Showing papers in "Intelligent Automation and Soft Computing in 2010"

Microgrids And Distributed Generation

Abstract: Application of individual distributed generators can cause as many problems as it may solve. A better way to realize the emerging potential of distributed generation is to take a system approach which views generation and associated loads as a subsystem or a “microgrid”. The sources can operate in parallel to the grid or can operate in island, providing UPS services. The system will disconnect from the utility during large events (i.e. faults, voltage collapses), but may also intentionally disconnect when the quality of power from the grid falls below certain standards. Utilization of waste heat from the sources will increase total efficiency, making the project more fmancially attractive. University of Wisconsin Laboratory verification of microgrid control concepts are included.

Estimating winter wheat biomass and nitrogen status using an active crop sensor

Abstract: Plant biomass and nitrogen status are important factors to consider when making in-season crop management decisions. Traditional sampling and analysis are time-consuming, labor-intensive and costly. It is desirable to estimate these parameters nondestructively using remote sensing technology. The objective of this study is to evaluate the potential of using an active crop canopy sensor, GreenSeeker, for estimating winter wheat biomass, nitrogen concentration and uptake in North China Plain. A total of 13 field experiments involving different N rates, varieties and sites were conducted from 2004 to 2007 in Shandong Province, China. In addition, data from 69 farmer’s fields were also collected to further evaluate the sensor’s potential application under on-farm conditions. The results indicated that across sites, years, experiments and growth stages, normalized difference vegetation index became saturated when biomass reached 3736 kg ha, or when plant nitrogen uptake reached 131 kg ha. Ratio vegetation index was linearly related with winter wheat biomass and plant nitrogen uptake and did not show obvious saturation effect. However, none of the two vegetation indices performed well for nitrogen concentration estimation. We conclude that RVI should be selected when using the GreenSeeker crop sensor to estimate winter wheat biomass or N uptake across sites, years and growth stages. The NDVI index can also be used before plant biomass and N uptake reach threshold values. More research is needed to further evaluate the results under more diverse conditions, and develop strategies of using the GreenSeeker 1220 Intelligent Automation and Soft Computing active sensor for diagnosing crop growth and N status and making in-season management decisions, especially under high-yielding conditions.

An Overview Of Microgrid Control

Abstract: A MicroGrid can be defined as an electrical network of small modular distributed generating units (whose prime movers may be photovoltaics, fuel cells, micro turbines or small wind generators), energy storage devices and controllable loads. A MicroGrid can operate in grid-connected or islanded mode and hence increase the reliability of energy supplies by disconnecting from the grid in the case of network faults or reduced power quality. The techniques that have been investigated to control MicroGrids in both modes are summarized as well as those proposed to maintain stability during the transitions from one mode to the other. Peer-peer control is contrasted with master-slave and the various approaches of droop control are discussed. The importance of energy storage to assist stability during transition between the operating modes is emphasised.

Optimal Car Dispatching For Elevator Groups Using Genetic Algorithms

Abstract: The caz dispatching problem in an elevator group consists of assigning cars to the hall calls at the same time that car call are served. The problem needs to coordinate the movements of individual cars with the objective of operating efficiently the whole group. In this paper, we propose an elevator group control system based on a genetic algorithm which makes use of a novel fitness function to evaluate the individuals. The fitness function allows a quick execution of the algorithm. Tests are provided forvarious types of high-rise buildings to assess the elevator service performance. Comparative simulations show that our genetic algorithm outperforms traditional conventional algorithms developed in the industry. It is important to note that the algorithm is quickly evaluated allowing areal-life implementation.

Small Signal Stability Of A Microgrid With Parallel Connected Distributed Generation

Abstract: Distributed Generation, or DG, involves utilization of small generators that are distributed in a power network, to supply the electric power demands of utility customers. This paper presents the small signal analysis of droop based generation control schemes for pazallel connected DG inverters comprising of active power-frequency and reactive power-voltage controllers. Small-signal models aze developed for microgrids consisting of several DGs connected in a parallel configuration. Mathematical propositions that develop sufficiency conditions for stability of the system are developed.

