Secure Authentication of WLAN Based on Elliptic Curve Cryptosystem

The security of wireless local area network (WLAN) becomes a bottleneck for its further applications. At present, many standard organizations and manufacturers of WLAN try to solve this problem. However, owing to the serious secure leak in IEEE802.11 standards, it is impossible to utterly solve the problem by simply adding some remedies. Based on the analysis on the security mechanism of WLAN and the latest techniques of WLAN security, a solution to WLAN security was presented. The solution makes preparation for the further combination of WLAN and Internet.     

Development of an Autonomous Flight Control System for Small Size Unmanned Helicopter Based on Dynamical Model

It is devoted to the development of an autonomous flight control system for small size unmanned helicopter based on dynamical model. At first, the mathematical model of a small size helicopter is described. After that simple but effective MTCV control algorithm was proposed. The whole flight control algorithm is composed of two parts: orientation controller based on the model for rotation dynamics and a robust position controller for a double integrator. The MTCV block is also used to achieve translation velocity control. To demonstrate the performance of the presented algorithm, simulation results and results achieved in real flight experiments were presented.     

Investigation of Wall Pressure Fluctuations in a Turbulent Boundary Layer by Large Eddy Simulation

Large eddy simulation (LES) was used to investigate the space-time field of the low Mach number, fully developed turbulent boundary layer on a smooth, rigid flat plate. The wall-pressure field simulated by LES was analyzed to obtain the pressure statistics, including the wall-pressure root-mean square, skewness and flatness factors, which show the wall pressure distribution was not Gaussian. The profile of the auto-power spectral density and the contour of the streamwise wavenumber-frequency spectral density of wall-pressure were plotted. The "convection ridge" can be observed clearly and the convection velocity can be calculated from the location of the convection peak.     

Study on Distributed Motion of Self-Reconfigurable Robot Based on Local Rules

The eigenvector of a module with six adjacent module's state was constructed according to self-reconfigurable robot M-Cubes and the configuration of system was expressed with the eigenvectors of all modules.According to the configuration and motion characteristics of the modules,a 3-dimension motion rule set was provided.The rule sets of each module was run according to eigenvector of the module after the motion direction of system decided and motion rules were selected.At last,the rapid and effective motion and metamorphosis were realized in system.The rule sets are operated on three systems and the distributed motion of system is fully realized.The result of simulation shows that the 3-dimension motion rule sets has perfect applicability and extensibility.The motion steps and communication load of the modules increase with the module number in linear.     

Design for Two-degree-of-freedom PID Regulator Based on Improved Generalized Extremal Optimization Algorithm

A kind of new design method for two-degree-of-freedom(2DOF)PID regulator was presented,in which,a new global search heuristic--improved generalized extremal optimization(GEO)algorithm is applied to the parameter optimization design of 2DOF PID regulator.The simulated results show that very good dynamic response performance of both command tracking and disturbance rejection characteristics can be achieved simultaneously.At the same time,the comparisons of simulation results with the improved GA,the basic GEO and the improved GEO were given.From the comparisons,it is shown that the improved GEO algorithm is competitive in performance with the GA and basic GEO and is an attractive tool to be used in the design of two-degree-of-freedom PID regulator.     

Wind Generator Stabilization with Doubly-Fed Asynchronous Machine

This paper investigates the function of doubly-fed asynchronous machine(DASM)with emphasis placed on its ability to the stabilization of the power system including wind generators.P(active power)and Q(reactive power)compensation from DASM can be regulated independently through secondary-excitation controlling.Simulation results by power system computer aided design(PSCAD)show that DASM can restore the wind-generator system to a normal operating condition rapidly even following severe transmission-line failures.Comparison studies have also been performed between wind turbine pitch control and proposed method.     

