CAN-BUS系统应用一例

CAN-BUS系统自问世以来,已将近30年,当代各品牌车辆纷纷采用,但大部分技术人员对CAN总线系统既熟悉又陌生。经常能听到,但具体操作又显得有些力不从心。本文通过对奇瑞A3品牌轿车CAN总线的巧妙应用,引导大家进一步理解和应用CAN总线。     

基于WiMAX通信网络的电源监控系统的构建

分析了全球微波接入互存(WiMAX)的技术特点和算法复杂度,探讨了其在电源监控系统中的应用,提出了基于Inter WiMAX Connection 2250技术的远程电源监控系统。在讨论WiMAX物理层算法的基础上,确定了以正交频分多址(OFDMA)模式为主体的物理层通信协议,提高了信道的利用率,抑制了码间干扰,为构建电源监控系统打下了良好的基础。     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.     

Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Comparative evaluation of different statistical tools for the prediction of uniaxial compressive strength of rocks

In this study, uniaxial compressive strength (UCS), unit weight (UW), Brazilian tensile strength (BTS), Schmidt hardness (SHH), Shore hardness (SSH), point load index (Is₅₀) and P-wave velocity (V_p) properties were determined. To predict the UCS, simple regression (SRA), multiple regression (MRA), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) have been utilized. The obtained UCS values were compared with the actual UCS values with the help of various graphs. Datasets were modeled using different methods and compared with each other. In the study where the performance indice PI_at was used to determine the best performing method, MRA method is the most successful method with a small difference. It is concluded that the mean PI_at equal to 2.46 for testing dataset suggests the superiority of the MRA, while these values are 2.44, 2.33, and 2.22 for GEP, ANFIS, and ANN techniques, respectively. The results pointed out that the MRA can be used for predicting UCS of rocks with higher capacity in comparison with others. According to the performance index assessment, the weakest model among the nine model is P7, while the most successful models are P2, P9, and P8, respectively.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system

The intermittent wind power in isolated hybrid distributed generation (IHDG) may cause serious problems associated with frequency (f) and power (P) fluctuation. Energy storage devices such as battery, super capacitor, and superconducting magnetic energy storage (SMES) may be used to reduce these fluctuations associated with f and P. This paper presents a study of IHDG power system for improving both f and P deviation profiles with the help of SMES. The studied IHDG power system is consisted of wind turbine generator and diesel engine generator. Both f and P control problems of the studied power system model are addressed in presence or absence of SMES. Fuzzy logic based proportional–integral–derivative (PID) controller with SMES is used for the purpose of minimization of f and P deviations. The different tunable parameters of the PID controller and those of the SMES are tuned by a novel quasi-oppositional harmony search algorithm. Performance study of the IHDG power system model is carried out under different perturbation conditions. The results demonstrate minimum f and P deviations may be achieved by using the proposed fuzzy logic based PID controller along with SMES.     

Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

Structural failures (bridge or building collapses) and geohazards (landslides, ground subsidence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made structures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems.One of the most used techniques for real-time deformation monitoring is the Global Navigation Satellite System (GNSS) real-time procedure, where the relative positioning approach, using a well-known reference station, has been applied.This study was conducted to evaluate the actual quality of the real-time kinematic Precise Point Positioning (PPP) GNSS solution for deformation monitoring, where it can be concluded that a promise tool is under development and should be taken into account on actual and near future real-time deformation monitoring studies and applications.     

The concept of smartness in cyber–physical systems and connection to urban environment

The next-generation systems are expected to be largely cyber–physical systems (CPSs) that autonomously control physical processes, through sensors and actuators typically in real-time feedback and cooperative control loops distributed among physical and cyber environments. The rapid technological advancements enhance the smartness of these CPSs, pushing their boundaries of performance and efficiency by embedding new information and communication technologies. However, to what extent CPSs should be smarter so that they do not compromise safety and security of safety critical systems? is an open research question. Towards this goal, the purpose of this study is to establish a grounded theory to analyse what makes these systems smart? and eventually, how to find a balance between smartness and safety risks? In this precinct, this article aims to develop a conceptual framework, define the dimensions and derive the characteristics that make CPSs smart. The proposed approach combines an automated informetric and systematic analysis of literature pertinent to the topic of smartness across anthropology, science, engineering and technology. The analysis of a case study building and the discussions presented herein support the connection between the existing understanding of CPSs and smartness offered by the building design approach in urban environment.