Designing communication and remote controlling of virtual instrument network system

International Nuclear Information System (INIS)

Lei Lin; Wang Houjun; Zhou Xue; Zhou Wenjian

2005-01-01

In this paper, a virtual instrument network through the LAN and finally remote control of virtual instruments is realized based on virtual instrument and LabWindows/CVI software platform. The virtual instrument network system is made up of three subsystems. There are server subsystem, telnet client subsystem and local instrument control subsystem. This paper introduced virtual instrument network structure in detail based on LabWindows. Application procedure design of virtual instrument network communication, the Client/the programming mode of the server, remote PC and server communication far realizing, the control power of the workstation is transmitted, server program and so on essential technical were introduced. And virtual instruments network may connect to entire Internet on. Above-mentioned technology, through measuring the application in the electronic measurement virtual instrument network that is already built up, has verified the actual using value of the technology. Experiment and application validate that this design is resultful

Congestion Control in Data Transmission Networks Sliding Mode and Other Designs

CERN Document Server

Ignaciuk, Przemysław

2013-01-01

Congestion Control in Data Transmission Networks details the modeling and control of data traffic in communication networks. It shows how various networking phenomena can be represented in a consistent mathematical framework suitable for rigorous formal analysis. The monograph differentiates between fluid-flow continuous-time traffic models, discrete-time processes with constant sampling rates, and sampled-data systems with variable discretization periods. The authors address a number of difficult real-life problems, such as: • optimal control of flows with disparate, time-varying delay; • the existence of source and channel nonlinearities; • the balancing of quality of service and fairness requirements; and • the incorporation of variable rate allocation policies. Appropriate control mechanisms which can handle congestion and guarantee high throughput in various traffic scenarios (with different networking phenomena being considered) are proposed. Systematic design procedures using sound control-theo...

Feedforward Nonlinear Control Using Neural Gas Network

Directory of Open Access Journals (Sweden)

Iván Machón-González

2017-01-01

Full Text Available Nonlinear systems control is a main issue in control theory. Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems. This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network. The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure. The direct model of the plant constitutes a piece-wise linear approximation of the nonlinear system and each neuron represents a local linear model for which a linear controller is designed. The neural gas model works as an observer and a controller at the same time. A state feedback control is implemented by estimation of the state variables based on the local transfer function that was provided by the local linear model. The gradient vectors obtained by the supervised neural gas algorithm provide a robust procedure for feedforward nonlinear control, that is, supposing the inexistence of disturbances.

Automatic control design procedures for restructurable aircraft control

Science.gov (United States)

Looze, D. P.; Krolewski, S.; Weiss, J.; Barrett, N.; Eterno, J.

1985-01-01

A simple, reliable automatic redesign procedure for restructurable control is discussed. This procedure is based on Linear Quadratic (LQ) design methodologies. It employs a robust control system design for the unfailed aircraft to minimize the effects of failed surfaces and to extend the time available for restructuring the Flight Control System. The procedure uses the LQ design parameters for the unfailed system as a basis for choosing the design parameters of the failed system. This philosophy alloys the engineering trade-offs that were present in the nominal design to the inherited by the restructurable design. In particular, it alloys bandwidth limitations and performance trade-offs to be incorporated in the redesigned system. The procedure also has several other desirable features. It effectively redistributes authority among the available control effectors to maximize the system performance subject to actuator limitations and constraints. It provides a graceful performance degradation as the amount of control authority lessens. When given the parameters of the unfailed aircraft, the automatic redesign procedure reproduces the nominal control system design.

Neural network based approach for tuning of SNS feedback and feedforward controllers

International Nuclear Information System (INIS)

Kwon, Sung-Il; Prokop, Mark S.; Regan, Amy H.

2002-01-01

The primary controllers in the SNS low level RF system are proportional-integral (PI) feedback controllers. To obtain the best performance of the linac control systems, approximately 91 individual PI controller gains should be optimally tuned. Tuning is time consuming and requires automation. In this paper, a neural network is used for the controller gain tuning. A neural network can approximate any continuous mapping through learning. In a sense, the cavity loop PI controller is a continuous mapping of the tracking error and its one-sample-delay inputs to the controller output. Also, monotonic cavity output with respect to its input makes knowing the detailed parameters of the cavity unnecessary. Hence the PI controller is a prime candidate for approximation through a neural network. Using mean square error minimization to train the neural network along with a continuous mapping of appropriate weights, optimally tuned PI controller gains can be determined. The same neural network approximation property is also applied to enhance the adaptive feedforward controller performance. This is done by adjusting the feedforward controller gains, forgetting factor, and learning ratio. Lastly, the automation of the tuning procedure data measurement, neural network training, tuning and loading the controller gain to the DSP is addressed.

Program Baseline Change Control Procedure

International Nuclear Information System (INIS)

1993-02-01

This procedure establishes the responsibilities and process for approving initial issues of and changes to the technical, cost, and schedule baselines, and selected management documents developed by the Office of Civilian Radioactive Waste Management (OCRWM) for the Civilian Radioactive Waste Management System. This procedure implements the OCRWM Baseline Management Plan and DOE Order 4700.1, Chg 1. It streamlines the change control process to enhance integration, accountability, and traceability of Level 0 and Level I decisions through standardized Baseline Change Proposal (BCP) forms to be used by the Level 0, 1, 2, and 3 Baseline Change Control Boards (BCCBs) and to be tracked in the OCRWM-wide Configuration Information System (CIS) Database.This procedure applies to all technical, cost, and schedule baselines controlled by the Energy System Acquisition Advisory Board (ESAAB) BCCB (Level 0) and, OCRWM Program Baseline Control Board (PBCCB) (Level 1). All baseline BCPs initiated by Level 2 or lower BCCBs, which require approval from ESAAB or PBCCB, shall be processed in accordance with this procedure. This procedure also applies to all Program-level management documents controlled by the OCRWM PBCCB

Retrofit of heat exchanger networks considering pressure drop and existing structure: a new targeting procedure

International Nuclear Information System (INIS)

PanjehShahi, M.H.; Nouzari, M.M.

2002-01-01

A new retrofit targeting procedure, based on pinch technology has been developed. The procedure considers existing structure and hydrodynamic system of a given network as two main constraint during targeting. The procedure uses a linear programming model to consider existing structure. The model finds a network structure that has maximum compatibility with existing structure. Furthermore, the procedure using the pressure drop equations, can consider decreasing the film coefficients of streams due to increasing network area. Good compatibility between old and new networks and non replacement of hydrodynamic equipment cause to the best use of capital in retrofit projects. The procedure has been checked by doing two case studies, in which the results compared to the established methods, and realized significant improvement

Intelligent networked teleoperation control

CERN Document Server

Li, Zhijun; Su, Chun-Yi

2015-01-01

This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

A Network Traffic Control Enhancement Approach over Bluetooth Networks

DEFF Research Database (Denmark)

Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

2003-01-01

This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated solu...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well......This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...

Radiation control standards and procedures

Energy Technology Data Exchange (ETDEWEB)

1956-12-14

This manual contains the Radiation Control Standards'' and Radiation Control Procedures'' at Hanford Operations which have been established to provide the necessary control radiation exposures within Irradiation Processing Department. Provision is also made for including, in the form of Bulletins'', other radiological information of general interest to IPD personnel. The purpose of the standards is to establish firm radiological limits within which the Irradiation Processing Department will operate, and to outline our radiation control program in sufficient detail to insure uniform and consistent application throughout all IPD facilities. Radiation Control Procedures are intended to prescribe the best method of accomplishing an objective within the limitations of the Radiation Control Standards. A procedure may be changed at any time provided the suggested changes is generally agreeable to management involved, and is consistent with department policies and the Radiation Control Standards.

Maximum entropy networks are more controllable than preferential attachment networks

International Nuclear Information System (INIS)

Hou, Lvlin; Small, Michael; Lao, Songyang

2014-01-01

A maximum entropy (ME) method to generate typical scale-free networks has been recently introduced. We investigate the controllability of ME networks and Barabási–Albert preferential attachment networks. Our experimental results show that ME networks are significantly more easily controlled than BA networks of the same size and the same degree distribution. Moreover, the control profiles are used to provide insight into control properties of both classes of network. We identify and classify the driver nodes and analyze the connectivity of their neighbors. We find that driver nodes in ME networks have fewer mutual neighbors and that their neighbors have lower average degree. We conclude that the properties of the neighbors of driver node sensitively affect the network controllability. Hence, subtle and important structural differences exist between BA networks and typical scale-free networks of the same degree distribution. - Highlights: • The controllability of maximum entropy (ME) and Barabási–Albert (BA) networks is investigated. • ME networks are significantly more easily controlled than BA networks of the same degree distribution. • The properties of the neighbors of driver node sensitively affect the network controllability. • Subtle and important structural differences exist between BA networks and typical scale-free networks

Procedural learning during declarative control.

Science.gov (United States)

Crossley, Matthew J; Ashby, F Gregory

2015-09-01

There is now abundant evidence that human learning and memory are governed by multiple systems. As a result, research is now turning to the next question of how these putative systems interact. For instance, how is overall control of behavior coordinated, and does learning occur independently within systems regardless of what system is in control? Behavioral, neuroimaging, and neuroscience data are somewhat mixed with respect to these questions. Human neuroimaging and animal lesion studies suggest independent learning and are mostly agnostic with respect to control. Human behavioral studies suggest active inhibition of behavioral output but have little to say regarding learning. The results of two perceptual category-learning experiments are described that strongly suggest that procedural learning does occur while the explicit system is in control of behavior and that this learning might be just as good as if the procedural system was controlling the response. These results are consistent with the idea that declarative memory systems inhibit the ability of the procedural system to access motor output systems but do not prevent procedural learning. (c) 2015 APA, all rights reserved).

Backbone of complex networks of corporations: The flow of control

Science.gov (United States)

Glattfelder, J. B.; Battiston, S.

2009-09-01

We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.

Identification-based chaos control via backstepping design using self-organizing fuzzy neural networks

International Nuclear Information System (INIS)

Peng Yafu; Hsu, C.-F.

2009-01-01

This paper proposes an identification-based adaptive backstepping control (IABC) for the chaotic systems. The IABC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SOFNN identifier. The SOFNN identifier is used to online estimate the chaotic dynamic function with structure and parameter learning phases of fuzzy neural network. The structure learning phase consists of the growing and pruning of fuzzy rules; thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the neural structure of fuzzy neural network. The parameter learning phase adjusts the interconnection weights of neural network to achieve favorable approximation performance. Finally, simulation results verify that the proposed IABC can achieve favorable tracking performance.

Procedure Redesign Methods : E3-Control: a redesign methodology for control procedures

NARCIS (Netherlands)

Liu, J.; Hofman, W.J.; Tan, Y.H.

2011-01-01

This chapter highlights the core research methodology, e3-control, that is applied throughout the ITAIDE project for the purpose of control procedure redesign. We present the key concept of the e3-control methodology and its technical guidelines. Based on the output of this chapter, domain experts

NETWORK-CENTRIC TECHNOLOGIES FOR CONTROL OF THREE-PHASE NETWORK OPERATION MODES

Directory of Open Access Journals (Sweden)

Ye. I. Sokol

2017-06-01

Full Text Available Purpose. The development of the control system for three-phase network is based on intelligent technologies of network-centric control of heterogeneous objects. The introduction of unmanned aerial vehicles for monitoring of three-phase network increases the efficiency of management. Methodology. The case of decomposition of the instantaneous capacities of the fixed and variable components for 3-wire system. The features of power balance for the different modes of its functioning. It should be noted that symmetric sinusoidal mode is balanced and good, but really unbalanced, if the standard reactive power is not zero. To solve the problem of compensation is sufficient knowledge of the total value of the inactive components of full power (value of the inactive power without detail. The creation of a methodology of measurement and assessment will require knowledge of the magnitudes of each inactive component separately, which leads to the development of a unified approach to the measurement and compensation of inactive components of full power and the development of a generalized theory of power. Results. Procedure for the compensation of the current of zero sequence excludes from circuit the source, as the active component of instantaneous power of zero sequence, and a vector due to a current of zero sequence. This procedure is performed without time delay as it does not require integration. Only a 3–wire system with symmetrical voltage eliminates pulsations and symmetrization of the equivalent conductances of the phases of the task. Under asymmetric voltage, the power is different, its analysis requires the creation of a vector mathematical model of the energy processes of asymmetrical modes of 3–phase systems. Originality. The proposed method extends the basis of the vector method for any zero sequence voltages and shows that the various theories of instantaneous power three wired scheme due to the choice of a basis in a two

Control and Optimization of Network in Networked Control System

Directory of Open Access Journals (Sweden)

Wang Zhiwen

2014-01-01

Full Text Available In order to avoid quality of performance (QoP degradation resulting from quality of service (QoS, the solution to network congestion from the point of control theory, which marks departure of our results from the existing methods, is proposed in this paper. The congestion and bandwidth are regarded as state and control variables, respectively; then, the linear time-invariant (LTI model between congestion state and bandwidth of network is established. Consequently, linear quadratic method is used to eliminate the network congestion by allocating bandwidth dynamically. At last, numerical simulation results are given to illustrate the effectiveness of this modeling approach.

Proxy SDN Controller for Wireless Networks

Directory of Open Access Journals (Sweden)

Won-Suk Kim

2016-01-01

Full Text Available Management of wireless networks as well as wired networks by using software-defined networking (SDN has been highlighted continually. However, control features of a wireless network differ from those of a wired network in several aspects. In this study, we identify the various inefficient points when controlling and managing wireless networks by using SDN and propose SDN-based control architecture called Proxcon to resolve these problems. Proxcon introduces the concept of a proxy SDN controller (PSC for the wireless network control, and the PSC entrusted with the role of a main controller performs control operations and provides the latest network state for a network administrator. To address the control inefficiency, Proxcon supports offloaded SDN operations for controlling wireless networks by utilizing the PSC, such as local control by each PSC, hybrid control utilizing the PSC and the main controller, and locally cooperative control utilizing the PSCs. The proposed architecture and the newly supported control operations can enhance scalability and response time when the logically centralized control plane responds to the various wireless network events. Through actual experiments, we verified that the proposed architecture could address the various control issues such as scalability, response time, and control overhead.

Controllability of Surface Water Networks

Science.gov (United States)

Riasi, M. Sadegh; Yeghiazarian, Lilit

2017-12-01

To sustainably manage water resources, we must understand how to control complex networked systems. In this paper, we study surface water networks from the perspective of structural controllability, a concept that integrates classical control theory with graph-theoretic formalism. We present structural controllability theory and compute four metrics: full and target controllability, control centrality and control profile (FTCP) that collectively determine the structural boundaries of the system's control space. We use these metrics to answer the following questions: How does the structure of a surface water network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Finally, we demonstrate the structural controllability theory in the analysis of a wide range of surface water networks, such as tributary, deltaic, and braided river systems.

The APS control system network

International Nuclear Information System (INIS)

Sidorowicz, K.V.; McDowell, W.P.

1995-01-01

The APS accelerator control system is a distributed system consisting of operator interfaces, a network, and computer-controlled interfaces to hardware. This implementation of a control system has come to be called the open-quotes Standard Model.close quotes The operator interface is a UNDC-based workstation with an X-windows graphical user interface. The workstation may be located at any point on the facility network and maintain full functionality. The function of the network is to provide a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The crate or input/output controller (IOC) provides direct control and input/output interfaces for each accelerator subsystem. The network is an integral part of all modem control systems and network performance will determine many characteristics of a control system. This paper will describe the overall APS network and examine the APS control system network in detail. Metrics are provided on the performance of the system under various conditions

Structural controllability and controlling centrality of temporal networks.

Science.gov (United States)

Pan, Yujian; Li, Xiang

2014-01-01

Temporal networks are such networks where nodes and interactions may appear and disappear at various time scales. With the evidence of ubiquity of temporal networks in our economy, nature and society, it's urgent and significant to focus on its structural controllability as well as the corresponding characteristics, which nowadays is still an untouched topic. We develop graphic tools to study the structural controllability as well as its characteristics, identifying the intrinsic mechanism of the ability of individuals in controlling a dynamic and large-scale temporal network. Classifying temporal trees of a temporal network into different types, we give (both upper and lower) analytical bounds of the controlling centrality, which are verified by numerical simulations of both artificial and empirical temporal networks. We find that the positive relationship between aggregated degree and controlling centrality as well as the scale-free distribution of node's controlling centrality are virtually independent of the time scale and types of datasets, meaning the inherent robustness and heterogeneity of the controlling centrality of nodes within temporal networks.

Data Quality Assurance and Control for AmeriFlux Network at CDIAC, ORNL

Science.gov (United States)

Shem, W.; Boden, T.; Krassovski, M.; Yang, B.

2014-12-01

The Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) serves as the long-term data repository for the AmeriFlux network. Datasets currently available include hourly or half-hourly meteorological and flux observations, biological measurement records, and synthesis data products. Currently there is a lack of standardized nomenclature and specifically designed procedures for data quality assurance/control in processing and handling micrometeorological and ecological data at individual flux sites. CDIAC's has bridged this gap by providing efficient and accurate procedures for data quality control and standardization of the results for easier assimilation by the models used in climate science. In this presentation we highlight the procedures we have put in place to scrutinize continuous flux and meteorological data within Ameriflux network. We itemize some basic data quality issues that we have observed over the past years and include some examples of typical data quality issues. Such issues, e.g., incorrect time-stamping, poor calibration or maintenance of instruments, missing or incomplete metadata and others that are commonly over-looked by PI's, invariably impact the time-series observations.

Control networks and hubs.

Science.gov (United States)

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

A Neural Networks Based Operation Guidance System for Procedure Presentation and Validation

International Nuclear Information System (INIS)

Seung, Kun Mo; Lee, Seung Jun; Seong, Poong Hyun

2006-01-01

In this paper, a neural network based operator support system is proposed to reduce operator's errors in abnormal situations in nuclear power plants (NPPs). There are many complicated situations, in which regular and suitable operations should be done by operators accordingly. In order to regulate and validate operators' operations, it is necessary to develop an operator support system which includes computer based procedures with the functions for operation validation. Many computerized procedures systems (CPS) have been recently developed. Focusing on the human machine interface (HMI) design and procedures' computerization, most of CPSs used various methodologies to enhance system's convenience, reliability and accessibility. Other than only showing procedures, the proposed system integrates a simple CPS and an operation validation system (OVS) by using artificial neural network (ANN) for operational permission and quantitative evaluation

In-Trail Procedure Air Traffic Control Procedures Validation Simulation Study

Science.gov (United States)

Chartrand, Ryan C.; Hewitt, Katrin P.; Sweeney, Peter B.; Graff, Thomas J.; Jones, Kenneth M.

2012-01-01

In August 2007, Airservices Australia (Airservices) and the United States National Aeronautics and Space Administration (NASA) conducted a validation experiment of the air traffic control (ATC) procedures associated with the Automatic Dependant Surveillance-Broadcast (ADS-B) In-Trail Procedure (ITP). ITP is an Airborne Traffic Situation Awareness (ATSA) application designed for near-term use in procedural airspace in which ADS-B data are used to facilitate climb and descent maneuvers. NASA and Airservices conducted the experiment in Airservices simulator in Melbourne, Australia. Twelve current operational air traffic controllers participated in the experiment, which identified aspects of the ITP that could be improved (mainly in the communication and controller approval process). Results showed that controllers viewed the ITP as valid and acceptable. This paper describes the experiment design and results.