Multi-Level Optimization Of Negative Selection Algorithm Detectors With Application In Motor Fault Detection

Abstract: This paper proposes amulti-level optimization strategy for the Negative Selection Algorithm (NSA) detectors, based on both the Genetic Algorithms (GA) and clonal selection principle The NSA is a natural immune response-inspired pattern discrimination method In our hierazchical optimization scheme, the NSA detectors are fast optimized by the GA to occupy the maximal coverage of the nonself space Next, these detectors are further fine-tuned and optimized using the Clonal Selection Algorithm (CSA) so as to achieve the best fault detection performance This novel NSA detectors optimization approach is also examined with artificial data and a practical motor fault detection example

Intelligent load control for frequency regulation in MicroGrids

Abstract: During autonomous operation, MicroGrids may suffer large fluctuations in frequency due to the mismatch between load and local generation. The available spinning reserve might not always be enough to provide the required frequency support. Control of non-critical loads is able to provide the required primary and secondary frequency support. The use of Intelligent Load Management Controllers (ILMC) installed at consumer nodes is investigated. The ILMC units use fuzzy logic to determine the shedding and the restoration frequencies for non-critical loads based on the current power measurement and the history of disconnection. The fuzzy rules were chosen to achieve high reliability and equity between consumers.

An Intelligent System Based On Adaptive CTBN For Uncertainty Reasoning In Sensor Networks

Abstract: ;onsisting of various sensing and computing devices deployed in a changing environrnent, a sensor network’s raw sensed data have many uncertainties. A natural way to deal with them is generating belief messages. Sensing objects continuously change with time, so are their beliefs. Therefore, dynamic models are required to monitor distributed states in the system. This paper presents a CTBN based intelligent system for modeling dynamics and processing uncertainties in sensor networks. Algorithms for message passing and parameter updating for adapting the model to the changing environrnent are provided. The effectiveness of the system is shown in experiments.

Adaptive Authentication And Registration Key Management Scheme Based On AAA Architecture

Abstract: The demand for mobile communications has been increasing significantly while inducing more challenges to security issues, especially in authenticating mobile hosts. In order to provide secure communications in mobile networks, the Authentication, Authorization, and Accounting (AAA) architecture is currently in use within the Internet access service. The AAA architecture is used to establish authentication between the communication hosts. However, the current azchitecture has an inefficient authentication procedure when a mobile host hands off from a home domain to foreign domains because the architecture assumes that the only reliable source of authenticating the mobile host is the AAA server located in the home domain. This problem becomes more significant when the mobile host traveling far way from its home domain establishes a mobility security association with mobility entities. To solve these problems, we propose in this paper an adaptive authentication and registration key management scheme...

Control of nuclear research reactors based on a generalized hopfield neural network

Abstract: ABSTR4CT-The purpose of tliis paper is to prcsellt a solution to the n~ininlization prohlenl of the transient time to accomplish the switching hetween different levels of power in a nuclear research reactor satislying the inverse period cons~rairtt and avoiding to use any physical model of the plant. 'l'be strategy liere proposed consists of two stazes. first. the optinul trajectory which satisfies the constraint is calculated 00-line: second. a control law based on a generalized Hopfield neuml network is employed to assure that the reactor power l'ollows this optimal tra,iectory. The boundedness Ibr both the weights and the identification error is guaranteed by a new online learning law. Likewise, proposed control law guarantees an nppr bound for the tracking error. The elfbclive~iess of this procedure is illustrated by numeric sinlularion.

Fume Suppression Agents For Environmental-Friendly Asphalt Pavement

Abstract: According to the impact of fumes generated by asphalt pavement construction under poor air ventilation conditions on environrnent and operators at pavement construction and mechanism of asphalt fumes generation this article provides the method of addition of addictives in asphalt to suppress fumes due to asphalt pavement construction. Through in house test the variation law of asphalt fames with heating temperature and heating time. The result shows that with an increase of heating time, the yield of asphalt fumes appears increasing tendency. During the initial stage, the smoke yielding rate is fast; in later stage the vaziation slows down; and finally the variation becomes stable. With higher heating temperature, the yield of asphalt fumes is greater. Paztial addictives aze selected for smoke suppression effect test from flame retardant agent, plastic smoke suppression agent, physical adsorbent, polymer modified agent and aging resistant agent. SBS and manometer calcium carbonate compound type m...

