Intelligent leaky bucket algorithms for sustainable-cell-rate usage parameter control in ATM networks

In this paper, we propose two intelligent leaky bucket algorithms for sustainable-cell-rate usage parameter control of multimedia transmission in asynchronous transfer mode networks. One is the fuzzy leaky bucket algorithm, in which a fuzzy increment controller (FIC) is incorporated with the conventional leaky bucket algorithm; the other is the neural fuzzy leaky bucket algorithm, where a neural fuzzy increment controller (NFIC) is added with the conventional leaky bucket algorithm. Both the FIC and the NFIC properly choose the long-term mean cell rate and the short-term mean cell rate as input variables to intelligently determine the increment value. Simulation results show that both intelligent leaky bucket algorithms have significantly outperformed the conventional leaky bucket algorithm, by responding about 160% faster when taking control actions against a nonconforming connection while reducing as much as 50% of the queueing delay experienced by a conforming connection. In addition, the neural fuzzy leaky bucket algorithm outperforms the fuzzy leaky bucket algorithm, in aspects of three performance measures such as selectivity, responsiveness, and queueing delay, especially when the traffic flow is bursty, dynamic, and nonstationary.     

高速公路非线性反馈模糊逻辑匝道控制器

入口匝道控制是高速公路交通控制和智能运输系统的重要组成部分,但现有的入口匝道控制效果尚不理想.为此,本文提出一种非线性反馈方法用模糊逻辑进行入口匝道控制.建立了高速公路交通流动态模型,在此基础上,结合模糊逻辑理论设计了非线性反馈匝道控制器,根据密度误差和误差变化用模糊控制决定匝道调节率,模糊变量选用三角形隶属度函数,并制定了包含56条模糊规则的规则库,最后用MATLAB软件进行系统仿真.结果表明该控制器具有优越的动态和稳态性能,它能使高速公路主线交通流密度保持为设定的期望密度,该方法用在高速公路入口匝道控制中效果良好.     

交通信号公交优先控制策略及智能控制方法

针对公交优先交通信号控制问题,研究了公交优先的信号控制策略,提出了一种变论域模糊神经网络公交优先智能控制方法.提出了基于相位优先度值的公交优先相位选择方法,并给出了其数学描述.建立了绿灯时间的3层模糊控制模型,分别为红灯排队疏散时间、绿灯延长时间和论域调节因子模糊控制器,其中红灯排队疏散时间和绿灯延长时间两个模糊控制器的输出变量均采用变论域,论域的变化考虑混合交通、天气情况、车流转向等因素由论域调节因子模糊控制器确定.模糊控制器采用粒子群优化神经网络实现.仿真结果表明该方法具有较好的公交优先控制效果.     

基于模糊逻辑的高速网络自适应拥塞控制研究

基于模糊逻辑 ,利用自适应拥塞控制机制来预测高速网络 (如Internet中 )的拥塞问题 .把路由器的缓冲系统看作一个非线性离散动态系统 ,利用基于模糊逻辑的控制器来预测源端发送速率的确切值以防止拥塞的发生 .通过对参数向量的调节来估计无法预测的和具有统计波动性的网络通信量 ,并利用Lyapunov分析方法来验证闭环系统的稳定性 .最后 ,以一个仿真例子说明了所提出方法的有效性 .     

基于网络演算的智能交通流量分配研究

精确的交通流量分配计算模型,能为实际的交通工程应用提供具体的流量出入速率或者信号灯控制时间方案,具有重大价值。首次将动态交通流量分配拟化为网络负载均衡问题,使用漏桶理论和网络演算方法,将交通的流量分配与路径时延转换为一系列极值运算,结合贪婪算法,以均衡网络延时为优化目标,得到交通配流。仿真结果表明,本模型在化解拥堵的同时,使分流后的道路平均延时普遍降低,能提升整体路网的通行能力。     