The importance of control considerations for heat exchanger network synthesis: a case study

Directory of Open Access Journals (Sweden)

S.G. Oliveira

2001-06-01

Full Text Available Cost optimization in the synthesis decision tree often leads to a reduced degree of freedom which degrades the process’s ability to reject disturbances as a consequence of low controllability. In fact, Heat Exchanger Networks (HENs obtained by traditional synthesis procedures that ignore controllability aspects must be evaluated in this context a posteriori. The aim of this work was to develop a procedure that includes RGA and SVD measures of controllability, which are solely based on steady state information, thereby freeing the synthesis procedure of the cumbersome dynamic analysis. When a structure is defined during a traditional HEN synthesis procedure, a degree of freedom analysis is approached as a simulation problem. Next, an optimization is performed, since new variables are usually added to increase the degree of freedom of the HEN in order to render it controllable. A key point in the proposed procedure is the inference of controllability based on the proposed controllability measures, which also provide a control scheme by pairing controlled and manipulated variables during the process design. A HEN reported in the literature is used to illustrate the proposed procedure. The steady state simulator Aspen Plus and the dynamic simulator Aspen Dynamics (Aspentech, Inc. were employed.

Semi-empirical neural network models of controlled dynamical systems

Directory of Open Access Journals (Sweden)

Mihail V. Egorchev

2017-12-01

Full Text Available A simulation approach is discussed for maneuverable aircraft motion as nonlinear controlled dynamical system under multiple and diverse uncertainties including knowledge imperfection concerning simulated plant and its environment exposure. The suggested approach is based on a merging of theoretical knowledge for the plant with training tools of artificial neural network field. The efficiency of this approach is demonstrated using the example of motion modeling and the identification of the aerodynamic characteristics of a maneuverable aircraft. A semi-empirical recurrent neural network based model learning algorithm is proposed for multi-step ahead prediction problem. This algorithm sequentially states and solves numerical optimization subproblems of increasing complexity, using each solution as initial guess for subsequent subproblem. We also consider a procedure for representative training set acquisition that utilizes multisine control signals.

Controllability of Train Service Network

Directory of Open Access Journals (Sweden)

Xuelei Meng

2015-01-01

Full Text Available Train service network is a network form of train service plan. The controllability of the train service plan determines the recovery possibility of the train service plan in emergencies. We first build the small-world model for train service network and analyze the scale-free character of it. Then based on the linear network controllability theory, we discuss the LB model adaptability in train service network controllability analysis. The LB model is improved and we construct the train service network and define the connotation of the driver nodes based on the immune propagation and cascading failure in the train service network. An algorithm to search for the driver nodes, turning the train service network into a bipartite graph, is proposed and applied in the train service network. We analyze the controllability of the train service network of China with the method and the results of the computing case prove the feasibility of it.

Network-targeted cerebellar transcranial magnetic stimulation improves attentional control

Science.gov (United States)

Esterman, Michael; Thai, Michelle; Okabe, Hidefusa; DeGutis, Joseph; Saad, Elyana; Laganiere, Simon E.; Halko, Mark A.

2018-01-01

Developing non-invasive brain stimulation interventions to improve attentional control is extremely relevant to a variety of neurologic and psychiatric populations, yet few studies have identified reliable biomarkers that can be readily modified to improve attentional control. One potential biomarker of attention is functional connectivity in the core cortical network supporting attention - the dorsal attention network (DAN). We used a network-targeted cerebellar transcranial magnetic stimulation (TMS) procedure, intended to enhance cortical functional connectivity in the DAN. Specifically, in healthy young adults we administered intermittent theta burst TMS (iTBS) to the midline cerebellar node of the DAN and, as a control, the right cerebellar node of the default mode network (DMN). These cerebellar targets were localized using individual resting-state fMRI scans. Participants completed assessments of both sustained (gradual onset continuous performance task, gradCPT) and transient attentional control (attentional blink) immediately before and after stimulation, in two sessions (cerebellar DAN and DMN). Following cerebellar DAN stimulation, participants had significantly fewer attentional lapses (lower commission error rates) on the gradCPT. In contrast, stimulation to the cerebellar DMN did not affect gradCPT performance. Further, in the DAN condition, individuals with worse baseline gradCPT performance showed the greatest enhancement in gradCPT performance. These results suggest that temporarily increasing functional connectivity in the DAN via network-targeted cerebellar stimulation can enhance sustained attention, particularly in those with poor baseline performance. With regard to transient attention, TMS stimulation improved attentional blink performance across both stimulation sites, suggesting increasing functional connectivity in both networks can enhance this aspect of attention. These findings have important implications for intervention applications

Research on NGN network control technology

Science.gov (United States)

Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

2004-04-01

Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

MRI quality control tools for procedures and analyses

International Nuclear Information System (INIS)

Di Nallo, A.M.; Ortenzia, O.; Benassi, M.; D'Arienzo, M.; Coniglio, D.

2006-01-01

Quality control in MRI includes acceptance tests on the installation of a new scanner and tests representative of the system's performance during clinical practice.The first tests are time consuming and carried out to evaluate the agreement of the system with the prescribed procurement specifications. The second tests identify the equipment malfunction requiring maintenance are not time consuming and are suited to a busy clinical scanner. The paper evaluates the feasibility of the AAPM protocols and proposes procedures and practical tools to achieve this purpose.The MRI images, captured from the scanner and transferred in DICOM (Digital Imaging and Communications in Medicine) format by a local network, are analyzed by computerized worksheets and commercial software

Secure network for beamline control

International Nuclear Information System (INIS)

Ohata, T.; Fukui, T.; Ishii, M.; Furukawa, Y.; Nakatani, T.; Matsushita, T.; Takeuchi, M.; Tanaka, R.; Ishikawa, T.

2001-01-01

In SPring-8, beamline control system is constructed with a highly available distributed network system. The socket based communication protocol is used for the beamline control mainly. Beamline users can control the equipment by sending simple control commands to a server process, which is running on a beamline-managing computer (Ohata et al., SPring-8 beamline control system, ICALEPCS'99, Trieste, Italy, 1999). At the beginning the network was based on the shared topology at all beamlines. Consequently, it has a risk for misapplication of the user's program to access different machines on the network system cross over beamlines. It is serious problem for the SPring-8 beamline control system, because all beamlines controlled with unified software interfaces. We introduced the switching technology and the firewalls to support network access control. Also the virtual networking (VLAN: IEEE 802.1Q) and the gigabit Ethernet technology (IEEE 802.3ab) are introduced. Thus the network security and the reliability are guaranteed at the higher level in SPring-8 beamline

Neural networks for aircraft control

Science.gov (United States)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Asynchronous control for networked systems

CERN Document Server

Rubio, Francisco; Bencomo, Sebastián

2015-01-01

This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

The development and work procedures to super speed network for the growing demands for the network

International Nuclear Information System (INIS)

Nosaki, Nobuhisa; Aoki, Kazuhisa

2001-01-01

Following the recently growing demands for the network, the modification of Local Area Network (LAN) and Wide Area Network (WAN) to super speed network have been reviewed in the Japan Nuclear Cycle Development Institute (JNC). Though the modification of the LAN to super speed network is being developed this year in Heisei 13 fiscal year, it of the WAN was developed in Heisei 12 fiscal year. In spite of various issues, technical reviews and etc., there are a lot of benefits and merit for the super speed network of the WAN and though the modification of it and reduction of the running cost are contradictory to each other, both of those have been achieved in the JNC. This paper introduces the development and work procedures for the WAN. (author)

Procedures for mastitis diagnosis and control.

Science.gov (United States)

Sears, P M; González, R N; Wilson, D J; Han, H R

1993-11-01

Procedures for mastitis diagnosis and control include culturing individual cow and bulk tank milk samples, antibiotic susceptibility testing, and evaluation of somatic cell count reports and clinical mastitis treatment records. Integrated use of such procedures is necessary for effective mastitis diagnosis and control.

ODIN. Online Database Information Network: ODIN Policy & Procedure Manual.

Science.gov (United States)

Townley, Charles T.; And Others

Policies and procedures are outlined for the Online Database Information Network (ODIN), a cooperative of libraries in south-central Pennsylvania, which was organized to improve library services through technology. The first section covers organization and goals, members, and responsibilities of the administrative council and libraries. Patrons…

Pinning synchronization of hybrid-coupled directed delayed dynamical network via intermittent control.

Science.gov (United States)

Cai, Shuiming; Zhou, Peipei; Liu, Zengrong

2014-09-01

This paper concerns the problem of exponential synchronization for a class of general delayed dynamical networks with hybrid coupling via pinning periodically intermittent control. Both the internal delay and coupling delay are taken into account in the network model. Meanwhile, the transmission delay and self-feedback delay are involved in the delayed coupling term. By establishing a new differential inequality, several simple and useful exponential synchronization criteria are derived analytically. It is shown that the controlled synchronization state can vary in comparison with the conventional synchronized solution, and the degree of the node and the inner delayed coupling matrix play important roles in the controlled synchronization state. By choosing different inner delayed coupling matrices and the degrees of the node, different controlled synchronization states can be obtained. Furthermore, the detail pinning schemes deciding what nodes should be chosen as pinned candidates and how many nodes are needed to be pinned for a fixed coupling strength are provided. The simple procedures illuminating how to design suitable intermittent controllers in real application are also given. Numerical simulations, including an undirected scale-free network and a directed small-world network, are finally presented to demonstrate the effectiveness of the theoretical results.

Neural PID Control Strategy for Networked Process Control

Directory of Open Access Journals (Sweden)

Jianhua Zhang

2013-01-01

Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

Science.gov (United States)

Xia, Kewei; Huo, Wei

2016-05-01

This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An electric mandate. The EU procedure for harmonising cross-border network codes for electricity

Energy Technology Data Exchange (ETDEWEB)

Jevnaker, Torbjoerg

2012-07-01

The research question addressed in this report is why the EU procedure for developing network codes for electricity was enacted in its particular form. Passed by the EU in 2009, European organisations partly outside of the formal EU structure were given a mandate to make rules that would apply across the EU. This was puzzling given the observed resistance on part of the member states to let go of national control over energy issues. Drawing on institutionalist perspectives, the analysis shows that the procedure would not have been passed without support from and compromise among the Commission, European Parliament and the member states in Council; that parts of the procedure imitated existing practices within related policy areas; that horizontal and vertical specialization within the nation-states along with a Commission actively promoting transnational cooperation changed the feedback mechanisms, which changed the direction of European energy market regulation; and finally, that the new actors played an active role vis-a-vis EU bodies as the latter were legislating on the procedure. (Author)

Towards structural controllability of local-world networks

International Nuclear Information System (INIS)

Sun, Shiwen; Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi

2016-01-01

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Towards structural controllability of local-world networks

Energy Technology Data Exchange (ETDEWEB)

Sun, Shiwen, E-mail: sunsw80@126.com [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China); Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China)

2016-05-20

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Studies on neutron noise diagnostics of control rod vibrations by neural networks

International Nuclear Information System (INIS)

Roston, G.; Kozma, R.; Kitamura, M.; Garis, N.S.; Pazsit, I.

1996-01-01

This work is focussed on the study of a neutron noise based technique for the diagnostics of reactor core internal, in particular, excessively vibrating control rods. The use of a combination of physical models and neural networks offers an alternative way of performing the inversion procedure. The application of a neural network technique to determine the rod position from the detector spectra is much faster, more effective and simpler to use than the conventional method. (author). 5 refs., 1 fig., 1 tab

Minimum energy control and optimal-satisfactory control of Boolean control network

International Nuclear Information System (INIS)

Li, Fangfei; Lu, Xiwen

2013-01-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

Directory of Open Access Journals (Sweden)

Matti Mantere

2013-09-01

Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

Neural Networks for Optimal Control

DEFF Research Database (Denmark)

Sørensen, O.

1995-01-01

Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

Tailoring groundwater quality monitoring to vulnerability: a GIS procedure for network design.

Science.gov (United States)

Preziosi, E; Petrangeli, A B; Giuliano, G

2013-05-01

Monitoring networks aiming to assess the state of groundwater quality and detect or predict changes could increase in efficiency when fitted to vulnerability and pollution risk assessment. The main purpose of this paper is to describe a methodology aiming at integrating aquifers vulnerability and actual levels of groundwater pollution in the monitoring network design. In this study carried out in a pilot area in central Italy, several factors such as hydrogeological setting, groundwater vulnerability, and natural and anthropogenic contamination levels were analyzed and used in designing a network tailored to the monitoring objectives, namely, surveying the evolution of groundwater quality relating to natural conditions as well as to polluting processes active in the area. Due to the absence of an aquifer vulnerability map for the whole area, a proxi evaluation of it was performed through a geographic information system (GIS) methodology, leading to the so called "susceptibility to groundwater quality degradation". The latter was used as a basis for the network density assessment, while water points were ranked by several factors including discharge, actual contamination levels, maintenance conditions, and accessibility for periodical sampling in order to select the most appropriate to the network. Two different GIS procedures were implemented which combine vulnerability conditions and water points suitability, producing two slightly different networks of 50 monitoring points selected out of the 121 candidate wells and springs. The results are compared with a "manual" selection of the points. The applied GIS procedures resulted capable to select the requested number of water points from the initial set, evaluating the most confident ones and an appropriate density. Moreover, it is worth underlining that the second procedure (point distance analysis [PDA]) is technically faster and simpler to be performed than the first one (GRID + PDA).

Procedures of quality control of radiopharmaceutical activity counters

International Nuclear Information System (INIS)

Oliveira, A.E. de; Iwahara, A.; Gaast, H.A. van der; Buckman, S.M.

1999-01-01

The Radionuclides Metrology Supervision-Ionizing Radiation Metrology National Laboratory maintain and distributes the brazilian standards for radioactivity measurements. The Brazilian Institute for Metrology, Regulation and Industrial Quality (INMETRO), which is the brazilian authority for standards verification, is coordinating the enhancement of the standards distribution. Concerning to the nuclear medicine related radioisotopes, this network will provide for calibration of brazilian hospitals and clinics instruments, assuring great accuracy of the radiopharmaceuticals activities. This work gives details of the calibration quality control procedures recommended by the Radionuclides Metrology Supervisory (Brazilian National Nuclear Energy Commission) and the Radioactive Standards Division of the Australian Nuclear Technology and Science Organization (ANSTO). This information can be used as a guide for the brazilian nuclear medicine services guaranty on the accuracy and precision of the radiopharmaceuticals activity measurements measurements

Template-based procedures for neural network interpretation.

Science.gov (United States)

Alexander, J A.; Mozer, M C.

1999-04-01

Although neural networks often achieve impressive learning and generalization performance, their internal workings are typically all but impossible to decipher. This characteristic of the networks, their opacity, is one of the disadvantages of connectionism compared to more traditional, rule-oriented approaches to artificial intelligence. Without a thorough understanding of the network behavior, confidence in a system's results is lowered, and the transfer of learned knowledge to other processing systems - including humans - is precluded. Methods that address the opacity problem by casting network weights in symbolic terms are commonly referred to as rule extraction techniques. This work describes a principled approach to symbolic rule extraction from standard multilayer feedforward networks based on the notion of weight templates, parameterized regions of weight space corresponding to specific symbolic expressions. With an appropriate choice of representation, we show how template parameters may be efficiently identified and instantiated to yield the optimal match to the actual weights of a unit. Depending on the requirements of the application domain, the approach can accommodate n-ary disjunctions and conjunctions with O(k) complexity, simple n-of-m expressions with O(k(2)) complexity, or more general classes of recursive n-of-m expressions with O(k(L+2)) complexity, where k is the number of inputs to an unit and L the recursion level of the expression class. Compared to other approaches in the literature, our method of rule extraction offers benefits in simplicity, computational performance, and overall flexibility. Simulation results on a variety of problems demonstrate the application of our procedures as well as the strengths and the weaknesses of our general approach.

Delays and networked control systems

CERN Document Server

Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

2016-01-01

This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

Science.gov (United States)

Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

2017-12-14

Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

A robust and high-performance queue management controller for large round trip time networks

Science.gov (United States)

Khoshnevisan, Ladan; Salmasi, Farzad R.

2016-05-01

Congestion management for transmission control protocol is of utmost importance to prevent packet loss within a network. This necessitates strategies for active queue management. The most applied active queue management strategies have their inherent disadvantages which lead to suboptimal performance and even instability in the case of large round trip time and/or external disturbance. This paper presents an internal model control robust queue management scheme with two degrees of freedom in order to restrict the undesired effects of large and small round trip time and parameter variations in the queue management. Conventional approaches such as proportional integral and random early detection procedures lead to unstable behaviour due to large delay. Moreover, internal model control-Smith scheme suffers from large oscillations due to the large round trip time. On the other hand, other schemes such as internal model control-proportional integral and derivative show excessive sluggish performance for small round trip time values. To overcome these shortcomings, we introduce a system entailing two individual controllers for queue management and disturbance rejection, simultaneously. Simulation results based on Matlab/Simulink and also Network Simulator 2 (NS2) demonstrate the effectiveness of the procedure and verify the analytical approach.

Vulnerability and controllability of networks of networks

International Nuclear Information System (INIS)

Liu, Xueming; Peng, Hao; Gao, Jianxi

2015-01-01

Network science is a highly interdisciplinary field ranging from natural science to engineering technology and it has been applied to model complex systems and used to explain their behaviors. Most previous studies have been focus on isolated networks, but many real-world networks do in fact interact with and depend on other networks via dependency connectivities, forming “networks of networks” (NON). The interdependence between networks has been found to largely increase the vulnerability of interacting systems, when a node in one network fails, it usually causes dependent nodes in other networks to fail, which, in turn, may cause further damage on the first network and result in a cascade of failures with sometimes catastrophic consequences, e.g., electrical blackouts caused by the interdependence of power grids and communication networks. The vulnerability of a NON can be analyzed by percolation theory that can be used to predict the critical threshold where a NON collapses. We review here the analytic framework for analyzing the vulnerability of NON, which yields novel percolation laws for n-interdependent networks and also shows that percolation theory of a single network studied extensively in physics and mathematics in the last 50 years is a specific limited case of the more general case of n interacting networks. Understanding the mechanism behind the cascading failure in NON enables us finding methods to decrease the vulnerability of the natural systems and design of more robust infrastructure systems. By examining the vulnerability of NON under targeted attack and studying the real interdependent systems, we find two methods to decrease the systems vulnerability: (1) protect the high-degree nodes, and (2) increase the degree correlation between networks. Furthermore, the ultimate proof of our understanding of natural and technological systems is reflected in our ability to control them. We also review the recent studies and challenges on the

Launch Control Network Engineer

Science.gov (United States)

Medeiros, Samantha

2017-01-01

The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

Modeling, Optimization & Control of Hydraulic Networks

DEFF Research Database (Denmark)

Tahavori, Maryamsadat

2014-01-01

. The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

Science.gov (United States)

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Control of collective network chaos.

Science.gov (United States)

Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A F; So, Paul

2014-06-01

Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

Accelerator Control and Global Networks State of the Art

CERN Document Server

Gurd, D P

2004-01-01

As accelerators increase in size and complexity, demands upon their control systems increase correspondingly. Machine complexity is reflected in complexity of control system hardware and software and careful configuration management is essential. Model-based procedures and fast feedback based upon even faster beam instrumentation are often required. Managing machine protection systems with tens of thousands of inputs is another significant challenge. Increased use of commodity hardware and software introduces new issues of security and control. Large new facilities will increasingly be built by national (e.g. SNS) or international (e.g. a linear collider) collaborations. Building an integrated control system for an accelerator whose development is geographically widespread presents particular problems, not all of them technical. Recent discussions of a “Global Accelerator Network” include the possibility of multiple remote control rooms and no more night shifts. Based upon current experien...