Study of a microgrid with vehicle-to-grid sources during network contingencies

Abstract: A MicroGrid without a central fast-acting controller or a central energy storage unit was considered in order to establish the problems of a MicroGrid using traditional technology and to identify the additional benefits which could be derived by installing supplementary hardwaze (i.e. energy storage and central control). In view of the fast expanding electric drive vehicle market, fuel cell cars were considered as a combined micro-source/energy storage unit along with Photovoltaic units. Simulation results aze presented. The study highlights that voltage regulation is critically important in a MicroGrid, there are still substantial challenges in the design of control for renewable sources in such systems and energy storage is crucial for successful operation of any MicroGrid, though such storage may be distributed throughout the system. It was established that electric vehicles or plug-in-hybrids could be highly suitable due to the fast charge/dischazge chazacteristic of on-board storage.

A Robust Fuzzy Clustering Approach and its Application to Principal Component Analysis

Abstract: A robust fuzzy clustering approach is proposed to simplify the task of principal component analysis (PCA) by reducing the data complexity of an image. This approach performs well on function curves and character images that not only have loops, shazp corners and intersections but also include data with noise and outliers. The proposed approach is composed of two phases: fustly, input data are clustered using the proposed distance analysis to get good and reasonable number of clusters; secondly, the input data are further re-clustered by the proposed robust fuzzy c-means (RFCM) to mitigate the influence of noise and outlier data so that a good result of principal components can be found. Experimental results have shown the approach works well on PCA for both curves and images despite their input data sets include loops, corners, intersections, noise and outliers.

L 2 -Stability Analysis Of Proportional Takagi-Sugeno Fuzzy Controller Based Control Systems.

Abstract: In this paper, the mathematical properties of the proportional TakagiSugeno (T-S) fuzzy controller are first investigated. Based on these properties, the L2stability of the fuzzy control systems, in which the proportional T-S fuzzy controller is utilized, is analyzed by using the well-known circle criterion. A sufficient condition with elegant graphical explanation in the frequency domain is next derived to guarantee the L2stability of the fuzzy control systems. Finally, the proposed sufficient condition is examined with two numerical simulations.

Device authentication in wireless and pervasive environments

Abstract: Security can only be guaranteed as long as the hardwaze and other key parameters, including software components, secret keys etc, of a device remain genuine and unrnodified. Under this context, device authentication must be considered as a key security issue, complementary and of equal importance to user authentication, in today’s wireless and forthcoming ubiquitous realms. This paper classifies and analyses possible major solutions proposed until now towazds solving the device authentication issue. We constructively argue on each solution presented examining its advantages and disadvantages. A qualitative comparative analysis for the device authentication schemes in question is also offered, probing its applicability for both infrastructure and ad-hoc deployments. Inter-domain device authentication, where applicable, and users’ privacy as aside-effect are investigated as well.

Estimation Of Passenger Waiting Time In Elevator Systems With Artificial Neural Network

Abstract: In this study, a simulation program for elevator control system with 10 floor apartment with 300 people was prepared by using C++ builder programming language. In simulation program, the cabin was controlled with both artificial neural network (ANN) and traditional methods under 10 different variable speeds with constant acceleration. In the program, the number of passenger and their waiting times were multiplied and applied to ANN inputs as degrees of weight. Thus, the waiting time of passengers has been added to control algorithm which is different from traditional control methods. With the suggested system, the cabin was directed to floor that has the most weighted grade. Consequently, passenger’s waiting time was scattered for each floor in balanced manner. Moreover the cabin travel time and passengers waiting time have been decreased by about 18%using suggested method for up peak traffic situation.

Conserving bandwidth in a wireless sensor network for telemedicine application

Abstract: Telemedicine aided by wireless sensor networks (WSN) has recently become a healthcare trend. Many previous studies have adopted the ZigBee-based WSN to implement a platform and/or a telemedicine system. However, the low data rate and bandwidth have limited the maximum number of nodes in a WSN during continuous and simultaneous transmission. The issue of low data throughput has not been addressed in previous reseazch. In this study, we propose an arrhythmia-aware system, and a new DSPbased WSN platform is developed for the high compression performance of physiological data in a ZigBee-based WSN. Proven by simulations and several real tests, the combination of the proposed platform and the sensor nodes can lead to more bandwidth conservation and extend the WSN scale for the next generation of telemedicine system.