一种新型嵌入式网络信号机研究与设计

交通信号机是智能交通系统的基础之一,为了满足信号机的网络化和智能化的要求,研究并提出了一种新型的嵌入式网络信号机,该信号机的硬件结构采用ARM和CPLD,以触摸屏为基础采用QT/Embedded设计了人性化的人机接口,信号机支持多种通信接口,其协议采用XML予以定义;为了避免绿冲突,以两级模式进行冲突判断;单点模糊控制机制的设计能够适应动态的交通流状况,有效提高交叉口的通行能力;连接交通仿真软件,模拟实际路口,实验显示该信号机工作稳定,性能优越。     

模糊控制在智能交通灯监控系统中的应用

为了解决拥挤的城市交通问题,针对交通灯监控系统中可变的交通状况,提出一种基于模糊算法的监控系统。应用模糊算法,通过模糊控制实现交通灯的控制,使道路通畅。对监控系统进行分析,合理选择模糊控制器的结构,根据动态的车流量,通过模糊算法分配当前车道的通行时间,并全面考虑同时通行的各种车道组合。该监控系统提高了车辆通行效率,使道路更为通畅。与传统的固定配时系统相比,它更适于当前纷繁复杂的交通状况。     

基于动态目标位置的智能车辆动态避障控制研究

为了真实地模拟驾驶员在动态环境中避让动态障碍物的行为方式,提出了动态目标位置概念,并采用三次样条曲线作为动态避障的路径拟合曲线。以模糊逻辑为控制策略,以T-S模糊模型为控制结构,以自适应神经网络为隶属度函数的参数调整手段,设计出一种智能车辆横向运动控制器,并通过计算机仿真实现。结果表明,基于动态目标位置概念的控制器设计具有较好的控制性能,较为理想地模拟实际交通环境中车辆动态避障的特性。     

A hop-by-hop flow controller for a virtual path

In this paper, we propose a hop-by-hop robust controller for the flow regulation of the best-effort (ABR) traffic along a virtual path (VP) in high-speed networks. The local controller at each VP switch can regulate the transmission rate of virtual connections (VCs) based on the knowledge of the buffer occupancy in downstream VP switches. The fluid-flow model is used to design the hop-by-hop congestion controller, and used to study dynamic and steady behaviors of the network. A condition for the network's stability is derived. It is shown that with this controller applied, the network is asymptotically stable without oscillation. It is also shown that the proposed controller can achieve fairness and high utilization, and reduce the overhead traffic.     

MULTITUNING FUZZY CONTROL SYSTEMS DESIGN

A multituning fuzzy control system structure that involves two simple, but effective tuning mechanisms, is proposed: one is called fuzzy control rule tuning mechanism (FCRTM); the other is called dynamic scalar tuning mechanism (DSTM). In FCRTM, it is used to generate the necessary control rules with a center extension method. In DSTM, it contains three fuzzy IF-THEN rules for determining the appropriate scaling factors for the fuzzy control system. In this paper, a method based on the genetic algorithm (GA) is proposed to simultaneously choose the appropriate parameters in FCRTM and DSTM. That is, the proposed GA-based method can automatically generate the required rule base of fuzzy controller and efficiently determine the appropriate map for building the dynamic scalars of fuzzy controller. A multiobjective fitness function is proposed to determine an appropriate parameter set such that not only the selected fuzzy control structure has fewer fuzzy rules, but also the controlled system has a good control performance. Finally, an inverted pendulum control problem is given to illustrate the effectiveness of the proposed control scheme.     