Stabilization of model-based networked control systems

Energy Technology Data Exchange (ETDEWEB)

Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)

2016-06-08

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

Network Access Control For Dummies

CERN Document Server

Kelley, Jay; Wessels, Denzil

2009-01-01

Network access control (NAC) is how you manage network security when your employees, partners, and guests need to access your network using laptops and mobile devices. Network Access Control For Dummies is where you learn how NAC works, how to implement a program, and how to take real-world challenges in stride. You'll learn how to deploy and maintain NAC in your environment, identify and apply NAC standards, and extend NAC for greater network security. Along the way you'll become familiar with what NAC is (and what it isn't) as well as the key business drivers for deploying NAC.Learn the step

Pinning Control Strategy of Multicommunity Structure Networks

Directory of Open Access Journals (Sweden)

Chao Ding

2017-01-01

Full Text Available In order to investigate the effects of community structure on synchronization, a pinning control strategy is researched in a class of complex networks with community structure in this paper. A feedback control law is designed based on the network community structure information. The stability condition is given and proved by using Lyapunov stability theory. Our research shows that as to community structure networks, there being a threshold hT≈5, when coupling strength bellows this threshold, the stronger coupling strength corresponds to higher synchronizability; vice versa, the stronger coupling strength brings lower synchronizability. In addition the synchronizability of overlapping and nonoverlapping community structure networks was simulated and analyzed; while the nodes were controlled randomly and intensively, the results show that intensive control strategy is better than the random one. The network will reach synchronization easily when the node with largest betweenness was controlled. Furthermore, four difference networks’ synchronizability, such as Barabási-Albert network, Watts-Strogatz network, Erdös-Rényi network, and community structure network, are simulated; the research shows that the community structure network is more easily synchronized under the same control strength.

Dynamic Frequency Control in Power Networks

OpenAIRE

Zhao, Changhong; Mallada Garcia, Enrique; Low, Steven H.

2016-01-01

Node controllers in power distribution networks in accordance with embodiments of the invention enable dynamic frequency control. One embodiment includes a node controller comprising a network interface a processor; and a memory containing a frequency control application; and a plurality of node operating parameters describing the operating parameters of a node, where the node is selected from a group consisting of at least one generator node in a power distribution network wherein the proces...

Automated fault tree synthesis by semantic network modeling, rulebased development and recursive 3-value procedure

International Nuclear Information System (INIS)

Kumamoto, Hiromitsu; Henley, E.J.

1995-01-01

A concept of flow is introduced to represent any material, information, energy, activity, or phenomenon which can move or propagate along flow paths to cause events specific to the system to be analyzed. A graphical equipment library is given to represent typical types of 'generation rate' and 'aperture' controllers. The system is modeled by a semantic network with labeled arrows showing effect to cause (backward) relationships between flow and equipment nodes. A correspondence between the equipment library and the system components is established, and the semantic network is constructed by integrating network fragments in the library. Fixed and/or free boundary conditions can be specified explicitly for flow or equipment nodes. Forward-chaining event development rules locally trace the labeled arrows, while a 3-value procedure guides the FT generation by recursive rule applications. The rules are obtained from tables and equipment definitions. The 3-value logic is used to truncate FTs according to the boundary conditions. Different FTs are generated for different top events and boundary conditions, given a semantic network model. FT modules and their hierarchies can be identified by examining network theoretic properties of flow nodes. The proposed approach is demonstrated for a relay system, a hypothetical swimming pool reactor and a chemical reactor

Virtualized Network Control (VNC)

Energy Technology Data Exchange (ETDEWEB)

Lehman, Thomas [Univ. of Southern California, Los Angeles, CA (United States); Guok, Chin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States)

2013-01-31

The focus of this project was on the development of a "Network Service Plane" as an abstraction model for the control and provisioning of multi-layer networks. The primary motivation for this work were the requirements of next generation networked applications which will need to access advanced networking as a first class resource at the same level as compute and storage resources. A new class of "Intelligent Network Services" were defined in order to facilitate the integration of advanced network services into application specific workflows. This new class of network services are intended to enable real-time interaction between the application co-scheduling algorithms and the network for the purposes of workflow planning, real-time resource availability identification, scheduling, and provisioning actions.

Internal Control Organization Procedure

OpenAIRE

Radu Dorin Lenghel

2013-01-01

Internal control represents the totality of policies and procedures adopted by management, which contribute: to the fulfilment of managerial objectives, to the prevention and detection of frauds or errors, to the accuracy and exhaustiveness of accounting entries, as well as to the preparation in due course of financial accounting information. Internal control represents a managerial instrument which assures the fulfilment of objectives of the entity, being an ongoing process in which administ...

A new traffic control design method for large networks with signalized intersections

Science.gov (United States)

Leininger, G. G.; Colony, D. C.; Seldner, K.

1979-01-01

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

Distributed controller clustering in software defined networks.

Directory of Open Access Journals (Sweden)

Ahmed Abdelaziz

Full Text Available Software Defined Networking (SDN is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN SDN and Open Network Operating System (ONOS controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

Distributed controller clustering in software defined networks.

Science.gov (United States)

Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

Pinning impulsive control algorithms for complex network

Energy Technology Data Exchange (ETDEWEB)

Sun, Wen [School of Information and Mathematics, Yangtze University, Jingzhou 434023 (China); Lü, Jinhu [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Chen, Shihua [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China); Yu, Xinghuo [School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001 (Australia)

2014-03-15

In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.

Pinning impulsive control algorithms for complex network

International Nuclear Information System (INIS)

Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

2014-01-01

In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms

Communication and control for networked complex systems

CERN Document Server

Peng, Chen; Han, Qing-Long

2015-01-01

This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

Neural Networks in Control Applications

DEFF Research Database (Denmark)

Sørensen, O.

are examined. The models are separated into three groups representing input/output descriptions as well as state space descriptions: - Models, where all in- and outputs are measurable (static networks). - Models, where some inputs are non-measurable (recurrent networks). - Models, where some in- and some...... outputs are non-measurable (recurrent networks with incomplete state information). The three groups are ordered in increasing complexity, and for each group it is shown how to solve the problems concerning training and application of the specific model type. Of particular interest are the model types...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

MPC control of water supply networks

DEFF Research Database (Denmark)

Baunsgaard, Kenneth Marx Hoe; Ravn, Ole; Kallesoe, Carsten Skovmose

2016-01-01

This paper investigates the modelling and predictive control of a drinking water supply network with the aim of minimising the energy and economic cost. A model predictive controller, MPC, is applied to a nonlinear model of a drinking water network that follows certain constraints to maintain......, controlling the drinking water supply network with the MPC showed reduction of the energy and the economic cost of running the system. This has been achieved by minimising actuator control effort and by shifting the actuator use towards the night time, where energy prices are lower. Along with energy cost...... consumer pressure desire. A model predictive controller, MPC, is based on a simple model that models the main characteristics of a water distribution network, optimizes a desired cost minimisation, and keeps the system inside specified constraints. In comparison to a logic (on/off) control design...

Neural Networks in Control Applications

DEFF Research Database (Denmark)

Sørensen, O.

The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

Enabling Controlling Complex Networks with Local Topological Information.

Science.gov (United States)

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Adaptive optimization and control using neural networks

Energy Technology Data Exchange (ETDEWEB)

Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

1993-10-22

Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

Wireless sensor network topology control

OpenAIRE

Zuk, Olexandr; Romanjuk, Valeriy; Sova, Oleg

2010-01-01

Topology control process for the wireless sensor network is considered. In this article the use of rule base for making decision on the search of optimum network topology is offered for the realization of different aims of network management.

Simplified LQG Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1997-01-01

A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

Data Quality Control of the French Permanent Broadband Network in the RESIF Framework

Science.gov (United States)

Grunberg, Marc; Lambotte, Sophie; Engels, Fabien; Dretzen, Remi; Hernandez, Alain

2014-05-01

In the framework of the RESIF (Réseau Sismologique et géodésique Français) project, a new information system is being setting up, allowing the improvement of the management and the distribution of high quality data from the different elements of RESIF and the associated networks. Within this information system, EOST (in Strasbourg) is in charge of collecting real-time permanent broadband seismic waveform, and performing Quality Control on these data. The real-time and validated data set are pushed to the French National Distribution Center (Isterre/Grenoble) in order to make them publicly available. Furthermore EOST hosts the BCSF-ReNaSS, in charge of the French metropolitan seismic bulletin. This allows to benefit from some high-end quality control based on the national and world-wide seismicity. Here we present first the real-time seismic data flow from the stations of the French National Broad Band Network to EOST, and then, the data Quality Control procedures that were recently installed, including some new developments. The data Quality Control consists in applying a variety of subprocesses to check the consistency of the whole system and process from the stations to the data center. This allows us to verify that instruments and data transmission are operating correctly. Moreover analysis of the ambient noise helps to characterize intrinsic seismic quality of the stations and to identify other kind of disturbances. The deployed Quality Control consist in a pipeline that starts with low-level procedures : check the real-time miniseed data file (file naming convention, data integrity), check for inconsistencies between waveform and meta-data (channel name, sample rate, etc.), compute waveform statistics (data availability, gap/overlap, mean, rms, time quality, spike). It is followed by some high-level procedures such as : power spectral density computation (PSD), STA/LTA computation to be correlated to the seismicity, phases picking and stations magnitudes

Control range: a controllability-based index for node significance in directed networks

International Nuclear Information System (INIS)

Wang, Bingbo; Gao, Lin; Gao, Yong

2012-01-01

While a large number of methods for module detection have been developed for undirected networks, it is difficult to adapt them to handle directed networks due to the lack of consensus criteria for measuring the node significance in a directed network. In this paper, we propose a novel structural index, the control range, motivated by recent studies on the structural controllability of large-scale directed networks. The control range of a node quantifies the size of the subnetwork that the node can effectively control. A related index, called the control range similarity, is also introduced to measure the structural similarity between two nodes. When applying the index of control range to several real-world and synthetic directed networks, it is observed that the control range of the nodes is mainly influenced by the network's degree distribution and that nodes with a low degree may have a high control range. We use the index of control range similarity to detect and analyze functional modules in glossary networks and the enzyme-centric network of homo sapiens. Our results, as compared with other approaches to module detection such as modularity optimization algorithm, dynamic algorithm and clique percolation method, indicate that the proposed indices are effective and practical in depicting structural and modular characteristics of sparse directed networks

Filtering and control of wireless networked systems

CERN Document Server

Zhang, Dan; Yu, Li

2017-01-01

This self-contained book, written by leading experts, offers a cutting-edge, in-depth overview of the filtering and control of wireless networked systems. It addresses the energy constraint and filter/controller gain variation problems, and presents both the centralized and the distributed solutions. The first two chapters provide an introduction to networked control systems and basic information on system analysis. Chapters (3–6) then discuss the centralized filtering of wireless networked systems, presenting different approaches to deal with energy efficiency and filter/controller gain variation problems. The next part (chapters 7–10) explores the distributed filtering of wireless networked systems, addressing the main problems of energy constraint and filter gain variation. The final part (chapters 11–14) focuses on the distributed control of wireless networked systems. networked systems for communication and control applications, the bo...

Efficient Beacon Collision Resolution Procedure for IEEE 802.15.4 /Zigbee Wireless Personal Area Networks

Directory of Open Access Journals (Sweden)

Bassam A. Zafar

2017-04-01

Full Text Available While IEEE 802.15.4/Zigbee is a promising technology for Wireless Personal Area Networks, several transmission problems are not yet resolved. In particular, the problem of beacon transmission interferences is causing the device connection loss to the network. In order to resolve this problem, we present a new distributed and reactive procedure for beacon collision resolution. It is an extension of the alignment procedure to reorganize randomly the beacon transmission time when a collision has occurred. The detail of the proposed procedure will be fully described and analyzed. The performance of our approach is performed by simulations. The results show that our approach reduces the collision probability and the device disconnections consequently.

Guaranteed Cost Fault-Tolerant Control for Networked Control Systems with Sensor Faults

Directory of Open Access Journals (Sweden)

Qixin Zhu

2015-01-01

Full Text Available For the large scale and complicated structure of networked control systems, time-varying sensor faults could inevitably occur when the system works in a poor environment. Guaranteed cost fault-tolerant controller for the new networked control systems with time-varying sensor faults is designed in this paper. Based on time delay of the network transmission environment, the networked control systems with sensor faults are modeled as a discrete-time system with uncertain parameters. And the model of networked control systems is related to the boundary values of the sensor faults. Moreover, using Lyapunov stability theory and linear matrix inequalities (LMI approach, the guaranteed cost fault-tolerant controller is verified to render such networked control systems asymptotically stable. Finally, simulations are included to demonstrate the theoretical results.

On generalized fixed sequence procedures for controlling the FWER.

Science.gov (United States)

Qiu, Zhiying; Guo, Wenge; Lynch, Gavin

2015-12-30

Testing a sequence of pre-ordered hypotheses to decide which of these can be rejected or accepted while controlling the familywise error rate (FWER) is of importance in many scientific studies such as clinical trials. In this paper, we first introduce a generalized fixed sequence procedure whose critical values are defined by using a function of the numbers of rejections and acceptances, and which allows follow-up hypotheses to be tested even if some earlier hypotheses are not rejected. We then construct the least favorable configuration for this generalized fixed sequence procedure and present a sufficient condition for the FWER control under arbitrary dependence. Based on the condition, we develop three new generalized fixed sequence procedures controlling the FWER under arbitrary dependence. We also prove that each generalized fixed sequence procedure can be described as a specific closed testing procedure. Through simulation studies and a clinical trial example, we compare the power performance of these proposed procedures with those of the existing FWER controlling procedures. Finally, when the pairwise joint distributions of the true null p-values are known, we further improve these procedures by incorporating pairwise correlation information while maintaining the control of the FWER. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Infrastructure of Taiwan photon source control network

International Nuclear Information System (INIS)

Chang, Y.T.; Kuo, C.H.; Cheng, Y.S.; Jenny Chen; Hsu, S.Y.; Wu, C.Y.; Hu, K.H.; Hsu, K.T.

2012-01-01

A reliable, flexible and secure network is essential for the Taiwan Photon Source (TPS) control system which is based upon the EPICS tool-kit framework. Subsystem sub-nets will connect to control system via EPICS based CA gateways for forwarding data and reducing network traffic. Combining cyber security technologies such as fire-wall, NAT and VLAN, control network is isolated to protect IOCs and accelerator components. Network management tools are used to improve network performance. Remote access mechanism will be constructed for maintenance and troubleshooting. The Ethernet is also used as field-bus for instruments such as power supplies. This paper will describe the system architecture for the TPS control network. Cabling topology, redundancy and maintainability are also discussed. (authors)

New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks.

Science.gov (United States)

Bouchard, M

2001-01-01

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.

Joint control algorithm in access network

Institute of Scientific and Technical Information of China (English)

2008-01-01

To deal with long probing delay and inaccurate probing results in the endpoint admission control method,a joint local and end-to-end admission control algorithm is proposed,which introduces local probing of access network besides end-to-end probing.Through local probing,the algorithm accurately estimated the resource status of the access network.Simulation shows that this algorithm can improve admission control performance and reduce users' average waiting time when the access network is heavily loaded.

Information and control in networks

CERN Document Server

Bernhardsson, Bo; Rantzer, Anders

2014-01-01

Information and Control in Networks demonstrates the way in which system dynamics and information flows intertwine as they evolve, and the central role played by information in the control of complex networked systems. It is a milestone on the road to that convergence from traditionally independent development of control theory and information theory which has emerged strongly in the last fifteen years, and is now a very active research field. In addition to efforts in control and information theory, the text is witness to strong research in such diverse fields as computer science, mathematics, and statistics. Aspects that are given specialist treatment include: ·                 data-rate theorems; ·                 computation and control over communication networks; ·                 decentralized stochastic control; ·                 Gaussian networks and Gaussian–Markov random fields; and ·                 routability ...

Control theory of digitally networked dynamic systems

CERN Document Server

Lunze, Jan

2013-01-01

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

Science.gov (United States)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1997-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

On the Design of Energy Efficient Optical Networks with Software Defined Networking Control Across Core and Access Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2013-01-01

This paper presents a Software Defined Networking (SDN) control plane based on an overlay GMPLS control model. The SDN control platform manages optical core networks (WDM/DWDM networks) and the associated access networks (GPON networks), which makes it possible to gather global information...... and enable wider areas' energy efficiency networking. The energy related information of the networks and the types of the traffic flows are collected and utilized for the end-to-end QoS provision. Dynamic network simulation results show that by applying different routing algorithms according to the type...... of traffic in the core networks, the energy efficiency of the network is improved without compromising the quality of service....

Additive Feed Forward Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1999-01-01

This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

Carrier ethernet network control plane based on the Next Generation Network

DEFF Research Database (Denmark)

Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert

2008-01-01

This paper contributes on presenting a step towards the realization of Carrier Ethernet control plane based on the next generation network (NGN). Specifically, transport MPLS (T-MPLS) is taken as the transport technology in Carrier Ethernet. It begins with providing an overview of the evolving...... architecture of the next generation network (NGN). As an essential candidate among the NGN transport technologies, the definition of Carrier Ethernet (CE) is also introduced here. The second part of this paper depicts the contribution on the T-MPLS based Carrier Ethernet network with control plane based on NGN...... at illustrating the improvement of the Carrier Ethernet network with the NGN control plane....

The APS control system network upgrade

International Nuclear Information System (INIS)

Sidorowicz, K. v.; Leibfritz, D.; McDowell, W. P.

1999-01-01

When it was installed,the Advanced Photon Source (APS) control system network was at the state-of-the-art. Different aspects of the system have been reported at previous meetings [1,2]. As loads on the controls network have increased due to newer and faster workstations and front-end computers, we have found performance of the system declining and have implemented an upgraded network. There have been dramatic advances in networking hardware in the last several years. The upgraded APS controls network replaces the original FDDI backbone and shared Ethernet hubs with redundant gigabit uplinks and fully switched 10/100 Ethernet switches with backplane fabrics in excess of 20 Gbits/s (Gbps). The central collapsed backbone FDDI concentrator has been replaced with a Gigabit Ethernet switch with greater than 30 Gbps backplane fabric. Full redundancy of the system has been maintained. This paper will discuss this upgrade and include performance data and performance comparisons with the original network

2016 Network Games, Control, and Optimization Conference

CERN Document Server

Jimenez, Tania; Solan, Eilon

2017-01-01

This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...

Software-Defined Congestion Control Algorithm for IP Networks

Directory of Open Access Journals (Sweden)

Yao Hu

2017-01-01

Full Text Available The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP network. However, it is possible that a software-defined approach can relieve the network congestion problem more efficiently. This approach has the characteristic of centralized control and can obtain a global topology for unified network management. In this paper, we propose a software-defined congestion control (SDCC algorithm for an IP network. We consider the difference between TCP and the user datagram protocol (UDP and propose a new method to judge node congestion. We initially apply the congestion control mechanism in the congested nodes and then optimize the link utilization to control network congestion.

Neural network-based model reference adaptive control system.