Context-aware workflow management for intelligent navigation applications in pervasive environments ♠

Abstract: Pervasive computing is auser-centric distributed computing paradigm, allowing users to access their preferred services even while moving around. To make this vision a reality, context-aware workflow management is one of key issues because the context of pervasive applications is changing dynamically. In this paper, we propose a context model for intelligent navigation applications and then present acontext-aware workflow management algorithm (CAWM) which can adaptively adjust workflow execution behaviours based on current context information. The correctness of the CAWM algorithm has been also verified theoretically by formulating it as a Petri-net model. Furthermore, the proposed context model and workflow management algorithm can apply to other applications by simply revising the corresponding context structures only.

Fatigue Cumulative Damage Evaluation Based On Smart Stay Cables

Abstract: Stay cables are one of the most critical structural components of cable-stayed bridge. However, stay cables readily suffer from fatigue damage, corrosion damage and their coupled effects. Thus, health monitoring of stay cables is important for ensuring the integrity and safety of a bridge. The application of the smart stay cables on the Tianjin Yonghe Bridge is demonstrated and the vehicle fatigue load effects smart stay cables are evaluated based on field monitoring data. Secondly, based on fatigue test results of corroded wires obtained from dissection of actual parallel wire cables which were used on Tianjin Yonghe cable-stayed bridge, the fatigue properties of corroded cable are investigated by the method of Monte Cazlo simulation. The results of fatigue lives and corrosion degree of corroded wire are presented. Comparisons between the original design information and fatigue test results, it can be seen that corrosions make the fatigue lives of wires decreasing sharply and the cable fatigue l...

Routing Protocol With Scalability, Energy Efficiency And Reliability In WSN

Abstract: The world around us will soon be interconnected as a pervasive network of intelligent devices. Through this, people will be able to get online and have almost continuous access to their preferred services. WSN (Wireless Sensor Networks) is the emerging technology expected to prevail in the pervasive computing environrnent of the future. Geographic routing protocol is an attractive localized routing scheme for wireless sensor networks because of its directional routing properties and scalability. Sensor nodes are highly energy-constrained. Also, sensor nodes can be deployed in a hostile condition. This is the reason why we have to consider not only the energy but also the wireless link condition. In this paper, we propose a geographic routing scheme considering the wireless link condition. If wireless link condition is not considered, the node which is at the end distance of the transitional region where packets can be received with errors can be selected as the next hop. This draws out retransmis...

Fuzzy-Based Filtering Solution Selection Method For Dynamic Sensor Networks1

Abstract: In wireless sensor networks, adversaries can compromise sensor nodes and use them to inject forged reports, which can lead to false alarms and energy depletion. Recently, several reseazch solutions have been proposed to detect and drop such forged reports during the forwarding process. Since each of them has its own energy consumption characteristics, employing only a single filtering solution for a network is not a recommended strategy, in terms of energy savings. While a technique for the adaptive selection of filtering solutions has been proposed, it considers only static networks. This paper presents afuzzy-based filtering solution selection method for dynamic sensor networks. In order to save energy, a fuzzy rule-based system chooses between two filtering solutions and controls detection power by considering network status. The effectiveness of the proposed method is shown by the simulation results described in the final pazt of the paper.

Elevator dispatching using heuristic search

Abstract: Monitoring and prediction of passenger movements are able to generate timely heuristic information that reduces the complexity of the elevator dispatching task to one of finding the best route through already computed data. This paper demonstrates that such information, when used by heuristic search techniques, allows optimal dispatching solutions to be achieved in a practical elevator installation. Results are also included to demonstrate that a new search approach, when considered alongside existing well-known search methods, compares favorably in its application to real elevator dispatching problems.

Study On Regularity Of Fumes Emitting From Asphalt

Abstract: A large number of poisonous asphalt fames are emitted into environrnent during the mix and compaction process on the pavement placement, which pollute environrnent and do harm to people’s health In this paper, the regularity of emitting fumes from asphalt and the effect of suppressing smoke with additives on asphalt were investigated. The results showed that the amount of fumes emitted was related to temperature, thickness and surface area of the asphalt; the amount of fumes was reduced by using melamine, polyethylene, and activated carbon additives respectively, and good effects were achieved It has great significance on improving working condition on the pavement placement and promoting the construction of environrnent-friendly society.