基于城市区域路网的分散协调控制研究

根据城域多路口交通系统的特点,摒弃统一信号周期的方法,以各单路口为基点,采用分散协调控制策略,综合考虑各相邻路口及两路口间的交通流,实时控制各路口交通信号,并智能的加以协调,使区域内道路的交通通行能力得到提高,降低车辆的延误时间。为提高系统的控制精度和鲁棒性,采用神经网络技术实现模糊控制。仿真结果表明,该方法控制效果良好。     

Development of a fuzzy logic traffic system for isolated signalized intersections in the State of Kuwait

In a conventional traffic signals controller, the lights change at constant cycle time. In many cities, automatic traffic signals are often based on a constant green-to-red cycle. The time period for green light (or red light) to be on is determined based on a stochastic model. The traditional vehicle-actuated control of isolated intersections attempts continuously to adjust green times. The decision to change green light duration involves fuzzy factors that cannot be precisely determined.The main objective of this paper is to develop a fuzzy logic traffic system that considers the two two-way intersections and is able to adjust changes in time intervals of a traffic signal based on traffic situation level.The proposed system has been applied and tested using real data collected from signalized intersection in Hawalli governorate in the State of Kuwait. Twenty-seven iterations have been done; the results show that the proposed fuzzy logic traffic system provides better performance in terms of total waiting time, total moving time, and vehicle queue. Finally, it can be observed from the results that the proposed system can be used to accelerate the cycle time and to give other phases the chance to gain more benefit from the green time lost.     

A fuzzy approach to active usage parameter control in IEEE 802.11b wireless networks

Abstract: Usage parameter control (UPC) provides support for quality of service across heterogeneous networks. For the network operator UPC assists in limiting network usage through traffic shaping, to prevent unacceptable delay. Traditional methods to apply UPC involve the generic cell rate algorithm or ‘leaky bucket’ algorithm, now commonly implemented in asynchronous transmission mode networks. This paper proposes a novel form of UPC for 802.11b wireless networks. The method proposed measures the rate of individual network flows to actively manage link utilization using a fuzzy logic controller (FLC). The FLC monitors the flow rate and adjusts the sending transmissions to stabilize flows as close to the optimum desired rate as possible. Imposing UPC and using the FLC within a packet switched TCP network enforces cooperation between competing streams of traffic. After carrying out experiments within a wireless network, the results obtained significantly improve upon a ‘best effort’ service.     

基于变论域模糊增量理论的质子交换膜燃料电池温度控制

质子交换膜燃料电池(PEMFC)内部的电化学反应过程直接表现为温度的变化,所以有效的温度控制是保证燃料电池可靠性和耐久性的关键.本文将模糊增量控制用于PEMFC热管理系统中,将PEMFC的温度和电堆出入口温度差保持在设定值.首先,建立PEMFC热管理系统的动态模型,包括PEMFC电堆模型和辅助散热设备模型.然后,基于建立的系统模型,设计了一种变论域的模糊增量控制器.该控制器通过伸缩因子来动态调节模糊控制器中的量化因子和比例因子,实现对模糊论域的调节,从而提高控制的灵敏性和精确度.最后,将该温度控制方法用于10 kW燃料电池系统中,实验结果表明变论域模糊增量控制器相比于其他模糊控制方法,不仅具有更快的动态响应速度,还具有更强的鲁棒性和更高的控制精度.     

Dynamic switching based fuzzy control strategy for a class of distributed parameter system

In this work, a dynamic switching based fuzzy controller combined with spectral method is proposed to control a class of nonlinear distributed parameter systems (DPSs). Spectral method can transform infinite-dimensional DPS into finite ordinary differential equations (ODEs). A dynamic switching based fuzzy controller is constructed to track reference values for the multi-inputs multi-outputs (MIMO) ODEs. Only a traditional fuzzy logic system (FLS) and a rule base are used in the controller, and membership functions (MFs) for different ODEs are adjusted by scaling factors. Analytical models of the dynamic switching based fuzzy controller are deduced to design the scaling factors and analyze stability of the control system. In order to obtain a good control performance, particle swarm optimization (PSO) is adopted to design the scaling factors. Moreover, stability of fuzzy control system is analyzed by using the analytical models, definition of the stability and Lyapunov stability theory. Finally, a nonlinear rod catalytic reaction process is used as an illustrated example for demonstration. The simulation results show that performance of proposed dynamic switching based fuzzy control strategy is better than a multi-variable fuzzy logic controller.     