Science.gov (United States)

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

Parallel processing data network of master and slave transputers controlled by a serial control network

Science.gov (United States)

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

12 CFR 1731.5 - Internal controls, procedures, and training.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Internal controls, procedures, and training... HOUSING AND URBAN DEVELOPMENT SAFETY AND SOUNDNESS MORTGAGE FRAUD REPORTING § 1731.5 Internal controls, procedures, and training. An Enterprise shall establish adequate and efficient internal controls and...

Neural Network Based Load Frequency Control for Restructuring ...

African Journals Online (AJOL)

Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.

Control patterns in an healthcare network

NARCIS (Netherlands)

Kartseva, V.; Hulstijn, J.; Gordijn, J.; Tan, Y.H.

2010-01-01

To keep a network of enterprises sustainable, inter-organizational control measures are needed to detect or prevent opportunistic behaviour of network participants. We present a requirements engineering method for understanding control problems and designing solutions, based on an economic value

Congestion control and routing over satellite networks

Science.gov (United States)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE

Network performance for graphical control systems

International Nuclear Information System (INIS)

Clout, P.; Geib, M.; Westervelt, R.

1992-01-01

Vsystem is a toolbox for building graphically-based control systems. The real-tiem database component, Vaccess, includes all the networking support necessary to build multi-computer control systems. Vaccess has two modes of database access, synchronous and asynchronous. Vdraw is another component of Vsystem that allows developers and users to develop control screens and windows by drawing rather than programming. Based on X-windows, Vsystem provides the possibility of running Vdraw either on the workstation with the graphics or on the computer with the database. We have made some measurements on the cpu loading, elapsed time and the network loading to give some guidance in system configuration performance. It will be seen that asynchronous network access gives large performance increases and that the network database change notification protocol can be either more or less efficient than the X-window network protocol, depending on the graphical representation of the data. (author)

Survey procedure: Control and accountability of nuclear materials

International Nuclear Information System (INIS)

Van Ness, H.

1987-02-01

This procedure outlines the method by which the Department of Energy (DOE) San Francisco Operations Office (SAN) will plan and execute periodic field surveys of the Material Control and Accountability (MC and A) program and practices at designated contractors' facilities. The surveys will be conducted in accordance with DOE Order 5630.7, Control and Accountability of Nuclear Materials Surveys (7/8/81) to ascertain compliance with applicable DOE Orders and SAN Management Directives in the 5630 series, as well as the adequacy of the contractor's program and procedures. Surveys will be conducted by the Safeguards and Security Division of DOE-SAN. The survey team will review and evaluate the adequacy of the contractor's procedures and practices for nuclear material control and accounting by means of physical inventory, internal control, measurement and statistics, material control indicators, records and reports, and personnel training. The survey will include an audit of records and reports, observation of inventory procedures, an independent test of the inventory and a review and evaluation of the inventory differences, accidental losses, and normal operational losses as applicable to the facility to be surveyed

Application of the Wallingford Procedure to sewer network rehabilitation. Rehabilitacion de redes de alcantarillado. Aplicando el sistema de Wallingford

Energy Technology Data Exchange (ETDEWEB)

Gomez, M. (Universidad Politecnica de de Cataluna. Barcelona (Spain)); Lopez, R. (Universitat de Lleida. Lleida (Spain))

1999-01-01

In this paper we present a summary of the Wallingford Procedure application to sewer network rehabilitation studies. After the methodology of the Procedure is revised, an application to a sewer network of Sant Boi de Llobregat is showed. Flow survey campaigns, calibration and validation processes and the alternative proposed to improve the initial situation are described. Finally, the benefits to apply such methodologies to the sewer network rehabilitation analysis are exposed. (Author) 3 refs.

Application of the Wallingford Procedure to sewer network rehabilitation; Rehabilitacion de redes de alcantarillado. Aplicando el sistema de Wallingford

Energy Technology Data Exchange (ETDEWEB)

Gomez, M. [Universidad Politecnica de de Cataluna. Barcelona (Spain); Lopez, R. [Universitat de Lleida. Lleida (Spain)

1999-11-01

In this paper we present a summary of the Wallingford Procedure application to sewer network rehabilitation studies. After the methodology of the Procedure is revised, an application to a sewer network of Sant Boi de Llobregat is showed. Flow survey campaigns, calibration and validation processes and the alternative proposed to improve the initial situation are described. Finally, the benefits to apply such methodologies to the sewer network rehabilitation analysis are exposed. (Author) 3 refs.

Control of bursting synchronization in networks of Hodgkin-Huxley-type neurons with chemical synapses.

Science.gov (United States)

Batista, C A S; Viana, R L; Ferrari, F A S; Lopes, S R; Batista, A M; Coninck, J C P

2013-04-01

Thermally sensitive neurons present bursting activity for certain temperature ranges, characterized by fast repetitive spiking of action potential followed by a short quiescent period. Synchronization of bursting activity is possible in networks of coupled neurons, and it is sometimes an undesirable feature. Control procedures can suppress totally or partially this collective behavior, with potential applications in deep-brain stimulation techniques. We investigate the control of bursting synchronization in small-world networks of Hodgkin-Huxley-type thermally sensitive neurons with chemical synapses through two different strategies. One is the application of an external time-periodic electrical signal and another consists of a time-delayed feedback signal. We consider the effectiveness of both strategies in terms of protocols of applications suitable to be applied by pacemakers.

Enhanced vaccine control of epidemics in adaptive networks

Science.gov (United States)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Application of CPM procedures in mine ventilation

International Nuclear Information System (INIS)

Wang, Y.J.; Mutmansky, J.M.

1982-01-01

Mine ventilation analysis is an engineering discipline that can be considered a branch of the body of science known as network analysis. Likewise, the group of engineering procedures known as the critical path method (CPM) is considered a branch of network analysis. It is therefore not surprising that mine ventilation network analysis and CPM have many similarities. These similarities are useful in analyzing several types of mine ventilation problems and will be utilized in this paper. The analogy between the free split in a ventilation circuit and the critical path in a scheduling network has been recognized by Owili-Eger (1973). While this was recognized as a property of a general ventilation network, many important applications to controlled-splitting problems also exist. The mathematical procedures necessary to apply CPM and network methods have previously been presented (Wang, 1981; Wang, 1982). This paper will illustrate the implementation of these methods by application to mine ventilation networks

Autonomous Congestion Control in Delay-Tolerant Networks

Science.gov (United States)

Burleigh, Scott; Jennings, Esther; Schoolcraft, Joshua

2006-01-01

This presentation highlights communication congestion control in delay-tolerant networks (DTNs). Large-scale future space exploration will offer complex communication challenges that may be best addressed by establishing a network infrastructure. However, current internet techniques for congestion control are not well suited for operation of a network over interplanetary distances. An alternative, delay-tolerant technique for congestion control in a delay-tolerant network is presented. A simple DTN was constructed and an experimental congestion control mechanism was applied. The mechanism appeared to be effective and each router was able to make its bundle acceptance decisions autonomously. Future research will examine more complex topologies and alternative bundle acceptance rules that might enhance performance.

Effective augmentation of networked systems and enhancing pinning controllability

Science.gov (United States)

Jalili, Mahdi

2018-06-01

Controlling dynamics of networked systems to a reference state, known as pinning control, has many applications in science and engineering. In this paper, we introduce a method for effective augmentation of networked systems, while also providing high levels of pinning controllability for the final augmented network. The problem is how to connect a sub-network to an already existing network such that the pinning controllability is maximised. We consider the eigenratio of the augmented Laplacian matrix as a pinning controllability metric, and use graph perturbation theory to approximate the influence of edge addition on the eigenratio. The proposed metric can be effectively used to find the inter-network links connecting the disjoint networks. Also, an efficient link rewiring approach is proposed to further optimise the pinning controllability of the augmented network. We provide numerical simulations on synthetic networks and show that the proposed method is more effective than heuristic ones.

Trends in Integrated Ship Control Networking

DEFF Research Database (Denmark)

Jørgensen, N.; Nielsen, Jens Frederik Dalsgaard

1997-01-01

Integrated Ship Control systems can be designed as robust, distributed, autonomous control systems. The EU funded ATOMOS and ATOMOS II projects involves both technical and non technical aspects of this process. A reference modelling concept giving an outline of a generic ISC system covering...... the network and the equipment connected to it, a framework for verification of network functionality and performance by simulation and a general distribution platform for ISC systems, The ATOMOS Network, are results of this work....

Network aspects of the Fermilab control system

International Nuclear Information System (INIS)

Barton, H.R. Jr.

1977-01-01

The control system of the Fermi National Accelerator is a heavily computerized network of distributed processors. One part of the control system includes a multidrop network of eleven Lockheed MAC-16 processors, a Digital Equipment Corporation PDP-11 computer, a Xerox 530, and a Control Data 6600 system. These computers exchange information using serial hardware and dedicated cable buses. The individual functions of the central processing units in this network, the message protocols for computer communications, and design guidelines for future distributed processing control systems are discussed

Control of autonomous robot using neural networks

Science.gov (United States)

Barton, Adam; Volna, Eva

2017-07-01

The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

Optical network control plane for multi-domain networking

DEFF Research Database (Denmark)

Manolova, Anna Vasileva

This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic...... process are not enough for efficient TE in mesh multi-domain networks. Enhancing the protocol with multi-path dissemination capability, combined with the employment of an end-to-end TE metric proves to be a highly efficient solution. Simulation results show good performance characteristics of the proposed...... is not as essential for improved network performance as the length of the provided paths. Second, the issue of multi-domain survivability support is analyzed. An AS-disjoint paths is beneficial not only for resilience support, but also for facilitating adequate network reactions to changes in the network, which...

PID Neural Network Based Speed Control of Asynchronous Motor Using Programmable Logic Controller

Directory of Open Access Journals (Sweden)

MARABA, V. A.

2011-11-01

Full Text Available This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.

The Effects of Procedural Knowledge Transparency on Adoption in Corporate Social Networks

Science.gov (United States)

Jensen, Bjoern J. M.

2017-01-01

This dissertation investigated how a certain type of organizational knowledge sharing, procedural knowledge transparency, affected innovation adoption rates of members of a corporate social network within a large Scandinavian organization, in its two years of activity. It also explored the mediation of these effects by different types of…

Neural Networks for Non-linear Control

DEFF Research Database (Denmark)

Sørensen, O.

1994-01-01

This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....

An accelerator controls network designed for reliability and flexibility

International Nuclear Information System (INIS)

McDowell, W. P.; Sidorowicz, K. V.

1997-01-01

The APS accelerator control system is a typical modern system based on the standard control system model, which consists of operator interfaces to a network and computer-controlled interfaces to hardware. The network provides a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The network is an integral part of all modern control systems and network performance will determine many characteristics of a control system. This paper describes the methods used to provide redundancy for various network system components as well as methods used to provide comprehensive monitoring of this network. The effect of archiving tens of thousands of data points on a regular basis and the effect on the controls network will be discussed. Metrics are provided on the performance of the system under various conditions

Distributed medium access control in wireless networks

CERN Document Server

Wang, Ping

2013-01-01

This brief investigates distributed medium access control (MAC) with QoS provisioning for both single- and multi-hop wireless networks including wireless local area networks (WLANs), wireless ad hoc networks, and wireless mesh networks. For WLANs, an efficient MAC scheme and a call admission control algorithm are presented to provide guaranteed QoS for voice traffic and, at the same time, increase the voice capacity significantly compared with the current WLAN standard. In addition, a novel token-based scheduling scheme is proposed to provide great flexibility and facility to the network servi

Epidemic Propagation of Control Plane Failures in GMPLS Controlled Optical Transport Networks

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Fagertun, Anna Manolova

2013-01-01

In this paper, we investigate the behaviour of a dataplane-decoupled GMPLS control plane, when it is affected by failures that spread in the network in an epidemic manner. In particular, we consider network nodes to be either fully functional, or having a failed control plane, or having both...... a failed control and data plane. Through large-scale network simulation, we evaluate the effect of epidemically spreading control plane failures in terms of blocked connections requests and the amount of stranded capacity due to a dysfunctional control plane. Furthermore, we investigate the effect...... of the epidemic and the epidemic spreading intensity. In particular, networks with long epidemic durations do not necessarily result in worst performance in terms of blocked requests and capacity. Also epidemic scenarios, resulting in worst impact on the network availability does not necessarily result in worst...

Joint Design of Control and Power Efficiency in Wireless Networked Control System

Directory of Open Access Journals (Sweden)

Yan Wang

2014-01-01

Full Text Available This paper presents a joint design method for wireless networked control system (WNCS to balance both the demands of network service and the control performance. Since the problems of power consumption, communication reliability, and system stability exist simultaneously and interdependently in WNCS, most of the achieved results in the wireless network and wired networked control system cannot be used directly. To coordinate the three problems, sampling period is found to be the linking bridge. An adaptive sampling power efficiency algorithm is proposed to manage the power consumption such that it can meet the demands of network life span. The sampling period is designed to update periodically on the constraints of network schedulability and system stability. The convergence of the power efficiency algorithm is further proved. The sampling period is no longer a fixed value, however; thus, increasing the difficulty in modeling and controlling such a complicated time-varying system remains. In this work, a switched control system scheme is applied to model such a WNCS, and the effect of network-induced delay is considered. Switched feedback controllers are introduced to stabilize the WNCS, and some considerations on stability condition and the bounds of the update circle for renewing sampling period are discussed. A numerical example shows the effectiveness of the proposed method.

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

Accelerator and feedback control simulation using neural networks

International Nuclear Information System (INIS)

Nguyen, D.; Lee, M.; Sass, R.; Shoaee, H.

1991-05-01

Unlike present constant model feedback system, neural networks can adapt as the dynamics of the process changes with time. Using a process model, the ''Accelerator'' network is first trained to simulate the dynamics of the beam for a given beam line. This ''Accelerator'' network is then used to train a second ''Controller'' network which performs the control function. In simulation, the networks are used to adjust corrector magnetics to control the launch angle and position of the beam to keep it on the desired trajectory when the incoming beam is perturbed. 4 refs., 3 figs

Flexible Tube-Based Network Control, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...

Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

CERN Document Server

Su, Housheng

2013-01-01

Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

Analysis of Time Delay Simulation in Networked Control System

OpenAIRE

Nyan Phyo Aung; Zaw Min Naing; Hla Myo Tun

2016-01-01

The paper presents a PD controller for the Networked Control Systems (NCS) with delay. The major challenges in this networked control system (NCS) are the delay of the data transmission throughout the communication network. The comparative performance analysis is carried out for different delays network medium. In this paper, simulation is carried out on Ac servo motor control system using CAN Bus as communication network medium. The True Time toolbox of MATLAB is used for simulation to analy...

COORDINATION IN MULTILEVEL NETWORK-CENTRIC CONTROL SYSTEMS OF REGIONAL SECURITY: APPROACH AND FORMAL MODEL

Directory of Open Access Journals (Sweden)

A. V. Masloboev

2015-01-01

Full Text Available The paper deals with development of methods and tools for mathematical and computer modeling of the multilevel network-centric control systems of regional security. This research is carried out under development strategy implementation of the Arctic zone of the Russian Federation and national safeguarding for the period before 2020 in the Murmansk region territory. Creation of unified interdepartmental multilevel computer-aided system is proposed intended for decision-making information support and socio-economic security monitoring of the Arctic regions of Russia. The distinctive features of the investigated system class are openness, self-organization, decentralization of management functions and decision-making, weak hierarchy in the decision-making circuit and goal generation capability inside itself. Research techniques include functional-target approach, mathematical apparatus of multilevel hierarchical system theory and principles of network-centric control of distributed systems with pro-active components and variable structure. The work considers network-centric management local decisions coordination problem-solving within the multilevel distributed systems intended for information support of regional security. The coordination problem-solving approach and problem formalization in the multilevel network-centric control systems of regional security have been proposed based on developed multilevel recurrent hierarchical model of regional socio-economic system complex security. The model provides coordination of regional security indexes, optimized by the different elements of multilevel control systems, subject to decentralized decision-making. The model specificity consists in application of functional-target technology and mathematical apparatus of multilevel hierarchical system theory for coordination procedures implementation of the network-centric management local decisions. The work-out and research results can find further

Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

DEFF Research Database (Denmark)

Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

2015-01-01

% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control...... motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles...

Adaptive mechanism-based congestion control for networked systems

Science.gov (United States)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

An Improved Car-Following Model in Vehicle Networking Based on Network Control

Directory of Open Access Journals (Sweden)

D. Y. Kong

2014-01-01

Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

Quality control procedures in positron tomography

International Nuclear Information System (INIS)

Spinks, T.; Jones, T.; Heather, J.; Gilardi, M.

1989-01-01

The derivation of physiological parameters in positron tomography relies on accurate calibration of the tomograph. Normally, the calibration relates image pixel count density to the count rate from an external blood counter per unit activity concentration in each device. The quality control of the latter is simple and relies on detector stability assessed by measurement of a standard source of similar geometry to a blood sample. The quality control of the tomographic data depends on (i) detector stability, (ii) uniformity of calibration and normalisation sources and (iii) reproducibility of the attenuation correction procedure. A quality control procedure has been developed for an 8 detector ring (15 transaxial plane) tomograph in which detector response is assessed by acquiring data from retractable transmission ring sources. These are scanned daily and a print out of detector efficiencies is produced as well as changes from a given data. This provides the raw data from which decisions on recalibration or renormalisation are made. (orig.)

Application of reflective memory network in Tokamak fast controller

International Nuclear Information System (INIS)

Weng Chuqiao; Zhang Ming; Liu Rui; Zheng Wei; Zhuang Ge

2014-01-01

A specific application of reflective memory network in Tokamak fast controller was introduced in this paper. The PMC-5565 reflective memory card and ACC-5565 network hub were used to build a reflective memory real-time network to test its real- time function. The real-time, rapidity and determinacy of the time delay for fast controller controlling power device under the reflective memory network were tested in the LabVIEW RT real-time operation system. Depending on the reflective memory technology, the data in several fast controllers were synchronized, and multiple control tasks using a single control task were finished. The experiment results show that the reflective memory network can meet the real-time requirements for fast controller to perform the feedback control over devices. (authors)

Intergrated approach to quality control procedures of radioisotopes and radiopharmaceuticals

International Nuclear Information System (INIS)

Rohani Mohamad

1986-01-01

Various aspects of the quality control procedures for radioisotopes and radiopharmaceuticals have been discussed. The paper high lighted those procedures that are important in ensuring the efficacy of the product. It also gives a general idea of the various procedures that are actually carried out by the Quality Control Section. (A.J.)

Controlling centrality in complex networks

Science.gov (United States)

Nicosia, V.; Criado, R.; Romance, M.; Russo, G.; Latora, V.

2012-01-01

Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We show that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We found that many large networks from the real world have surprisingly small controlling sets, containing even less than 5 – 10% of the nodes. PMID:22355732

Direct adaptive control using feedforward neural networks

OpenAIRE

Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

2003-01-01

ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

Automated Kick Control Procedure for an Influx in Managed Pressure Drilling Operations

Directory of Open Access Journals (Sweden)

Jing Zhou

2016-01-01

Full Text Available Within drilling of oil and gas wells, the Managed Pressure Drilling (MPD method with active control of wellbore pressure during drilling has partly evolved from conventional well control procedures. However, for MPD operations the instrumentation is typically more extensive compared to conventional drilling. Despite this, any influx of formation fluids (commonly known as a kick during MPD operations is typically handled by conventional well control methods, at least if the kick is estimated to be larger than a threshold value. Conventional well control procedures rely on manual control of the blow out preventer, pumps, and choke valves and do not capitalize on the benefits from the instrumentation level associated with MPD. This paper investigates two alternative well control procedures specially adapted to backpressure MPD: the dynamic shut-in (DSI procedure and the automatic kick control (AKC procedure. Both methods capitalize on improvements in Pressure While Drilling (PWD technology. A commercially available PWD tool buffers high-resolution pressure measurements, which can be used in an automated well control procedure. By using backpressure MPD, the choke valve opening is tuned automatically using a feedback-feedforward control method. The two procedures are evaluated using a high fidelity well flow model and cases from a North Sea drilling operation are simulated. The results show that using AKC procedure reduces the time needed to establish control of the well compared to DSI procedure. It also indicates that the AKC procedure reduces the total kick size compared to the DSI procedure, and thereby reduces the risk of lost circulation.

