收敛到TCP窗口真实值.通过反步设计法设计了一种非线性输出反馈控制算法,并给出了控制参数的取值范围.NS仿真表明,NOFC-VRTT算法具有较好的鲁棒性,较高的链路利用率和较低的丢包率,并且维持了各TCP源之间的公平性.     

基于非线性块反步控制的无人直升机航迹跟踪算法研究

针对小型无人直升机系统高度非线性、强耦合和易受内外部扰动干扰的特点,提出了一种非线性块反步控制与广义比例积分观测器相结合的控制策略。该方法采用广义比例积分观测器构建多阶观测回路对系统状态量、扰动量及扰动量的多阶导数进行估计,然后将扰动的估计值代入到直升机系统模型中,采用反步法回归递推得到直升机的跟踪飞行控制律。通过对阶跃信号和复杂“8”字形航迹的航迹跟踪仿真,结果表明：在多种内外部扰动影响下,所设计的控制律具有良好的动态响应和航迹跟踪性能以及抗干扰能力。相较于常规非线性扰动观测器,广义比例积分观测器对高阶和快速时变扰动具有更高的预估精度,可以达到更好的扰动抑制效果。     

基于模糊调节滑模面的TCP拥塞控制算法研究

基于模糊自适应滑模控制提出了一种拥塞控制算法。该算法通过模糊调节滑模表面使队列跟踪性能得到改善,对于网络模型的不确定性、网络参数的时变性以及非TCP适应流所引起的网络抖动该算法具有很强的鲁棒性。仿真结果表明该方法可以使队列长度快速收敛到设定值,同时使队列震荡最小,结果也表明在网络条件变化的情况下,该算法优于模糊控制和变结构控制。     

基于仿真的TCP拥塞控制研究

研究了几种不同的TCP拥塞控制算法原理。通过对于TCP Reno和TCP Vegas协议的实验仿真，研究在不同的数据流和不同的网络条件下算法的性能差异。提出了一种改进的RTT估计方法，在拥塞避免阶段，采用时延的指数滑动平均值取代瞬时的RTT。实验表明，这种改进增强了TCP Vcgas对于时延扰动的鲁棒性。     

TCP/AQM系统大时间尺度模型

网络传输连接的往返时延(round-trip times,RTT)大小各不相同,因此TCP/AQM系统本质为一多时滞回路耦合系统.由于RTT分布范围远大于控制量调节周期,这给准确评估控制效果带来很大困难.已有基于控制理论的主动队列管理(active queue management,AQM)算法多以流体流模型为基础进行设计,没有充分考虑RTT和采样周期对系统性能的影响.对于TCP/AQM系统,合理的评价方法是对调节过程进行评价,而非仅评价单个采样周期内的控制量是否合适.本文结合数据驱动控制思想和系统自身特征,统一从路由视角对TCP与AQM之间的交互进行抽象,通过时间扩展从更大的时间尺度去评价控制量调节过程,然后基于此模型设计自适应AQM算法–—大时间尺度AQM算法(large time scale AQM,LTSAQM).仿真结果表明,该算法收敛速度快,排队时延抖动小,特别是在长时滞网络环境下,性能明显改善.     

基于网络状态参数估计的主动队列管理PI改进算法

作为一种重要的主动队列管理手段,PI控制器算法通过积分嚣的引入有效地消除了队列长度控制的稳态误差,在提高网络吞吐的同时缩短了排队时延.但是PI控制器不能根据网络状态变化而自动调整控制参数,故当网络流量变化时PI控制器的收敛速度很慢.基于TCP-AQM系统模型,对经过中间节点的活动连接数、平均往返时间和前向链路容量等3个参数进行估计.通过计算击中概率的倒数,估计出活动流数;通过计算单位时间的数据包数,估计出网络容量;通过往返时延、活动流数、网络容量以及丢包概率在稳态时的关系式,估算出平均往返时延.在此基础上,提出了对网络状态变化自适应调整控制参数改进的快速收敛PI算法——FCPI算法.仿真结果表明,该算法有效提高了算法的收敛速度,并且鲁棒性好,易于实现,适用于未来高速网络的路由器.     

An Improved Link Model for Window Flow Control and Its Application to FAST TCP

This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones.      

电液比例位置同步线性自抗扰控制

电液比例位置同步液压系统受到元件安装精度、死区非线性以及系统参数摄动等因素的影响,导致两侧子系统性能不一致进而引起位置不同步.针对这一问题,提出由位置控制器、死区补偿器、同步控制器组成的复合控制方案.首先,建立电液比例位置控制系统数学模型,并分析系统内部参数摄动及比例阀死区特性对同步控制精度造成的影响.在此基础上,设计线性自抗扰同步控制器,实现对系统内外扰动的实时估计与主动补偿,同时为提高液压缸动态性能,减小稳态误差,设计了比例阀死区补偿器.仿真和实验结果表明,自抗扰控制器有效地抑制了内外扰动,提高了位置同步控制精度,而死区补偿器的引入改善了系统动态响应性能,降低了稳态位置同步误差.     

ATM网络模糊拥塞控制策略研究

ATM网络信息拥塞是制约网络发展的一个重要因素。本文针对单瓶颈节点网络,考虑两个饱和非线性因素,制定控制规则,寻找优化参数,设计模糊控制器。仿真结果表明在回路时延和可用带宽大幅波动的情况下,系统仍具有较好的控制效果,保证服务质量,进一步验证了算法的有效性。