Dynamic Fuzzy Controlled RWA Algorithm for IP/GMPLS over WDM Networks

This paper proposes a dynamic RWA scheme using fuzzy logic control on IP/GMPLS over WDM networks to achieve the best quality of network transmission. The proposed algorithm dynamically allocates network resources and reserves partial bandwidth based on the current network status, which includes the request bandwidth, average utilization for each wavelength and its coefficient of variance (C.V.) of data traffic, to determine whether the connection can be set up. Five fuzzy sets for request bandwidth, average rate and C.V. of data traffic are used to divide the variable space: very large (LP), large (SP), normal (ZE), small (SN), and very small (LN). Setting the fuzzy limit is a key part in the proposed algorithm. The simulation of scenarios in this paper has two steps. In the first step, the adaptive fuzzy limits are evaluated based on average transmission cost pertaining to ten network statuses. The second step is to compare the proposed algorithm with periodic measurement of traffic (PMT) in ATM networks in six network situations to show that the proposed FC-RWA algorithm can provide better network transmission.     

模糊反馈控制实时调度算法

为了解决模糊不确定任务集在不可预测环境下的动态抢占调度问题,应用模糊规则和模糊调度理论,提出一个基于模糊反馈控制的调度算法,并建立相应的调度架构.该架构由基本调度器和模糊反馈控制两部分组成.用模糊调度算法作为基本调度器的调度算法,将任务集按不同优先级等级进行划分,优先级等级高的任务优先调度,从而使得更多的重要任务得到调度;模糊控制器与任务流调节策略一起构成模糊反馈控制部分.仿真结果表明,模糊反     

Discrete time analysis of leaky-bucket congestion control

Traffic control at an ATM multiplexer is of fundamental importance in B-ISDN. Due to the presence of large propagation delay, effective traffic control tends to use only local information. Leaky bucket has been introduced as a rate control method. The present paper studies the system performance of a leaky bucket controller with the arrivals being Poisson processes or Markov modulated Poisson processes (MMPP). Numerical results indicate that a small to medium sized controller is sufficient to attain the capability of a leaky bucket controller; increasing the size of the controller will not offer much improvement in performance. Controlling MMPP type of arrivals with a leaky bucket device may incur low performance especially when the burst duration is long. The performance can be improved by controlling a group of bursty users instead of a single bursty user.     

A new model-free adaptive sliding controller for active suspension system

Active suspension systems are designed to provide better ride comfort and handling capability in the automotive industry. Since the active suspension system has nonlinear and time-varying characteristics, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, a functional approximation (FA) based adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The FA technique is employed to represent the unknown functions, which releases the model-based requirement of the sliding mode control. In addition, a fuzzy control scheme with online learning ability is employed to compensate for the modeling error of the FA with finite number of terms for reducing the implementation difficulty. To guarantee the control system stability, the update laws of the coefficients in the approximation function and the fuzzy tuning parameters are derived from the Lyapunov theorem. The proposed controller is employed on a quarter-car active suspension system. The simulation results and experimental results show that the proposed controller can suppress the oscillation amplitude of the sprung mass effectively. To evaluate the performance improvement of inducing a fuzzy compensator in this FA adaptive controller, the dynamic responses of the proposed hybrid controller are compared with those of FA-based adaptive sliding controller only.     

基于模糊理论的高速公路递阶控制

将递阶结构和模糊控制用于高速公路多匝道的协调控制,协调控制器采用多输入-多输出的模糊控制方法协调确定相邻路段的匝道入口调节率;各路段根据协调控制器给定的匝道入口调节率,利用单匝道模糊控制器将系统状态保持在给定的标称点范围内。给出了分层控制系统的结构和控制算法,并在交通仿真软件PARAMICS上进行了仿真实现。仿真结果表明,该方法能够有效地消除交通拥堵,维持主线车流稳定。