A numerical procedure for transient free surface seepage through fracture networks

Science.gov (United States)

Jiang, Qinghui; Ye, Zuyang; Zhou, Chuangbing

2014-11-01

A parabolic variational inequality (PVI) formulation is presented for the transient free surface seepage problem defined for a whole fracture network. Because the seepage faces are specified as Signorini-type conditions, the PVI formulation can effectively eliminate the singularity of spillpoints that evolve with time. By introducing a continuous penalty function to replace the original Heaviside function, a finite element procedure based on the PVI formulation is developed to predict the transient free surface response in the fracture network. The effects of the penalty parameter on the solution precision are analyzed. A relative error formula for evaluating the flow losses at steady state caused by the penalty parameter is obtained. To validate the proposed method, three typical examples are solved. The solutions for the first example are compared with the experimental results. The results from the last two examples further demonstrate that the orientation, extent and density of fractures significantly affect the free surface seepage behavior in the fracture network.

Cloud-based Networked Visual Servo Control

OpenAIRE

Wu, Haiyan; Lu, Lei; Chen, Chih-Chung; Hirche, Sandra; Kühnlenz, Kolja

2013-01-01

The performance of vision-based control systems, in particular of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitti...

A source-controlled data center network model.

Science.gov (United States)

Yu, Yang; Liang, Mangui; Wang, Zhe

2017-01-01

The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS.

A source-controlled data center network model

Science.gov (United States)

Yu, Yang; Liang, Mangui; Wang, Zhe

2017-01-01

The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS. PMID:28328925

Flexible brain network reconfiguration supporting inhibitory control.

Science.gov (United States)

Spielberg, Jeffrey M; Miller, Gregory A; Heller, Wendy; Banich, Marie T

2015-08-11

The ability to inhibit distracting stimuli from interfering with goal-directed behavior is crucial for success in most spheres of life. Despite an abundance of studies examining regional brain activation, knowledge of the brain networks involved in inhibitory control remains quite limited. To address this critical gap, we applied graph theory tools to functional magnetic resonance imaging data collected while a large sample of adults (n = 101) performed a color-word Stroop task. Higher demand for inhibitory control was associated with restructuring of the global network into a configuration that was more optimized for specialized processing (functional segregation), more efficient at communicating the output of such processing across the network (functional integration), and more resilient to potential interruption (resilience). In addition, there were regional changes with right inferior frontal sulcus and right anterior insula occupying more central positions as network hubs, and dorsal anterior cingulate cortex becoming more tightly coupled with its regional subnetwork. Given the crucial role of inhibitory control in goal-directed behavior, present findings identifying functional network organization supporting inhibitory control have the potential to provide additional insights into how inhibitory control may break down in a wide variety of individuals with neurological or psychiatric difficulties.

Controllability and observability of Boolean networks arising from biology

Science.gov (United States)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Practical synchronization on complex dynamical networks via optimal pinning control

Science.gov (United States)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

Science.gov (United States)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Fusion Control of Flexible Logic Control and Neural Network

Directory of Open Access Journals (Sweden)

Lihua Fu

2014-01-01

Full Text Available Based on the basic physical meaning of error E and error variety EC, this paper analyzes the logical relationship between them and uses Universal Combinatorial Operation Model in Universal Logic to describe it. Accordingly, a flexible logic control method is put forward to realize effective control on multivariable nonlinear system. In order to implement fusion control with artificial neural network, this paper proposes a new neuron model of Zero-level Universal Combinatorial Operation in Universal Logic. And the artificial neural network of flexible logic control model is implemented based on the proposed neuron model. Finally, stability control, anti-interference control of double inverted-pendulum system, and free walking of cart pendulum system on a level track are realized, showing experimentally the feasibility and validity of this method.

TCP Congestion Control for the Networks with Markovian Jump Parameters

Directory of Open Access Journals (Sweden)

MOMENI, H. R.

2011-05-01

Full Text Available This paper is concerned with the problem of TCP congestion control for the class of communication networks with random parameters. The linear dynamic model of TCP New Reno in congestion avoidance mode is considered which contains round trip delays in both state and input. The randomness of link capacity, round trip time delay and the number of TCP sessions is modeled with a continuous-time finite state Markov process. An Active Queue Management (AQM technique is then used to adjust the queue level of the congested link to a predefined value. For this purpose, a dynamic output feedback controller with mode dependent parameters is synthesized to stochastically stabilize the TCP/AQM dynamics. The procedure of the control synthesis is implemented by solving a linear matrix inequality (LMI. The results are tested within a simulation example and the effectiveness of the proposed design method is verified.

Optimal control of epidemic information dissemination over networks.

Science.gov (United States)

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Bio-inspired spiking neural network for nonlinear systems control.

Science.gov (United States)

Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

2018-08-01

Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

Science.gov (United States)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Environmental control procedures at the Savannah River Plant

International Nuclear Information System (INIS)

Sheldon, E.B.

1975-01-01

New environmental control activities in the past year at SRP have included improved control and reporting procedures for chemical spills, reclamation of high-value scrap from wastes, new disposal methods for solid wastes not suitable for the sanitary landfill, improved oil containment, and reduction of sediment discharges to on-plant streams. Interdepartmental committees provide the primary routes for planning and coordinating environmental protection throughout SRP. An improved site-use coordination procedure, developed and implemented by ERDA-SR, has provided more effective control and communication pertaining to activities of the several organizations actively using the 300-square-mile SRP site. (auth)

Generalized Mutual Synchronization between Two Controlled Interdependent Networks

OpenAIRE

Xu, Quan; Zhuang, Shengxian; Hu, Dan; Zeng, Yingfeng; Xiao, Jian

2014-01-01

This paper mainly focuses on the generalized mutual synchronization between two controlled interdependent networks. First, we propose the general model of controlled interdependent networks $A$ and $B$ with time-varying internetwork delays coupling. Then, by constructing Lyapunov functions and utilizing adaptive control technique, some sufficient conditions are established to ensure that the mutual synchronization errors between the state variables of networks $A$ and $B$ can asymptotically c...

Developing a Procedure for Segmenting Meshed Heat Networks of Heat Supply Systems without Outflows

Science.gov (United States)

Tokarev, V. V.

2018-06-01

The heat supply systems of cities have, as a rule, a ring structure with the possibility of redistributing the flows. Despite the fact that a ring structure is more reliable than a radial one, the operators of heat networks prefer to use them in normal modes according to the scheme without overflows of the heat carrier between the heat mains. With such a scheme, it is easier to adjust the networks and to detect and locate faults in them. The article proposes a formulation of the heat network segmenting problem. The problem is set in terms of optimization with the heat supply system's excessive hydraulic power used as the optimization criterion. The heat supply system computer model has a hierarchically interconnected multilevel structure. Since iterative calculations are only carried out for the level of trunk heat networks, decomposing the entire system into levels allows the dimensionality of the solved subproblems to be reduced by an order of magnitude. An attempt to solve the problem by fully enumerating possible segmentation versions does not seem to be feasible for systems of really existing sizes. The article suggests a procedure for searching rational segmentation of heat supply networks with limiting the search to versions of dividing the system into segments near the flow convergence nodes with subsequent refining of the solution. The refinement is performed in two stages according to the total excess hydraulic power criterion. At the first stage, the loads are redistributed among the sources. After that, the heat networks are divided into independent fragments, and the possibility of increasing the excess hydraulic power in the obtained fragments is checked by shifting the division places inside a fragment. The proposed procedure has been approbated taking as an example a municipal heat supply system involving six heat mains fed from a common source, 24 loops within the feeding mains plane, and more than 5000 consumers. Application of the proposed

Deep Convolutional Generative Adversarial Network for Procedural 3D Landscape Generation Based on DEM

OpenAIRE

Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig; Billeskov, Jonas Aksel

2018-01-01

This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM) of the alps. During map generation, the batch size and learning rate were optimized for the most efficient and satisfying map production. The diversity of the final output was tested against Perlin noise u...

Local and global control of ecological and biological networks

OpenAIRE

Alessandro Ferrarini

2014-01-01

Recently, I introduced a methodological framework so that ecological and biological networks can be controlled both from inside and outside by coupling network dynamics and evolutionary modelling. The endogenous control requires the network to be optimized at the beginning of its dynamics (by acting upon nodes, edges or both) so that it will then go inertially to the desired state. Instead, the exogenous control requires that exogenous controllers act upon the network at each time step. By th...

Cell fate reprogramming by control of intracellular network dynamics

Science.gov (United States)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Algorithm Design on Network Game of Chinese Chess

Science.gov (United States)

Xianmei, Fang

This paper describes the current situation of domestic network game. Contact the present condition of the local network game currently, we inquired to face to a multithread tcp client and server, such as Chinese chess, according to the information, and study the contents and meanings. Combining the Java of basic knowledge, the article study the compiling procedure facing to the object according to the information in Java Swing usage, and the method of the network procedure. The article researched the method and processes of the network procedure carry on the use of Sprocket under the Java Swing. Understood the basic process of compiling procedure using Java and how to compile a network procedure. The most importance is how a pair of machines correspondence-C/S the service system-is carried out. From here, we put forward the data structure,the basic calculate way of the network game- Chinese chess, and how to design and realize the server and client of that procedure. The online games -- chess design can be divided into several modules as follows: server module, client module and the control module.

Adaptive nonlinear control using input normalized neural networks

International Nuclear Information System (INIS)

Leeghim, Henzeh; Seo, In Ho; Bang, Hyo Choong

2008-01-01

An adaptive feedback linearization technique combined with the neural network is addressed to control uncertain nonlinear systems. The neural network-based adaptive control theory has been widely studied. However, the stability analysis of the closed-loop system with the neural network is rather complicated and difficult to understand, and sometimes unnecessary assumptions are involved. As a result, unnecessary assumptions for stability analysis are avoided by using the neural network with input normalization technique. The ultimate boundedness of the tracking error is simply proved by the Lyapunov stability theory. A new simple update law as an adaptive nonlinear control is derived by the simplification of the input normalized neural network assuming the variation of the uncertain term is sufficiently small

Organization of Multi-controller Interaction in Software Defined Networks

Directory of Open Access Journals (Sweden)

Sergey V. Morzhov

2018-01-01

Full Text Available Software Defined Networking (SDN is a promising paradigm for network management. It is a centralized network intelligence on a dedicated server, which runs network operating system, and is called SDN controller. It was assumed that such an architecture should have an improved network performance and monitoring. However, the centralized control architecture of the SDNs brings novel challenges to reliability, scalability, fault tolerance and interoperability. These problems are especially acute for large data center networks and can be solved by combining SDN controllers into clusters, called multi-controllers. Multi-controller architecture became very important for SDN-enabled networks nowadays. This paper gives a comprehensive overview of SDN multi-controller architectures. The authors review several most popular distributed controllers in order to indicate their strengths and weaknesses. They also investigate and classify approaches used. This paper explains in details the difference among various types of multi-controller architectures, the distribution method and the communication system. Furthermore, it provides already implemented architectures and some examples of architectures under consideration by describing their design, communication process, and performance results. In this paper, the authors show their own classification of multi-controllers and claim that, despite the existence of undeniable advantages, all reviewed controllers have serious drawbacks, which must be eliminated. These drawbacks hamper the development of multi-controllers and their widespread adoption in corporate networks. In the end, the authors conclude that now it is impossible to find a solution capable to solve all the tasks assigned to it adequately and fully. The article is published in the authors’ wording.

Neural Networks for Modeling and Control of Particle Accelerators

CERN Document Server

Edelen, A.L.; Chase, B.E.; Edstrom, D.; Milton, S.V.; Stabile, P.

2016-01-01

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Network for Optimization of Existing Control Systems

DEFF Research Database (Denmark)

Madsen, Per Printz

1995-01-01

The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....

Optimization of robustness of interdependent network controllability by redundant design.

Directory of Open Access Journals (Sweden)

Zenghu Zhang

Full Text Available Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy or DBS (degree based strategy for node backup and HDF(high degree first for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability.

Human factors in network security

OpenAIRE

Jones, Francis B.

1991-01-01

Human factors, such as ethics and education, are important factors in network information security. This thesis determines which human factors have significant influence on network security. Those factors are examined in relation to current security devices and procedures. Methods are introduced to evaluate security effectiveness by incorporating the appropriate human factors into network security controls

Submodularity in dynamics and control of networked systems

CERN Document Server

Clark, Andrew; Bushnell, Linda; Poovendran, Radha

2016-01-01

This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllabilit...

Control of fluxes in metabolic networks

Science.gov (United States)

Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

2016-01-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

Minimizing communication cost among distributed controllers in software defined networks

Science.gov (United States)

Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

2016-08-01

Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

Active Engine Mounting Control Algorithm Using Neural Network

Directory of Open Access Journals (Sweden)

Fadly Jashi Darsivan

2009-01-01

Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.

Optimization-Based Approaches to Control of Probabilistic Boolean Networks

Directory of Open Access Journals (Sweden)

Koichi Kobayashi

2017-02-01

Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.

Predictive Control of Networked Multiagent Systems via Cloud Computing.

Science.gov (United States)

Liu, Guo-Ping

2017-01-18

This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

Controlling extreme events on complex networks

Science.gov (United States)

Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

2014-08-01

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

Logistic control in automated transportation networks

NARCIS (Netherlands)

Ebben, Mark

2001-01-01

Increasing congestion problems lead to a search for alternative transportation systems. Automated transportation networks, possibly underground, are an option. Logistic control systems are essential for future implementations of such automated transportation networks. This book contributes to the

Controls from remote through Social networks

Directory of Open Access Journals (Sweden)

Alessandra Ingrao

2016-03-01

Full Text Available The Author focuses on the recently reformed provisions regulating the employer’s power to control from remote the employees’ activities (art. 4 of the Workers Statute, with particular regard to controls performed by means of Social networks.Such controls are in fact extremely powerful due to the versatile and multi-purpose character of Social networks, which may also be used as a working device. A widespread case law shows indeed that employer’s controls may cost a worker his job.Therefore, after the reform, all employees will have to read carefully the employer’s Privacy policies, before accessing socials during the worktime to express opinions and/or frustrations.

The network of global corporate control.

Science.gov (United States)

Vitali, Stefania; Glattfelder, James B; Battiston, Stefano

2011-01-01

The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international ownership network, along with the computation of the control held by each global player. We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. This core can be seen as an economic "super-entity" that raises new important issues both for researchers and policy makers.

On the Control of Consensus Networks: Theory and Applications

Science.gov (United States)

Hudoba de Badyn, Mathias

Signed networks allow the study of positive and negative interactions between agents. In this thesis, three papers are presented that address controllability of networked dynamics. First, controllability of signed consensus networks is approached from a symmetry perspective, for both linear and nonlinear consensus protocols. It is shown that the graph-theoretic property of signed networks known as structural balance renders the consensus protocol uncontrollable when coupled with a certain type of symmetry. Stabilizability and output controllability of signed linear consensus is also examined, as well as a data-driven approach to finding bipartite consensus stemming from structural balance for signed nonlinear consensus. Second, an algorithm is constructed that allows one to grow a network while preserving controllability, and some generalizations of this algorithm are presented. Submodular optimization is used to analyze a second algorithm that adds nodes to a network to maximize the network connectivity.

Optimization of controllability and robustness of complex networks by edge directionality

Science.gov (United States)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

A normalized PID controller in networked control systems with varying time delays.

Science.gov (United States)

Tran, Hoang-Dung; Guan, Zhi-Hong; Dang, Xuan-Kien; Cheng, Xin-Ming; Yuan, Fu-Shun

2013-09-01

It requires not only simplicity and flexibility but also high specified stability and robustness of system to design a PI/PID controller in such complicated networked control systems (NCSs) with delays. By gain and phase margins approach, this paper proposes a novel normalized PI/PID controller for NCSs based on analyzing the stability and robustness of system under the effect of network-induced delays. Specifically, We take into account the total measured network delays to formulate the gain and phase margins of the closed-loop system in the form of a set of equations. With pre-specified values of gain and phase margins, this set of equations is then solved for calculating the closed forms of control parameters which enable us to propose the normalized PI/PID controller simultaneously satisfying the following two requirements: (1) simplicity without re-solving the optimization problem for a new process, (2) high flexibility to cope with large scale of random delays and deal with many different processes in different conditions of network. Furthermore, in our method, the upper bound of random delay can be estimated to indicate the operating domain of proposed PI/PID controller. Finally, simulation results are shown to demonstrate the advantages of our proposed controller in many situations of network-induced delays. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Neural Networks for Modeling and Control of Particle Accelerators

Science.gov (United States)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Controller tuning with evolutionary multiobjective optimization a holistic multiobjective optimization design procedure

CERN Document Server

Reynoso Meza, Gilberto; Sanchis Saez, Javier; Herrero Durá, Juan Manuel

2017-01-01

This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.

Wavelet neural network load frequency controller

International Nuclear Information System (INIS)

Hemeida, Ashraf Mohamed

2005-01-01

This paper presents the feasibility of applying a wavelet neural network (WNN) approach for the load frequency controller (LFC) to damp the frequency oscillations of two area power systems due to load disturbances. The present intelligent control system trained the wavelet neural network (WNN) controller on line with adaptive learning rates, which are derived in the sense of a discrete type Lyapunov stability theorem. The present WNN controller is designed individually for each area. The proposed technique is applied successfully for a wide range of operating conditions. The time simulation results indicate its superiority and effectiveness over the conventional approach. The effects of consideration of the governor dead zone on the system performance are studied using the proposed controller and the conventional one

Network device interface for digitally interfacing data channels to a controller via a network

Science.gov (United States)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

2009-01-01

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

Goal-congruent default network activity facilitates cognitive control.

Science.gov (United States)

Spreng, R Nathan; DuPre, Elizabeth; Selarka, Dhawal; Garcia, Juliana; Gojkovic, Stefan; Mildner, Judith; Luh, Wen-Ming; Turner, Gary R

2014-10-15

Substantial neuroimaging evidence suggests that spontaneous engagement of the default network impairs performance on tasks requiring executive control. We investigated whether this impairment depends on the congruence between executive control demands and internal mentation. We hypothesized that activation of the default network might enhance performance on an executive control task if control processes engage long-term memory representations that are supported by the default network. Using fMRI, we scanned 36 healthy young adult humans on a novel two-back task requiring working memory for famous and anonymous faces. In this task, participants (1) matched anonymous faces interleaved with anonymous face, (2) matched anonymous faces interleaved with a famous face, or (3) matched a famous faces interleaved with an anonymous face. As predicted, we observed a facilitation effect when matching famous faces, compared with anonymous faces. We also observed greater activation of the default network during these famous face-matching trials. The results suggest that activation of the default network can contribute to task performance during an externally directed executive control task. Our findings provide evidence that successful activation of the default network in a contextually relevant manner facilitates goal-directed cognition. Copyright © 2014 the authors 0270-6474/14/3414108-07$15.00/0.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

OpenAIRE

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-01-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solv...

Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Directory of Open Access Journals (Sweden)

Hui-ying Chen

2013-01-01

Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.

Topology Control in Aerial Multi-Beam Directional Networks

Science.gov (United States)

2017-04-24

Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology ...underlying challenges to topology control in multi-beam direction networks. Two topology control algorithms are developed: a centralized algorithm

Energy efficient topology control algorithm for wireless mesh networks

CSIR Research Space (South Africa)

Aron, FO

2008-08-01

Full Text Available The control of the topology of a network makes it possible for the network nodes to reduce their power of transmission while ensuring that network connectivity is preserved. This paper explains the need for energy consumption control in Wireless...

A general digital computer procedure for synthesizing linear automatic control systems

International Nuclear Information System (INIS)

Cummins, J.D.

1961-10-01

The fundamental concepts required for synthesizing a linear automatic control system are considered. A generalized procedure for synthesizing automatic control systems is demonstrated. This procedure has been programmed for the Ferranti Mercury and the IBM 7090 computers. Details of the programmes are given. The procedure uses the linearized set of equations which describe the plant to be controlled as the starting point. Subsequent computations determine the transfer functions between any desired variables. The programmes also compute the root and phase loci for any linear (and some non-linear) configurations in the complex plane, the open loop and closed loop frequency responses of a system, the residues of a function of the complex variable 's' and the time response corresponding to these residues. With these general programmes available the design of 'one point' automatic control systems becomes a routine scientific procedure. Also dynamic assessments of plant may be carried out. Certain classes of multipoint automatic control problems may also be solved with these procedures. Autonomous systems, invariant systems and orthogonal systems may also be studied. (author)

Observability and Controllability of Networks: Symmetry in Representations of Brains and Controllers for Epidemics

Science.gov (United States)

Schiff, Steven

Observability and controllability are essential concepts to the design of predictive observer models and feedback controllers of networked systems. We present a numerical and group representational framework, to quantify the observability and controllability of nonlinear networks with explicit symmetries that shows the connection between symmetries and nonlinear measures of observability and controllability. In addition to the topology of brain networks, we have advanced our ability to represent network nodes within the brain using conservation principles and more accurate biophysics that unifies the dynamics of spikes, seizures, and spreading depression. Lastly, we show how symmetries in controller design can be applied to infectious disease epidemics. NIH Grants 1R01EB014641, 1DP1HD086071.

High intensity proton accelerator controls network upgrade

International Nuclear Information System (INIS)

Krempaska, R.; Bertrand, A.; Lendzian, F.; Lutz, H.

2012-01-01

The High Intensity Proton Accelerator (HIPA) control system network is spread through a vast area in PSI and it was grown historically in an unorganized way. The miscellaneous network hardware infrastructure and the lack of the documentation and components overview could no longer guarantee the reliability of the control system and the facility operation. Therefore, a new network, based on modern network topology, PSI standard hardware with monitoring and detailed documentation and overview was needed. The number of active components has been reduced from 25 to 9 Cisco Catalyst 24- or 48-port switches. They are the same type as other PSI switches, thus a replacement emergency stock is not an issue anymore. We would like to present how we successfully achieved this goal and the advantages of the clean and well documented network infrastructure. (authors)

Implementation of PID autotuning procedure in PLC controller

Directory of Open Access Journals (Sweden)

Daniun Marcin

2017-01-01

Full Text Available In this paper, we present the automatic PID tuning procedure based on the Method of Moments and AMIGO tuning rules. The advantage of the Method of Moments is that the time constant and transport delay are estimated at the areas rather than on the individual points. This results in high resistance to the measurement noises. The sensitivity to measurement noises is a serious problem in other autotuning methods. The second advantage of this method is that it approximates plant during identification process to first order model with time delay. We combined the Method of Moments with the AMIGO tuning rules and implemented this combination as a stand-alone autotuning procedure in Siemens S7-1200 PLC controller. Next, we compared this method with two built-in PID autotuning procedures which were available in Siemens S7-1200 PLC controller. The procedure was tested for three types of plant models: with lag-dominated, balanced, and delay-dominated dynamics. We simulated the plants on a PC in Matlab R2013a. The connection between the PC and PLC was maintained through a National Instruments data acquisition board, NI PCI-6229. We conducted tests for step change in the set point, trajectory tracking, and load disturbances. To assess control quality, we used IAE index. We limited our research to PI algorithm. The results prove that proposed method was better than two built-in tuning methods provided by Siemens, oscillating between a few and even a dozen percent in most cases. The proposed method is universal and can be implemented in any PLC controller.

Optimization of stochastic discrete systems and control on complex networks computational networks

CERN Document Server

Lozovanu, Dmitrii

2014-01-01

This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...

Controllability of Weighted and Directed Networks with Nonidentical Node Dynamics

Directory of Open Access Journals (Sweden)

Linying Xiang

2013-01-01

Full Text Available The concept of controllability from control theory is applied to weighted and directed networks with heterogenous linear or linearized node dynamics subject to exogenous inputs, where the nodes are grouped into leaders and followers. Under this framework, the controllability of the controlled network can be decomposed into two independent problems: the controllability of the isolated leader subsystem and the controllability of the extended follower subsystem. Some necessary and/or sufficient conditions for the controllability of the leader-follower network are derived based on matrix theory and graph theory. In particular, it is shown that a single-leader network is controllable if it is a directed path or cycle, but it is uncontrollable for a complete digraph or a star digraph in general. Furthermore, some approaches to improving the controllability of a heterogenous network are presented. Some simulation examples are given for illustration and verification.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

Science.gov (United States)

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks

Science.gov (United States)

Li, Yuhong

2018-01-01

In this paper, we propose a novel algorithm—parallel adaptive quantum genetic algorithm—which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes. PMID:29554140

Active queue management controller design for TCP communication networks: Variable structure control approach

International Nuclear Information System (INIS)

Chen, C.-K.; Liao, T.-L.; Yan, J.-J.

2009-01-01

On the basis of variable structure control (VSC), an active queue management (AQM) controller is presented for a class of TCP communication networks. In the TCP/IP networks, the packet drop probability is limited between 0 and 1. Therefore, we modeled TCP/AQM as a rate-based non-linear system with a saturated input. The objective of the VSC-based AQM controller is to achieve the desired queue size and to guarantee the asymptotic stability of the closed-loop TCP non-linear system with saturated input. The performance and effectiveness of the proposed control law are then validated for different network scenarios through numerical simulations in both MATLAB and Network Simulator-2 (NS-2). Both sets of simulation results have confirmed that the proposed scheme outperforms other AQM schemes.

Active queue management controller design for TCP communication networks: Variable structure control approach

Energy Technology Data Exchange (ETDEWEB)

Chen, C.-K. [Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan (China); Liao, T.-L. [Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan (China)], E-mail: tlliao@mail.ncku.edu; Yan, J.-J. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)

2009-04-15

On the basis of variable structure control (VSC), an active queue management (AQM) controller is presented for a class of TCP communication networks. In the TCP/IP networks, the packet drop probability is limited between 0 and 1. Therefore, we modeled TCP/AQM as a rate-based non-linear system with a saturated input. The objective of the VSC-based AQM controller is to achieve the desired queue size and to guarantee the asymptotic stability of the closed-loop TCP non-linear system with saturated input. The performance and effectiveness of the proposed control law are then validated for different network scenarios through numerical simulations in both MATLAB and Network Simulator-2 (NS-2). Both sets of simulation results have confirmed that the proposed scheme outperforms other AQM schemes.

Feedback Gating Control for Network Based on Macroscopic Fundamental Diagram

Directory of Open Access Journals (Sweden)

YangBeibei Ji

2016-01-01

Full Text Available Empirical data from Yokohama, Japan, showed that a macroscopic fundamental diagram (MFD of urban traffic provides for different network regions a unimodal low-scatter relationship between network vehicle density and network space-mean flow. This provides new tools for network congestion control. Based on MFD, this paper proposed a feedback gating control policy which can be used to mitigate network congestion by adjusting signal timings of gating intersections. The objective of the feedback gating control model is to maximize the outflow and distribute the allowed inflows properly according to external demand and capacity of each gating intersection. An example network is used to test the performance of proposed feedback gating control model. Two types of background signalization types for the intersections within the test network, fixed-time and actuated control, are considered. The results of extensive simulation validate that the proposed feedback gating control model can get a Pareto improvement since the performance of both gating intersections and the whole network can be improved significantly especially under heavy demand situations. The inflows and outflows can be improved to a higher level, and the delay and queue length at all gating intersections are decreased dramatically.

REAL TIME ANALYSIS OF WIRELESS CONTROLLER AREA NETWORK

Directory of Open Access Journals (Sweden)

Gerardine Immaculate Mary

2014-09-01

Full Text Available It is widely known that Control Area Networks (CAN are used in real-time, distributed and parallel processing which cover manufacture plants, humanoid robots, networking fields, etc., In applications where wireless conditions are encountered it is convenient to continue the exchange of CAN frames within the Wireless CAN (WCAN. The WCAN considered in this research is based on wireless token ring protocol (WTRP; a MAC protocol for wireless networks to reduce the number of retransmissions due to collision and the wired counterpart CAN attribute on message based communication. WCAN uses token frame method to provide channel access to the nodes in the system. This method allow all the nodes to share common broadcast channel by taken turns in transmitting upon receiving the token frame which is circulating within the network for specified amount of time. This method provides high throughput in bounded latency environment, consistent and predictable delays and good packet delivery ratio. The most important factor to consider when evaluating a control network is the end-to-end time delay between sensors, controllers, and actuators. The correct operation of a control system depends on the timeliness of the data coming over the network, and thus, a control network should be able to guarantee message delivery within a bounded transmission time. The proposed WCAN is modeled and simulated using QualNet, and its average end to end delay and packet delivery ratio (PDR are calculated. The parameters boundaries of WCAN are evaluated to guarantee a maximum throughput and a minimum latency time, in the case of wireless communications, precisely WCAN.

Generalized Mutual Synchronization between Two Controlled Interdependent Networks

Directory of Open Access Journals (Sweden)

Quan Xu

2014-01-01

Full Text Available This paper mainly focuses on the generalized mutual synchronization between two controlled interdependent networks. First, we propose the general model of controlled interdependent networks A and B with time-varying internetwork delays coupling. Then, by constructing Lyapunov functions and utilizing adaptive control technique, some sufficient conditions are established to ensure that the mutual synchronization errors between the state variables of networks A and B can asymptotically converge to zero. Finally, two numerical examples are given to illustrate the effectiveness of the theoretical results and to explore potential application in future smart grid. The simulation results also show how interdependent topologies and internetwork coupling delays influence the mutual synchronizability, which help to design interdependent networks with optimal mutual synchronizability.

Controlling the dynamics of multi-state neural networks

International Nuclear Information System (INIS)

Jin, Tao; Zhao, Hong

2008-01-01

In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

Development of Active External Network Topology Module for Floodlight SDN Controller

Directory of Open Access Journals (Sweden)

A. A. Noskov

2015-01-01

Full Text Available Traditional network architecture is inflexible and complicated. This observation has led to a paradigm shift towards software-defined networking (SDN, where network management level is separated from data forwarding level. This change was made possible by control plane transfer from the switching equipment to software modules that run on a dedicated server, called the controller (or network operating system, or network applications, that work with this controller. Methods of representation, storage and communication interfaces with network topology elements are the most important aspects of network operating systems available to SDN user because performance of some key controller modules is heavily dependent on internal representation of the network topology. Notably, firewall and routing modules are examples of such modules. This article describes the methods used for presentation and storage of network topologies, as well as interface to the corresponding Floodlight modules. An alternative algorithm has been suggested and developed for message exchange conveying network topology alterations between the controller and network applications. Proposed algorithm makes implementation of module alerting based on subscription to the relevant events. API for interaction between controller and network applications has been developed. This algorithm and API formed the base for Topology Tracker module capable to inform network applications about the changes that had occurred in the network topology and also stores compact representation of the network to speed up the interaction process.

Modern computer networks and distributed intelligence in accelerator controls

International Nuclear Information System (INIS)

Briegel, C.

1991-01-01

Appropriate hardware and software network protocols are surveyed for accelerator control environments. Accelerator controls network topologies are discussed with respect to the following criteria: vertical versus horizontal and distributed versus centralized. Decision-making considerations are provided for accelerator network architecture specification. Current trends and implementations at Fermilab are discussed

Passivity-based control and estimation in networked robotics

CERN Document Server

Hatanaka, Takeshi; Fujita, Masayuki; Spong, Mark W

2015-01-01

Highlighting the control of networked robotic systems, this book synthesizes a unified passivity-based approach to an emerging cross-disciplinary subject. Thanks to this unified approach, readers can access various state-of-the-art research fields by studying only the background foundations associated with passivity. In addition to the theoretical results and techniques,  the authors provide experimental case studies on testbeds of robotic systems  including networked haptic devices, visual robotic systems,  robotic network systems and visual sensor network systems. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The main body of the book consists of three parts. The first examines how passivity can be utilized for bilateral teleoperation and demonstrates the inherent robustness of the passivity-based controller against communication delays. The second part emphasizes passivity’s usefulness for visual feedback control ...

21 CFR 226.40 - Production and control procedures.

Science.gov (United States)

2010-04-01

...) DRUGS: GENERAL CURRENT GOOD MANUFACTURING PRACTICE FOR TYPE A MEDICATED ARTICLES Product Quality Control... event of any significant discrepancies, key personnel shall prevent distribution of the batch in... control procedures shall include provision for discontinuing distribution of any Type A medicated article...

Thermoelastic steam turbine rotor control based on neural network

Science.gov (United States)

Rzadkowski, Romuald; Dominiczak, Krzysztof; Radulski, Wojciech; Szczepanik, R.

2015-12-01

Considered here are Nonlinear Auto-Regressive neural networks with eXogenous inputs (NARX) as a mathematical model of a steam turbine rotor for controlling steam turbine stress on-line. In order to obtain neural networks that locate critical stress and temperature points in the steam turbine during transient states, an FE rotor model was built. This model was used to train the neural networks on the basis of steam turbine transient operating data. The training included nonlinearity related to steam turbine expansion, heat exchange and rotor material properties during transients. Simultaneous neural networks are algorithms which can be implemented on PLC controllers. This allows for the application neural networks to control steam turbine stress in industrial power plants.

Multi-agent model predictive control for transportation networks : Serial versus parallel schemes

NARCIS (Netherlands)

Negenborn, R.R.; De Schutter, B.; Hellendoorn, J.

2006-01-01

We consider the control of large-scale transportation networks, like road traffic networks, power distribution networks, water distribution networks, etc. Control of these networks is often not possible from a single point by a single intelligent control agent; instead control has to be performed

Covariance upperbound controllers for networked control systems

International Nuclear Information System (INIS)

Ko, Sang Ho

2012-01-01

This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers

Controlling noise-induced behavior of excitable networks

International Nuclear Information System (INIS)

Patidar, S; Pototsky, A; Janson, N B

2009-01-01

The paper demonstrates the possibility to control the collective behavior of a large network of excitable stochastic units, in which oscillations are induced merely by external random input. Each network element is represented by the FitzHugh-Nagumo system under the influence of noise, and the elements are coupled through the mean field. As known previously, the collective behavior of units in such a network can range from synchronous to non-synchronous spiking with a variety of states in between. We apply the Pyragas delayed feedback to the mean field of the network and demonstrate that this technique is capable of suppressing or weakening the collective synchrony, or of inducing the synchrony where it was absent. On the plane of control parameters we indicate the areas where suppression of synchrony is achieved. To explain the numerical observations on a qualitative level, we use the semi-analytic approach based on the cumulant expansion of the distribution density within Gaussian approximation. We perform bifurcation analysis of the obtained cumulant equations with delay and demonstrate that the regions of stability of its steady state have qualitatively the same structure as the regions of synchrony suppression of the original stochastic equations. We also demonstrate the delay-induced multistability in the stochastic network. These results are relevant to the control of unwanted behavior in neural networks.

Decentralized Networked Control of Building Structures

Czech Academy of Sciences Publication Activity Database

Bakule, Lubomír; Rehák, Branislav; Papík, Martin

2016-01-01

Roč. 31, č. 11 (2016), s. 871-886 ISSN 1093-9687 R&D Projects: GA ČR GA13-02149S Institutional support: RVO:67985556 Keywords : decentralized control * networked control * building structures Subject RIV: BC - Control Systems Theory Impact factor: 5.786, year: 2016

A randomized controlled trial testing a social network intervention to promote physical activity among adolescents.

Science.gov (United States)

van Woudenberg, Thabo J; Bevelander, Kirsten E; Burk, William J; Smit, Crystal R; Buijs, Laura; Buijzen, Moniek

2018-04-23

The current study examined the effectiveness of a social network intervention to promote physical activity among adolescents. Social network interventions utilize peer influence to change behavior by identifying the most influential individuals within social networks (i.e., influence agents), and training them to promote the target behavior. A total of 190 adolescents (46.32% boys; M age = 12.17, age range: 11-14 years) were randomly allocated to either the intervention or control condition. In the intervention condition, the most influential adolescents (based on peer nominations of classmates) in each classroom were trained to promote physical activity among their classmates. Participants received a research smartphone to complete questionnaires and an accelerometer to measure physical activity (steps per day) at baseline, and during the intervention one month later. A multilevel model tested the effectiveness of the intervention, controlling for clustering of data within participants and days. No intervention effect was observed, b = .04, SE = .10, p = .66. This was one of the first studies to test whether physical activity in adolescents could be promoted via influence agents, and the first social network intervention to use smartphones to do so. Important lessons and implications are discussed concerning the selection criterion of the influence agents, the use of smartphones in social network intervention, and the rigorous analyses used to control for confounding factors. Dutch Trial Registry (NTR): NTR6173 . Registered 5 October 2016 Study procedures were approved by the Ethics Committee of the Radboud University (ECSW2014-100614-222).

Fair and efficient network congestion control based on minority game

Science.gov (United States)

Wang, Zuxi; Wang, Wen; Hu, Hanping; Deng, Zhaozhang

2011-12-01

Low link utility, RTT unfairness and unfairness of Multi-Bottleneck network are the existing problems in the present network congestion control algorithms at large. Through the analogy of network congestion control with the "El Farol Bar" problem, we establish a congestion control model based on minority game(MG), and then present a novel network congestion control algorithm based on the model. The result of simulations indicates that the proposed algorithm can make the achievements of link utility closing to 100%, zero packet lose rate, and small of queue size. Besides, the RTT unfairness and the unfairness of Multi-Bottleneck network can be solved, to achieve the max-min fairness in Multi-Bottleneck network, while efficiently weaken the "ping-pong" oscillation caused by the overall synchronization.

Identifying Controlling Nodes in Neuronal Networks in Different Scales

Science.gov (United States)

Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen

2012-01-01

Recent studies have detected hubs in neuronal networks using degree, betweenness centrality, motif and synchronization and revealed the importance of hubs in their structural and functional roles. In addition, the analysis of complex networks in different scales are widely used in physics community. This can provide detailed insights into the intrinsic properties of networks. In this study, we focus on the identification of controlling regions in cortical networks of cats’ brain in microscopic, mesoscopic and macroscopic scales, based on single-objective evolutionary computation methods. The problem is investigated by considering two measures of controllability separately. The impact of the number of driver nodes on controllability is revealed and the properties of controlling nodes are shown in a statistical way. Our results show that the statistical properties of the controlling nodes display a concave or convex shape with an increase of the allowed number of controlling nodes, revealing a transition in choosing driver nodes from the areas with a large degree to the areas with a low degree. Interestingly, the community Auditory in cats’ brain, which has sparse connections with other communities, plays an important role in controlling the neuronal networks. PMID:22848475

System Identification, Prediction, Simulation and Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1997-01-01

a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: 1) Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. 2) Amongst numerous training algorithms, only the Recursive Prediction Error Method using...

