Space station automation of common module power management and distribution, volume 2

The new Space Station Module Power Management and Distribution System (SSM/PMAD) testbed automation system is described. The subjects discussed include testbed 120 volt dc star bus configuration and operation, SSM/PMAD automation system architecture, fault recovery and management expert system (FRAMES) rules english representation, the SSM/PMAD user interface, and the SSM/PMAD future direction. Several appendices are presented and include the following: SSM/PMAD interface user manual version 1.0, SSM/PMAD lowest level processor (LLP) reference, SSM/PMAD technical reference version 1.0, SSM/PMAD LLP visual control logic representation's (VCLR's), SSM/PMAD LLP/FRAMES interface control document (ICD) , and SSM/PMAD LLP switchgear interface controller (SIC) ICD

A service-oriented approach to embedded component-based manufacturing automation

This thesis is focused on the application of Component-Based (CB) technology to shop oor devices using a Service Oriented Architecture (SOA) and Web Services (WS) for the purpose of realising future generation agile manufacturing systems. The environment of manufacturing enterprises is now characterised by frequently changing market demands, time-to-market pressure, continuously emerging new technologies and global competition. Under these circumstances, manufacturing systems need to be agile and automation systems need to support this agility. More speci cally, an open, exible automation environment with plug and play connectivity is needed. Technically, this requires the easy connectivity of hardware devices and software components from di erent vendors. Functionally, there is a need of interoperability and integration of control functions on di erent hierarchical levels ranging from eld level to various higher level applications such as process control and operations management services. [Continues.

Software package applications for designing rail freight interchanges

Ph.D. ThesisRail freight transport has a crucial role to play in the economy, delivering significant reductions in logistics costs, pollution, and congestion. Typically, the conventional architecture and layout of the rail freight interchange constrain the capacity and performance of the whole railway system. A well-designed rail freight interchange can enhance the system performance by maximizing vehicle usage and minimizing last mile distribution cost. Therefore, the study of rail freight interchange operation is considered crucial to understand how to increase and improve the attractiveness for rail freight transport. This thesis uses game engines to develop software packages that are used for the design of new rail freight interchanges, considering multistakeholder decisions drivers. A novel and modular approach has been applied with the purpose of developing and deploying simulation tools that can be used by multiple stakeholders to: -Understand the impact of multiple-criteria decision analysis on rail freight interchange layouts; -Use a genetic algorithm to identify the most suitable components of the future interchange to be designed, considering the multi-stakeholders’ priorities; - Quickly enable the design of a wide variety of rail freight interchanges from the information selected by a decision maker in a computer-based userfriendly interface. This research has proposed a framework for software development. Three case studies are used to illustrate adaptability of a number of applications for different scenarios. The findings of the research contribute to a better understanding of the impacts of the multiple stakeholder’s decisions on rail freight interchange designs. Key words: Rail Freight Interchanges, Multi stakeholders decision, genetic algorith

A Hybrid Method for Predicting Traffic Congestion during Peak Hours in the Subway System of Shenzhen

Traffic congestion, especially during peak hours, has become a challenge for transportation systems in many metropolitan areas, and such congestion causes delays and negative effects for passengers. Many studies have examined the prediction of congestion however, these studies focus mainly on road traffic, and subway transit, which is the main form of transportation in densely populated cities, such as Tokyo, Paris, and Beijing and Shenzhen in China, has seldom been examined. This study takes Shenzhen as a case study for predicting congestion in a subway system during peak hours and proposes a hybrid method that combines a static traffic assignment model with an agent-based dynamic traffic simulation model to estimate recurrent congestion in this subway system. The homes and work places of the residents in this city are collected and taken to represent the traffic demand for the subway system of Shenzhen. An origin-destination (OD) matrix derived from the data is used as an input in this method of predicting traffic, and the traffic congestion is presented in simulations. To evaluate the predictions, data on the congestion condition of subway segments that are released daily by the Shenzhen metro operation microblog are used as a reference, and a comparative analysis indicates the appropriateness of the proposed method. This study could be taken as an example for similar studies that model subway traffic in other cities. Document type: Articl

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Web service control of component-based agile manufacturing systems

Current global business competition has resulted in significant challenges for manufacturing and production sectors focused on shorter product lifecyc1es, more diverse and customized products as well as cost pressures from competitors and customers. To remain competitive, manufacturers, particularly in automotive industry, require the next generation of manufacturing paradigms supporting flexible and reconfigurable production systems that allow quick system changeovers for various types of products. In addition, closer integration of shop floor and business systems is required as indicated by the research efforts in investigating "Agile and Collaborative Manufacturing Systems" in supporting the production unit throughout the manufacturing lifecycles. The integration of a business enterprise with its shop-floor and lifecycle supply partners is currently only achieved through complex proprietary solutions due to differences in technology, particularly between automation and business systems. The situation is further complicated by the diverse types of automation control devices employed. Recently, the emerging technology of Service Oriented Architecture's (SOA's) and Web Services (WS) has been demonstrated and proved successful in linking business applications. The adoption of this Web Services approach at the automation level, that would enable a seamless integration of business enterprise and a shop-floor system, is an active research topic within the automotive domain. If successful, reconfigurable automation systems formed by a network of collaborative autonomous and open control platform in distributed, loosely coupled manufacturing environment can be realized through a unifying platform of WS interfaces for devices communication. The adoption of SOA- Web Services on embedded automation devices can be achieved employing Device Profile for Web Services (DPWS) protocols which encapsulate device control functionality as provided services (e.g. device I/O operation, device state notification, device discovery) and business application interfaces into physical control components of machining automation. This novel approach supports the possibility of integrating pervasive enterprise applications through unifying Web Services interfaces and neutral Simple Object Access Protocol (SOAP) message communication between control systems and business applications over standard Ethernet-Local Area Networks (LAN's). In addition, the re-configurability of the automation system is enhanced via the utilisation of Web Services throughout an automated control, build, installation, test, maintenance and reuse system lifecycle via device self-discovery provided by the DPWS protocol...cont'd

Development, Test and Evaluation of Autonomous Unmanned Aerial Systems in A Simulated Wide Area Search Scenario: An Implementation of the Autonomous Systems Reference Architecture

The implementation and testing of autonomous and cooperative unmanned systems is challenging due to the inherent design complexity, infinite test spaces, and lack of autonomy specific measures. These challenges are limiting the USAF\u27s ability to deploy and take advantage of tactical and strategic advantages offered by these systems. This research instantiates an Autonomous System Reference Architecture (ASRA) on a Wide Area Search (WAS) scenario as a test bed for rapid prototyping and evaluation of autonomous and cooperative systems. This research aims to pro- vide a framework to evaluate the system’s ability to achieve mission and autonomy objectives, develop reusable autonomous behaviors, and develop reusable cooperative decision making algorithms. For this research and application to the WAS mission, metrics of autonomy were derived from literature requirements for autonomous systems implementing reactive architectures and control: responsiveness, robustness, and perception accuracy. Autonomous behaviors, to include more complex behaviors combining simple (atomic) behaviors were developed, and a variety of cooperative decision rules were defined. The subsequent evaluation implemented a face centered cubic design of experiments over four scenarios including a single vehicle, and three levels of cooperation between two vehicles. Following a rigorous test plan, the tests were conducted in simulation implementing automated testing and expedited analysis. The test results were used to create a response surface model to characterize the system and conduct multiple response optimization to determine an optimal configuration that maximizes area searched, percent detected, and perception accuracy in a given target density