驾驶人“感知-决策-操控”行为模型

为准确模拟驾驶人跟车行为,提出基于隐马尔可夫模型(Hidden Markov Model,HMM)的驾驶人“感知-决策-操控”行为模型。建立描述驾驶意愿的HMM模型,模拟驾驶人感知过程,获得期望的车间距;预测模块模拟驾驶人根据交通环境和自身生理、心理状态预测车辆未来轨迹,即决策过程;优化模块描述驾驶人为使预测的车辆轨迹跟踪上期望的车辆间距而采取的操控汽车的执行动作,即操控过程。上述3个模块的滚动过程实现了对驾驶人跟车行为的模拟。利用自然驾驶数据进行算例分析,结果表明,本文模型预测车间距平均误差仅为1.47%,证明了所建模型的有效性及准确性。本文为驾驶行为建模方法的理论研究和应用拓宽了思路。     

Controller design for gating traffic control in presence of time-delay in urban road networks

Recent studies demonstrated the efficiency of feedback-based gating control in mitigating congestion in urban networks by exploiting the notion of macroscopic or network fundamental diagram (MFD or NFD). The employed feedback regulator of proportional-integral (PI)-type targets an operating NFD point of maximum throughput to enhance the mobility in the urban road network during the peak period, under saturated traffic conditions. In previous studies, gating was applied directly at the border of the protected network (PN), i.e. the network part to be protected from over-saturation. In this work, the recently developed feedback-based gating concept is applied at junctions located further upstream of the PN. This induces a time-delay, which corresponds to the travel time needed for gated vehicles to approach the PN. The resulting extended feedback control problem can be also tackled by use of a PI-type regulator, albeit with different gain values compared to the case without time-delay. Detailed procedures regarding the appropriate design of related feedback regulators are provided. In addition, the developed feedback concept is shown to work properly with very long time-steps as well. A large part of the Chania, Greece, urban network, modelled in a microscopic simulation environment under realistic traffic conditions, is used as test-bed in this study. The reported results demonstrate a stable and efficient behaviour and improved mobility of the overall network in terms of mean speed and travel time.     

Towards data-driven car-following models

Car following models have been studied with many diverse approaches for decades. Nowadays, technological advances have significantly improved our traffic data collection capabilities. Conventional car following models rely on mathematical formulas and are derived from traffic flow theory; a property that often makes them more restrictive. On the other hand, data-driven approaches are more flexible and allow the incorporation of additional information to the model; however, they may not provide as much insight into traffic flow theory as the traditional models. In this research, an innovative methodological framework based on a data-driven approach is proposed for the estimation of car-following models, suitable for incorporation into microscopic traffic simulation models. An existing technique, i.e. locally weighted regression (loess), is defined through an optimization problem and is employed in a novel way. The proposed methodology is demonstrated using data collected from a sequence of instrumented vehicles in Naples, Italy. Gipps’ model, one of the most extensively used car-following models, is calibrated against the same data and used as a reference benchmark. Optimization issues are raised in both cases. The obtained results suggest that data-driven car-following models could be a promising research direction.     

Socially optimal electric driving range of plug-in hybrid electric vehicles

This study determines the optimal electric driving range of plug-in hybrid electric vehicles (PHEVs) that minimizes the daily cost borne by the society when using this technology. An optimization framework is developed and applied to datasets representing the US market. Results indicate that the optimal range is 16 miles with an average social cost of $3.19 per day when exclusively charging at home, compared to $3.27 per day of driving a conventional vehicle. The optimal range is found to be sensitive to the cost of battery packs and the price of gasoline. When workplace charging is available, the optimal electric driving range surprisingly increases from 16 to 22 miles, as larger batteries would allow drivers to better take advantage of the charging opportunities to achieve longer electrified travel distances, yielding social cost savings. If workplace charging is available, the optimal density is to deploy a workplace charger for every 3.66 vehicles. Moreover, the diversification of the battery size, i.e., introducing a pair and triple of electric driving ranges to the market, could further decrease the average societal cost per PHEV by 7.45% and 11.5% respectively.