Controllability of switched singular mix-valued logical control networks with constraints

Science.gov (United States)

Deng, Lei; Gong, Mengmeng; Zhu, Peiyong

2018-03-01

The present paper investigates the controllability problem of switched singular mix-valued logical control networks (SSMLCNs) with constraints on states and controls. First, using the semi-tenser product (STP) of matrices, the SSMLCN is expressed in an algebraic form, based on which a necessary and sufficient condition is given for the uniqueness of solution of SSMLCNs. Second, a necessary and sufficient criteria is derived for the controllability of constrained SSMLCNs, by converting a constrained SSMLCN into a parallel constrained switched mix-valued logical control network. Third, an algorithm is presented to design a proper switching sequence and a control scheme which force a state to a reachable state. Finally, a numerical example is given to demonstrate the efficiency of the results obtained in this paper.

Design and implementation of a new fuzzy PID controller for networked control systems.

Science.gov (United States)

Fadaei, A; Salahshoor, K

2008-10-01

This paper presents a practical network platform to design and implement a networked-based cascade control system linking a Smar Foundation Fieldbus (FF) controller (DFI-302) and a Siemens programmable logic controller (PLC-S7-315-2DP) through Industrial Ethernet to a laboratory pilot plant. In the presented network configuration, the Smar OPC tag browser and Siemens WinCC OPC Channel provide the communicating interface between the two controllers. The paper investigates the performance of a PID controller implemented in two different possible configurations of FF function block (FB) and networked control system (NCS) via a remote Siemens PLC. In the FB control system implementation, the desired set-point is provided by the Siemens Human-Machine Interface (HMI) software (i.e, WinCC) via an Ethernet Modbus link. While, in the NCS implementation, the cascade loop is realized in remote Siemens PLC station and the final element set-point is sent to the Smar FF station via Ethernet bus. A new fuzzy PID control strategy is then proposed to improve the control performances of the networked-based control systems due to an induced transmission delay degradation effect. The proposed strategy utilizes an innovative idea based on sectionalizing the error signal of the step response into three different functional zones. The supporting philosophy behind these three functional zones is to decompose the desired control objectives in terms of rising time, settling time and steady-state error measures maintained by an appropriate PID-type controller in each zone. Then, fuzzy membership factors are defined to configure the control signal on the basis of the fuzzy weighted PID outputs of all three zones. The obtained results illustrate the effectiveness of the proposed fuzzy PID control scheme in improving the performances of the implemented NCS for different transportation delays.

Improvement of Networked Control Systems Performance Using a New Encryption Algorithm

Directory of Open Access Journals (Sweden)

Seyed Ali Mesbahifard

2014-07-01

Full Text Available Networked control systems are control systems which controllers and plants are connected via telecommunication network. One of the most important challenges in networked control systems is the problem of network time delay. Increasing of time delay may affect on control system performance extremely. Other important issue in networked control systems is the security problems. Since it is possible that unknown people access to network especially Internet, the probability of terrible attacks such as deception attacks is greater, therefore presentation of methods which could decrease time delay and increase system immunity are desired. In this paper a symmetric encryption with low data volume against deception attacks is proposed. This method has high security and low time delay rather than the other encryption algorithms and could improve the control system performance against deception attacks.

ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

STAR-TYPE LOCAL AREA NETWORK ACCESS CONTROL

Institute of Scientific and Technical Information of China (English)

逯昭义; 齐藤忠夫

1990-01-01

The multiple access fashion is a new resolution for the star-type local area network (LAN) access control and star-type optical fibre LAN. Arguments about this network are discussed, and the results are introduced.

Data Exchange Network

DEFF Research Database (Denmark)

Grau Larsen, Anton; Ellersgaard, Christoph

2015-01-01

This article presents the extensive Danish elite network. Collected during 2012 and 2013, the data comprises 56,536 positions within 5,079 affiliations, and connects 37,750 individuals. The network consists of the largest Danish corporations, state institutions, NGO’s, and other integrative...... networks such as social clubs or royal events. Data were gathered through an inclusion principle, adding all potentially interesting affiliations. Procedures of name-matching and quality control are presented. Finally, the data are introduced: made available through a package for R, which enables...

SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks

Science.gov (United States)

Lin, Likun

Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network

Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder.

Science.gov (United States)

Dong, Guangheng; Lin, Xiao; Hu, Yanbo; Xie, Chunming; Du, Xiaoxia

2015-03-17

Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD.

H-Infinity Control Design Considering Packet Loss as a Disturbance for Networked Control Systems

OpenAIRE

OGURA, Takashi; KOBAYASHI, Kentaro; OKADA, Hiraku; KATAYAMA, Masaaki

2017-01-01

This paper studies H∞ control for networked control systems with packet loss. In networked control systems, packet loss is one of major weakness because the control performance deteriorates due to packet loss. H∞ control, which is one of robust control, can design a controller to reduce the influence of disturbances acting on the controlled object. This paper proposes an H∞ control design that considers packet loss as a disturbance. Numerical examples show that the proposed H∞ control design ...

Ideomotor feedback control in a recurrent neural network.

Science.gov (United States)

Galtier, Mathieu

2015-06-01

The architecture of a neural network controlling an unknown environment is presented. It is based on a randomly connected recurrent neural network from which both perception and action are simultaneously read and fed back. There are two concurrent learning rules implementing a sort of ideomotor control: (i) perception is learned along the principle that the network should predict reliably its incoming stimuli; (ii) action is learned along the principle that the prediction of the network should match a target time series. The coherent behavior of the neural network in its environment is a consequence of the interaction between the two principles. Numerical simulations show a promising performance of the approach, which can be turned into a local and better "biologically plausible" algorithm.

D0 Central Tracking Solenoid Energization, Controls, Interlocks and Quench Protection Operating Procedures

International Nuclear Information System (INIS)

Hance, R.

1998-01-01

This procedure is used when it is necessary to operate the solenoid energization, controls, interlocks and quench detection system. Note that a separate procedure exists for operating the solenoid 'cryogenic' systems. Only D0 Control Room Operators or the Project Electrical Engineer are qualified to execute these procedures or operate the solenoid system. This procedure assumes that the operator is familiar with using the Distributed Manufacturing Automation and Control Software (DMACS).

Network Communication for Low Level RF Control

International Nuclear Information System (INIS)

Liu Weiqing; Yin Chengke; Zhang Tongxuan; Fu Zechuan; Liu Jianfei

2009-01-01

Low Level RF (LLRF) control system for storage ring of Shanghai Synchrotron Radiation Facility (SSRF) has been built by digital technology. The settings of parameters and the feedback loop status are carried out through the network communication interface, and the local oscillation and clock, which is the important component of the digital LLRF control system, are also configured through network communication. NIOS II processor was employed as a core to build the embedded system with a real-time operating system MicroC/OS-II, finally Lightweight TCP/IP (LwIP) was used to achieve the communication interface. The communication network is stable after a long-term operation. (authors)

Modeling and Speed Control of Induction Motor Drives Using Neural Networks

Directory of Open Access Journals (Sweden)

V. Jamuna

2010-08-01

Full Text Available Speed control of induction motor drives using neural networks is presented. The mathematical model of single phase induction motor is developed. A new simulink model for a neural network-controlled bidirectional chopper fed single phase induction motor is proposed. Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. Comparative study has been made between the conventional and neural network controllers. It is observed that the neural network controlled drive system has better dynamic performance, reduced overshoot and faster transient response than the conventional controlled system.

Control of beam halo-chaos using neural network self-adaptation method

International Nuclear Information System (INIS)

Fang Jinqing; Huang Guoxian; Luo Xiaoshu

2004-11-01

Taking the advantages of neural network control method for nonlinear complex systems, control of beam halo-chaos in the periodic focusing channels (network) of high intensity accelerators is studied by feed-forward back-propagating neural network self-adaptation method. The envelope radius of high-intensity proton beam is reached to the matching beam radius by suitably selecting the control structure of neural network and the linear feedback coefficient, adjusted the right-coefficient of neural network. The beam halo-chaos is obviously suppressed and shaking size is much largely reduced after the neural network self-adaptation control is applied. (authors)

Structure-based control of complex networks with nonlinear dynamics.

Science.gov (United States)

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Self-teaching neural network learns difficult reactor control problem

International Nuclear Information System (INIS)

Jouse, W.C.

1989-01-01

A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits

Evaluation of Voltage Control Approaches for Future Smart Distribution Networks

Directory of Open Access Journals (Sweden)

Pengfei Wang

2017-08-01

Full Text Available This paper evaluates meta-heuristic and deterministic approaches for distribution network voltage control. As part of this evaluation, a novel meta-heuristic algorithm, Cuckoo Search, is applied for distribution network voltage control and compared with a deterministic voltage control algorithm, the oriented discrete coordinate decent method (ODCDM. ODCDM has been adopted in a state-of-the-art industrial product and applied in real distribution networks. These two algorithms have been evaluated under a set of test cases, which were generated to represent the voltage control problems in current and future distribution networks. Sampled test results have been presented, and findings have been discussed regarding the adoption of different optimization algorithms for current and future distribution networks.

Fabrication procedures for HFIR control plates

Energy Technology Data Exchange (ETDEWEB)

Bowden, G.A.; Hicks, G.R.; Knight, R.W.

1984-10-01

The HFIR control system uses Alclad cylindrically shaped components, which have regions containing 31 vol % Eu/sub 2/O/sub 3/ and 38 vol % Ta, respectively. Exacting control of the water passage between these components and adjacent reactor parts is mandatory, and precise dimensional control of the finished products is required. This report describes the procedures developed for manufacturing outer control plates and inner control cylinders. Results are cited which demonstrate that circular-shaped outer control plates can be produced with less than 0.025-in. variation from the specified 9.300-in. radius in any region of the plate. Other results show that, by the exercise of careful control, inner control, inner control plates can be welded into cylindrical geometry with diametrical variations held to less than +- 0.010 in. of the intended 17.846-in. average diam. The cylinders can then be explosively sized, while under compression, with diametric variations of less than 0.005 in. while controlling roundness variations to less than 0.030 in. from the specified 17.842-in. finished diam.

Fabrication procedures for HFIR control plates

International Nuclear Information System (INIS)

Bowden, G.A.; Hicks, G.R.; Knight, R.W.

1984-10-01

The HFIR control system uses Alclad cylindrically shaped components, which have regions containing 31 vol % Eu 2 O 3 and 38 vol % Ta, respectively. Exacting control of the water passage between these components and adjacent reactor parts is mandatory, and precise dimensional control of the finished products is required. This report describes the procedures developed for manufacturing outer control plates and inner control cylinders. Results are cited which demonstrate that circular-shaped outer control plates can be produced with less than 0.025-in. variation from the specified 9.300-in. radius in any region of the plate. Other results show that, by the exercise of careful control, inner control, inner control plates can be welded into cylindrical geometry with diametrical variations held to less than +- 0.010 in. of the intended 17.846-in. average diam. The cylinders can then be explosively sized, while under compression, with diametric variations of less than 0.005 in. while controlling roundness variations to less than 0.030 in. from the specified 17.842-in. finished diam

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

Science.gov (United States)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

Directory of Open Access Journals (Sweden)

Xiaohui Lin

2017-01-01

Full Text Available Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1 no control strategy, (2 boundary control, and (3 boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.

Modelling, Estimation and Control of Networked Complex Systems

CERN Document Server

Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

2009-01-01

The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.

Science.gov (United States)

Wan, Ying; Cao, Jinde; Wen, Guanghui

In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control

Information spread in networks: Games, optimal control, and stabilization

Science.gov (United States)

Khanafer, Ali

This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack

Interacting with Networks : How Does Structure Relate to Controllability in Single-Leader, Consensus Networks?

NARCIS (Netherlands)

Egerstedt, Magnus; Martini, Simone; Cao, Ming; Camlibel, Kanat; Bicchi, Antonio

As networked dynamical systems appear around us at an increasing rate, questions concerning how to manage and control such systems are becoming more important. Examples include multiagent robotics, distributed sensor networks, interconnected manufacturing chains, and data networks. In response to

Development of the Global Measles Laboratory Network.

Science.gov (United States)

Featherstone, David; Brown, David; Sanders, Ray

2003-05-15

The routine reporting of suspected measles cases and laboratory testing of samples from these cases is the backbone of measles surveillance. The Global Measles Laboratory Network (GMLN) has developed standards for laboratory confirmation of measles and provides training resources for staff of network laboratories, reference materials and expertise for the development and quality control of testing procedures, and accurate information for the Measles Mortality Reduction and Regional Elimination Initiative. The GMLN was developed along the lines of the successful Global Polio Laboratory Network, and much of the polio laboratory infrastructure was utilized for measles. The GMLN has developed as countries focus on measles control activities following successful eradication of polio. Currently more than 100 laboratories are part of the global network and follow standardized testing and reporting procedures. A comprehensive laboratory accreditation process will be introduced in 2002 with six quality assurance and performance indicators.

Using a Control System Ethernet Network as a Field Bus

CERN Document Server

De Van, William R; Lawson, Gregory S; Wagner, William H; Wantland, David M; Williams, Ernest

2005-01-01

A major component of a typical accelerator distributed control system (DCS) is a dedicated, large-scale local area communications network (LAN). The SNS EPICS-based control system uses a LAN based on the popular IEEE-802.3 set of standards (Ethernet). Since the control system network infrastructure is available throughout the facility, and since Ethernet-based controllers are readily available, it is tempting to use the control system LAN for "fieldbus" communications to low-level control devices (e.g. vacuum controllers; remote I/O). These devices may or may not be compatible with the high-level DCS protocols. This paper presents some of the benefits and risks of combining high-level DCS communications with low-level "field bus" communications on the same network, and describes measures taken at SNS to promote compatibility between devices connected to the control system network.

Synchronizability on complex networks via pinning control

Indian Academy of Sciences (India)

Keywords. Complex network; the pinning synchronization; synchronizability. ... The findings reveal the relationship between the decreasing speed of maximum eigenvalue sequence of the principal submatrices for coupling matrix and the synchronizability on complex networks via pinning control. We discuss the ...

Resilient distributed control in the presence of misbehaving agents in networked control systems.

Science.gov (United States)

Zeng, Wente; Chow, Mo-Yuen

2014-11-01

In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Directory of Open Access Journals (Sweden)

Li Wang

2013-01-01

Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

Standard formatted data units-control authority procedures

Science.gov (United States)

1991-01-01

The purpose of this document is to establish a set of minimum and optional requirements for the implementation of Control Authority (CA) organizations within and among the Agencies participating in the Consultative Committee for Space Data Systems (CCSDS). By satisfying these requirements, the resultant cooperating set of CA organizations will produce a global CA service supporting information transfer with digital data under the Standard Formatted Data Unit (SFDU) concept. This service is primarily accomplished through the registration, permanent archiving, and dissemination of metadata in the form of Metadata Objects (MDO) that assist in the interpretation of data objects received in SFDU form. This Recommendation addresses the responsibilities, services, and interface protocols for a hierarchy of CA organizations. The top level, consisting of the CCSDS Secretariat and its operational agent, is unique and primarily provides a global coordination function. The lower levels are Agency CA organizations that have primary responsibility for the registration, archiving, and dissemination of MDOs. As experience is gained and technology evolves, the CA Procedures will be extended to include enhanced services and their supporting protocols. In particular, it is anticipated that eventually CA organizations will be linked via networks on a global basis, and will provide requestors with online automated access to CA services. While this Recommendation does not preclude such operations, it also does not recommend the specific protocols to be used to ensure global compatibility of these services. These recommendations will be generated as experience is gained.

Control procedure for well drilling operations

Energy Technology Data Exchange (ETDEWEB)

Bourdon, J C

1988-09-09

A control procedure of rotary drilling operations is proposed. It uses the Drill off test. The drill-off test permits to determine the rock drill speed variation as a function of the wright applied on the top of the pipe. We can deduce from that a rock drill wear parameter. The method permits to prevent a rupture and its grave economic consequences.

Benchmarking Measures of Network Controllability on Canonical Graph Models

Science.gov (United States)

Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

2018-03-01

The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical

A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network

Science.gov (United States)

Lussana, C.; Ranci, M.; Uboldi, F.

2012-04-01

In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.

Design and drafting document control procedures for CPRF/ZTH experiment

International Nuclear Information System (INIS)

Pollat, L.L.; Kewish, R.W.

1989-01-01

This paper will present, in general, the control procedures for design approval, review, changes, and release of engineering documents. It will also discuss interface control for tasks so that possible design interference does not occur. A document control procedure to insure that design criteria are met and technical specifications translate into workable drawings was instituted to support the Confinement Physics Research Facility (CPRF/ZTH) construction program. Our goal, to eliminate any conflicts that might arise between various tasks as the final designs are developed, required tight control and up-to-date design information. Detailed procedure for reviews were instituted, since circumventing the process of design and drafting anywhere might have proven disastrous to the CPRF/ZTH program. Design is a process of translating technical requirements, according to established standards, into drawings that are usable for fabrication and assembly. Both the designer and engineer are responsible for adhering to standards that have been established by the Mechanical Engineering Section for the CPRF/ZTH program. 6 refs., 5 figs

Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

Neural Network-Based Resistance Spot Welding Control and Quality Prediction

Energy Technology Data Exchange (ETDEWEB)

Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.

1999-07-10

This paper describes the development and evaluation of neural network-based systems for industrial resistance spot welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld quality assessment, The second describes the development and evaluation of a static neural network-based weld quality assessment system that relied on experimental design to limit the influence of environmental variability. Relevant data analysis methods are also discussed. The weld classifier resulting from the analysis successfldly balances predictive power and simplicity of interpretation. The results presented for both systems demonstrate clearly that neural networks can be employed to address two significant problems common to the resistance spot welding industry, control of the process itself, and non-destructive determination of resulting weld quality.

Neural-Network Control Of Prosthetic And Robotic Hands

Science.gov (United States)

Buckley, Theresa M.

1991-01-01

Electronic neural networks proposed for use in controlling robotic and prosthetic hands and exoskeletal or glovelike electromechanical devices aiding intact but nonfunctional hands. Specific to patient, who activates grasping motion by voice command, by mechanical switch, or by myoelectric impulse. Patient retains higher-level control, while lower-level control provided by neural network analogous to that of miniature brain. During training, patient teaches miniature brain to perform specialized, anthropomorphic movements unique to himself or herself.