A Study On Addictives For Fume Reduction In Asphalt Pavement Construction

Abstract: In the construction process, asphalt pavement will generate a lot of asphalt fumes, which contain a large number of toxic and hazardous substances that will produce injury to the construction workers and residence around. In order to radically reduce asphalt fumes in the construction process, through self-designed test equipment, we added SBS (Styrene Butadiene Styrene), melamine and activated carbon which may have fumes suppression effect to the asphalt and experimented, obtained: (1) SBS which had fumes suppression effect, could be used as an additive to reduce asphalt fumes; (2) Melamine and activated carbon, which would produced a number of side effects, could not be used as an additive to reduce asphalt fume. At present the research of modified asphalt which produces lower fumes is basically still in a blank state, but the paper will fill the gaps in this aspect and provide a test device and method to study on modified asphalt with low fumes.

Online Public Key Cryptographic Scheme For Data Security In Bridge Health Monitoring

Abstract: the paper proposes an online-public-key cryptographic scheme for data security in bridge health monitoring. The scheme solves the problem such as how to preserve and manipulate the users’ private key securely. Meanwhile, it realizes the mutual authentication between user and server, in which the private key splitting method is proven to be secure in the RO model. The analysis shows that the scheme is able to resist the normal attacks such as the denial of service or the off-line password guess effectively. It has strong robustness in applications.

Lyapunov Exponent Analysis On Real-Time Monitoring Information Of Extractive Structure Health Based On Chaos Time Sequence

Abstract: The article has made a maximum Lyapunov exponent analysis of ASCE Benchmark and the health monitoring data of Chongqing Masangxi Bridge using non-linear theory and chaos time sequence. The maximum Lyapunov exponents in the two kinds of structural monitored data are both over zero, indicating that in the structural system chaos phenomenon has appeared. Meanwhile, experiments have shown that the maximum Lyapunov exponent is sensitive of the amount of samples and the time delay. So, to compute the chaos index, the amount of samples and the time duration are of importance.

Document Classification Using Information Theory And A Fast Back-Propagation Neural Network

Abstract: In this paper, a fast back-propagation neural network is developed to build document classifiers and the information gain method is used for feature selection. According to the rank of the information gain of all the words contained in the documents, those words that contain more information to classify the documents aze selected as the input features of the artificial neural network (ANN) classifiers. The neural network developed assumes athree-layer structure with a fast back-propagation learning algorithm. Because of the information contained in the vectors selected, the learning efficiency of the developed ANN is very high. For the output of the ANN, Shannon entropy is used to tune the threshold of the binazy classifiers. The classifiers are tested using the Reuters corpus. Two performance measures aze used to evaluate the performance of the classifiers and generally the results of this study are better than those claimed in literature.

Bi-Parameters Method For Structural Vulnerability Analysis

Abstract: Vulnerability originally means the susceptibility of a system to damage. In civil engineering, structural vulnerability can be defined as the susceptibility of structural performance to local damage. This paper studied the quantitative analysis method on structural vulnerability. The proposed method bases on two parameters, the influence of damage scenazio to structural performance, and the proportion of the damage scenario in the overall structural system. By using these two parameters, the vulnerability of a structure can be quantitatively evaluated for different damage degree under a certain damage scenario, or for different damage degree under different damage scenarios.

Pso-Based Real-Time Scheduling For Elevator Group Supervisory Control System

Abstract: Elevator group supervisory control system (EGSCS) is an important and essential component in an industrial elevator system. This paper will introduce particle swarm optimization (PSO) as a heuristic intelligent search method to optimize in real time elevator traffic scheduling solution of EGSCS. The proposed PSO-based scheduling approach will be applied to effectively handle the peak elevator traffic. The overall experimental results will be used to validate its scheduling efficiency and effectiveness.

A Proxy-Based System For Dynamic Content Negotiation And Collaborative Optimization In Heterogenic Environments

Abstract: Ubiquitous and Pervasive Computing relies on ubiquitous network access and applications’ context-awareness. This pervasive access implies exchanging traffic with a wide spectrum of devices across heterogenic networks. Services and applications deployed on these networks should adapt its operation and presentation to the characteristics of the underlying network technologies and the actual client device capabilities. Cellulaz wide azea networks like UMTS are used as Internet access networks for particular users but, in some cases, they can also be employed to provide Internet access to other smaller networks. The main inconvenient is that cellular networks have not the same bandwidth as wired networks and therefore, the cellular channel becomes a network bottle-neck. To help to mitigate this situation and in order to improve the user’s experience different optimization techniques exist, especially in web traffic. This paper studies the existing synergies at HTTP layer between device capabilities e...