Optimal Control of Interdependent Epidemics in Complex Networks

OpenAIRE

Chen, Juntao; Zhang, Rui; Zhu, Quanyan

2017-01-01

Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

Science.gov (United States)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Modeling of the height control system using artificial neural networks

Directory of Open Access Journals (Sweden)

A. R Tahavvor

2016-09-01

Full Text Available Introduction Automation of agricultural and machinery construction has generally been enhanced by intelligent control systems due to utility and efficiency rising, ease of use, profitability and upgrading according to market demand. A broad variety of industrial merchandise are now supplied with computerized control systems of earth moving processes to be performed by construction and agriculture field vehicle such as grader, backhoe, tractor and scraper machines. A height control machine which is used in measuring base thickness is consisted of two mechanical and electronic parts. The mechanical part is consisted of conveyor belt, main body, electrical engine and invertors while the electronic part is consisted of ultrasonic, wave transmitter and receiver sensor, electronic board, control set, and microcontroller. The main job of these controlling devices consists of the topographic surveying, cutting and filling of elevated and spotted low area, and these actions fundamentally dependent onthe machine's ability in elevation and thickness measurement and control. In this study, machine was first tested and then some experiments were conducted for data collection. Study of system modeling in artificial neural networks (ANN was done for measuring, controlling the height for bases by input variable input vectors such as sampling time, probe speed, conveyer speed, sound wave speed and speed sensor are finally the maximum and minimum probe output vector on various conditions. The result reveals the capability of this procedure for experimental recognition of sensors' behavior and improvement of field machine control systems. Inspection, calibration and response, diagnosis of the elevation control system in combination with machine function can also be evaluated by some extra development of this system. Materials and Methods Designing and manufacture of the planned apparatus classified in three dissimilar, mechanical and electronic module, courses of

Chaotification of complex networks with impulsive control.

Science.gov (United States)

Guan, Zhi-Hong; Liu, Feng; Li, Juan; Wang, Yan-Wu

2012-06-01

This paper investigates the chaotification problem of complex dynamical networks (CDN) with impulsive control. Both the discrete and continuous cases are studied. The method is presented to drive all states of every node in CDN to chaos. The proposed impulsive control strategy is effective for both the originally stable and unstable CDN. The upper bound of the impulse intervals for originally stable networks is derived. Finally, the effectiveness of the theoretical results is verified by numerical examples.

Research of user access control for networked manufacturing system

Institute of Scientific and Technical Information of China (English)

ZHENG Xiao-lin; LEI Yu; CHEN De-ren

2006-01-01

An integrated user access control method was proposed to address the issues of security and management in networked manufacturing systems (NMS).Based on the analysis of the security issues in networked manufacturing system,an integrated user access control method composed of role-based access control (RBAC),task-based access control (TBAC),relationship-driven access control (RDAC)and coalition-based access control (CBAC) was proposed,including the hierarchical user relationship model,the reference model and the process model.The elements and their relationships were defined,and the expressions of constraints authorization were given.The extensible access control markup language (XACML) was used to implement this method.This method was used in the networked manufacturing system in the Shaoxing spinning region of China.The results show that the integrated user access control method can reduce the costs of system security maintenance and management.

Prediction based chaos control via a new neural network

International Nuclear Information System (INIS)

Shen Liqun; Wang Mao; Liu Wanyu; Sun Guanghui

2008-01-01

In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network

Gain control network conditions in early sensory coding.

Directory of Open Access Journals (Sweden)

Eduardo Serrano

Full Text Available Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

Optimal traffic control in highway transportation networks using linear programming

KAUST Repository

Li, Yanning

2014-06-01

This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.

Synchronization Control for a Class of Discrete-Time Dynamical Networks With Packet Dropouts: A Coding-Decoding-Based Approach.

Science.gov (United States)

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2017-09-06

The synchronization control problem is investigated for a class of discrete-time dynamical networks with packet dropouts via a coding-decoding-based approach. The data is transmitted through digital communication channels and only the sequence of finite coded signals is sent to the controller. A series of mutually independent Bernoulli distributed random variables is utilized to model the packet dropout phenomenon occurring in the transmissions of coded signals. The purpose of the addressed synchronization control problem is to design a suitable coding-decoding procedure for each node, based on which an efficient decoder-based control protocol is developed to guarantee that the closed-loop network achieves the desired synchronization performance. By applying a modified uniform quantization approach and the Kronecker product technique, criteria for ensuring the detectability of the dynamical network are established by means of the size of the coding alphabet, the coding period and the probability information of packet dropouts. Subsequently, by resorting to the input-to-state stability theory, the desired controller parameter is obtained in terms of the solutions to a certain set of inequality constraints which can be solved effectively via available software packages. Finally, two simulation examples are provided to demonstrate the effectiveness of the obtained results.

Enhancements to inventory control procedures used at Koeberg nuclear power station

International Nuclear Information System (INIS)

Barker, M.P.; Adams, A.R.

1991-01-01

In industry today, industrial engineers are forced to seek new and innovative ideas to reduce costs. This can often be accomplished by simplified or modernized operational procedures. With the advancement in computer technology, operational procedures can be enhanced. Despite the fact that Eskom's Koeberg nuclear power station is one of a kind in Africa, it, like most other industries requires a large stock holding capacity. There are currently 25 000 stock items in the Koeberg Stores Information System. Controlling all of these items is no minor task and management is continually trying to optimise the inventory control procedures. One of these procedures is described. 3 refs., 1 fig

Energy management and multi-layer control of networked microgrids

Science.gov (United States)

Zamora, Ramon

Networked microgrids is a group of neighboring microgrids that has ability to interchange power when required in order to increase reliability and resiliency. Networked microgrid can operate in different possible configurations including: islanded microgrid, a grid-connected microgrid without a tie-line converter, a grid-connected microgrid with a tie-line converter, and networked microgrids. These possible configurations and specific characteristics of renewable energy offer challenges in designing control and management algorithms for voltage, frequency and power in all possible operating scenarios. In this work, control algorithm is designed based on large-signal model that enables microgrid to operate in wide range of operating points. A combination between PI controller and feed-forward measured system responses will compensate for the changes in operating points. The control architecture developed in this work has multi-layers and the outer layer is slower than the inner layer in time response. The main responsibility of the designed controls are to regulate voltage magnitude and frequency, as well as output power of the DG(s). These local controls also integrate with a microgrid level energy management system or microgrid central controller (MGCC) for power and energy balance for. the entire microgrid in islanded, grid-connected, or networked microgid mode. The MGCC is responsible to coordinate the lower level controls to have reliable and resilient operation. In case of communication network failure, the decentralized energy management will operate locally and will activate droop control. Simulation results indicate the superiority of designed control algorithms compared to existing ones.

Motion control of servo cylinder using neural network

International Nuclear Information System (INIS)

Hwang, Un Kyoo; Cho, Seung Ho

2004-01-01

In this paper, a neural network controller that can be implemented in parallel with a PD controller is suggested for motion control of a hydraulic servo cylinder. By applying a self-excited oscillation method, the system design parameters of open loop transfer function of servo cylinder system are identified. Based on system design parameters, the PD gains are determined for the desired closed loop characteristics. The neural network is incorporated with PD control in order to compensate the inherent nonlinearities of hydraulic servo system. As an application example, a motion control using PD-NN has been performed and proved its superior performance by comparing with that of a PD control

Applying Trusted Network Technology To Process Control Systems

Science.gov (United States)

Okhravi, Hamed; Nicol, David

Interconnections between process control networks and enterprise networks expose instrumentation and control systems and the critical infrastructure components they operate to a variety of cyber attacks. Several architectural standards and security best practices have been proposed for industrial control systems. However, they are based on older architectures and do not leverage the latest hardware and software technologies. This paper describes new technologies that can be applied to the design of next generation security architectures for industrial control systems. The technologies are discussed along with their security benefits and design trade-offs.

Energy Effective Congestion Control for Multicast with Network Coding in Wireless Ad Hoc Network

Directory of Open Access Journals (Sweden)

Chuanxin Zhao

2014-01-01

Full Text Available In order to improve network throughput and reduce energy consumption, we propose in this paper a cross-layer optimization design that is able to achieve multicast utility maximization and energy consumption minimization. The joint optimization of congestion control and power allocation is formulated to be a nonlinear nonconvex problem. Using dual decomposition, a distributed optimization algorithm is proposed to avoid the congestion by control flow rate at the source node and eliminate the bottleneck by allocating the power at the intermediate node. Simulation results show that the cross-layer algorithm can increase network performance, reduce the energy consumption of wireless nodes and prolong the network lifetime, while keeping network throughput basically unchanged.

17 CFR 240.15d-15 - Controls and procedures.

Science.gov (United States)

2010-04-01

... Investment Company Act of 1940 (15 U.S.C. 80a-4(2)), must maintain disclosure controls and procedures (as... year or had filed an annual report with the Commission for the prior fiscal year, internal control over... the issuer's internal control over financial reporting. The framework on which management's evaluation...

Neural network application to aircraft control system design

Science.gov (United States)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

Neural network application to aircraft control system design

Science.gov (United States)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

Practical Application of Neural Networks in State Space Control

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon

the networks, although some modifications are needed for the method to apply to the multilayer perceptron network. In connection with the multilayer perceptron networks it is also pointed out how instantaneous, sample-by-sample linearized state space models can be extracted from a trained network, thus opening......In the present thesis we address some problems in discrete-time state space control of nonlinear dynamical systems and attempt to solve them using generic nonlinear models based on artificial neural networks. The main aim of the work is to examine how well such control algorithms perform when...... theoretic notions followed by a detailed description of the topology, neuron functions and learning rules of the two types of neural networks treated in the thesis, the multilayer perceptron and the neurofuzzy networks. In both cases, a Least Squares second-order gradient method is used to train...

Topology control with IPD network creation games

International Nuclear Information System (INIS)

Scholz, Jan C; Greiner, Martin O W

2007-01-01

Network creation games couple a two-players game with the evolution of network structure. A vertex player may increase its own payoff with a change of strategy or with a modification of its edge-defined neighbourhood. By referring to the iterated prisoners dilemma (IPD) game we show that this evolutionary dynamics converges to network-Nash equilibria, where no vertex is able to improve its payoff. The resulting network structure exhibits a strong dependence on the parameter of the payoff matrix. Degree distributions and cluster coefficients are also strongly affected by the specific interactions chosen for the neighbourhood exploration. This allows network creation games to be seen as a promising artificial-social-systems approach for a distributive topology control of complex networked systems

17 CFR 270.30a-3 - Controls and procedures.

Science.gov (United States)

2010-04-01

... and procedures, within the 90-day period prior to the filing date of each report on Form N-CSR (§§ 249... to be disclosed by the investment company on Form N-CSR (§§ 249.331 and 274.128 of this chapter) and... include, without limitation, controls and procedures designed to ensure that information required to be...

Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

Directory of Open Access Journals (Sweden)

Zhicong Zhang

2018-01-01

Full Text Available We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

Directory of Open Access Journals (Sweden)

Yuanjiang Huang

2014-01-01

Full Text Available The sensor nodes in the Wireless Sensor Networks (WSNs are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC, of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC, of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.

Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

Directory of Open Access Journals (Sweden)

Jose P. Perez

2014-01-01

Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

Robust receding horizon control for networked and distributed nonlinear systems

CERN Document Server

Li, Huiping

2017-01-01

This book offers a comprehensive, easy-to-understand overview of receding-horizon control for nonlinear networks. It presents novel general strategies that can simultaneously handle general nonlinear dynamics, system constraints, and disturbances arising in networked and large-scale systems and which can be widely applied. These receding-horizon-control-based strategies can achieve sub-optimal control performance while ensuring closed-loop stability: a feature attractive to engineers. The authors address the problems of networked and distributed control step-by-step, gradually increasing the level of challenge presented. The book first introduces the state-feedback control problems of nonlinear networked systems and then studies output feedback control problems. For large-scale nonlinear systems, disturbance is considered first, then communication delay separately, and lastly the simultaneous combination of delays and disturbances. Each chapter of this easy-to-follow book not only proposes and analyzes novel ...

Pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions

International Nuclear Information System (INIS)

Yan-Li, Zou; Guan-Rong, Chen

2009-01-01

This paper studies pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions. To study a state-feedback pinning-controlled network with N nodes, it first converts the controlled network to an extended network of N+1 nodes without controls. It is shown that the controlled synchronizability of the given network is determined by the real part of the smallest nonzero eigenvalue of the coupling matrix of its extended network when the synchronized region is unbounded; but it is determined by the ratio of the real parts of the largest and the smallest nonzero eigenvalues of the coupling matrix when the synchronized region is bounded. Both theoretical analysis and numerical simulation show that the portion of controlled nodes has no critical values when the synchronized region is unbounded, but it has a critical value when the synchronized region is bounded. In the former case, therefore, it is possible to control the network to achieve synchronization by pinning only one node. In the latter case, the network can achieve controlled synchronization only when the portion of controlled nodes is larger than the critical value. (general)

Towards Controlling Latency in Wireless Networks

KAUST Repository

Bouacida, Nader

2017-04-24

Wireless networks are undergoing an unprecedented revolution in the last decade. With the explosion of delay-sensitive applications in the Internet (i.e., online gaming and VoIP), latency becomes a major issue for the development of wireless technology. Taking advantage of the significant decline in memory prices, industrialists equip the network devices with larger buffering capacities to improve the network throughput by limiting packets drops. Over-buffering results in increasing the time that packets spend in the queues and, thus, introducing more latency in networks. This phenomenon is known as “bufferbloat”. While throughput is the dominant performance metric, latency also has a huge impact on user experience not only for real-time applications but also for common applications like web browsing, which is sensitive to latencies in order of hundreds of milliseconds. Concerns have arisen about designing sophisticated queue management schemes to mitigate the effects of such phenomenon. My thesis research aims to solve bufferbloat problem in both traditional half-duplex and cutting-edge full-duplex wireless systems by reducing delay while maximizing wireless links utilization and fairness. Our work shed lights on buffer management algorithms behavior in wireless networks and their ability to reduce latency resulting from excessive queuing delays inside oversized static network buffers without a significant loss in other network metrics. First of all, we address the problem of buffer management in wireless full-duplex networks by using Wireless Queue Management (WQM), which is an active queue management technique for wireless networks. Our solution is based on Relay Full-Duplex MAC (RFD-MAC), an asynchronous media access control protocol designed for relay full-duplexing. Compared to the default case, our solution reduces the end-to-end delay by two orders of magnitude while achieving similar throughput in most of the cases. In the second part of this thesis

Control of coupled oscillator networks with application to microgrid technologies

Science.gov (United States)

Arenas, Alex

The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable syn- chronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

Control of coupled oscillator networks with application to microgrid technologies.

Science.gov (United States)

Skardal, Per Sebastian; Arenas, Alex

2015-08-01

The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

Adaptive neural network backstepping control for a class of uncertain fractional-order chaotic systems with unknown backlash-like hysteresis

Energy Technology Data Exchange (ETDEWEB)

Wu, Yimin [School of Mathematics and Statistics, Suzhou University, Suzhou 234000 (China); Lv, Hui, E-mail: lvhui207@gmail.com [Department of Applied Mathematics, Huainan Normal University, Huainan 232038 (China)

2016-08-15

In this paper, we consider the control problem of a class of uncertain fractional-order chaotic systems preceded by unknown backlash-like hysteresis nonlinearities based on backstepping control algorithm. We model the hysteresis by using a differential equation. Based on the fractional Lyapunov stability criterion and the backstepping algorithm procedures, an adaptive neural network controller is driven. No knowledge of the upper bound of the disturbance and system uncertainty is required in our controller, and the asymptotical convergence of the tracking error can be guaranteed. Finally, we give two simulation examples to confirm our theoretical results.

National Ignition Facility (NIF) Control Network Design and Analysis

International Nuclear Information System (INIS)

Bryant, R M; Carey, R W; Claybourn, R V; Pavel, G; Schaefer, W J

2001-01-01

The control network for the National Ignition Facility (NIF) is designed to meet the needs for common object request broker architecture (CORBA) inter-process communication, multicast video transport, device triggering, and general TCP/IP communication within the NIF facility. The network will interconnect approximately 650 systems, including the embedded controllers, front-end processors (FEPs), supervisory systems, and centralized servers involved in operation of the NIF. All systems are networked with Ethernet to serve the majority of communication needs, and asynchronous transfer mode (ATM) is used to transport multicast video and synchronization triggers. CORBA software infra-structure provides location-independent communication services over TCP/IP between the application processes in the 15 supervisory and 300 FEP systems. Video images sampled from 500 video cameras at a 10-Hz frame rate will be multicast using direct ATM Application Programming Interface (API) communication from video FEPs to any selected operator console. The Ethernet and ATM control networks are used to broadcast two types of device triggers for last-second functions in a large number of FEPs, thus eliminating the need for a separate infrastructure for these functions. Analysis, design, modeling, and testing of the NIF network has been performed to provide confidence that the network design will meet NIF control requirements

Mathematical inference and control of molecular networks from perturbation experiments

Science.gov (United States)

Mohammed-Rasheed, Mohammed

in order to affect the time evolution of molecular activity in a desirable manner. In this proposal, we address both the inference and control problems of GRNs. In the first part of the thesis, we consider the control problem. We assume that we are given a general topology network structure, whose dynamics follow a discrete-time Markov chain model. We subsequently develop a comprehensive framework for optimal perturbation control of the network. The aim of the perturbation is to drive the network away from undesirable steady-states and to force it to converge to a unique desirable steady-state. The proposed framework does not make any assumptions about the topology of the initial network (e.g., ergodicity, weak and strong connectivity), and is thus applicable to general topology networks. We define the optimal perturbation as the minimum-energy perturbation measured in terms of the Frobenius norm between the initial and perturbed networks. We subsequently demonstrate that there exists at most one optimal perturbation that forces the network into the desirable steady-state. In the event where the optimal perturbation does not exist, we construct a family of sub-optimal perturbations that approximate the optimal solution arbitrarily closely. In the second part of the thesis, we address the inference problem of GRNs from time series data. We model the dynamics of the molecules using a system of ordinary differential equations corrupted by additive white noise. For large-scale networks, we formulate the inference problem as a constrained maximum likelihood estimation problem. We derive the molecular interactions that maximize the likelihood function while constraining the network to be sparse. We further propose a procedure to recover weak interactions based on the Bayesian information criterion. For small-size networks, we investigated the inference of a globally stable 7-gene melanoma genetic regulatory network from genetic perturbation experiments. We considered five

Stability and synchronization control of stochastic neural networks

CERN Document Server

Zhou, Wuneng; Zhou, Liuwei; Tong, Dongbing

2016-01-01

This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.

A network society communicative model for optimizing the Refugee Status Determination (RSD procedures

Directory of Open Access Journals (Sweden)

Andrea Pacheco Pacífico

2013-01-01

Full Text Available This article recommends a new way to improve Refugee Status Determination (RSD procedures by proposing a network society communicative model based on active involvement and dialogue among all implementing partners. This model, named after proposals from Castells, Habermas, Apel, Chimni, and Betts, would be mediated by the United Nations High Commissioner for Refugees (UNHCR, whose role would be modeled after that of the International Committee of the Red Cross (ICRC practice.

Improving the development, use and control of maintenance procedures

International Nuclear Information System (INIS)

Morgenstern, M.H.; Barnes, V.E.; Radford, L.R.; Wheeler, W.A.; Badalamente, R.V.

1985-12-01

This paper describes the results of a project conducted for the US Nuclear Regulatory Commission (NRC) to assess and document the need for guidance or regulatory involvement by the NRC in the development, upgrading, use and control of maintenance procedures in US nuclear power plants. Presented are the findings of the following activities: (1) a survey of current maintenance procedure practices in seven US nuclear power plants; (2) a review and analysis of plant administrative and maintenance procedures; (3) a survey of maintenance procedure practices in industries that share some characteristics with the nuclear industry; and (4) a review of the research pertaining to job performance aids and a brief analysis of their applicability to maintenance in nuclear power plants. Based on these findings, several recommendations to upgrade maintenance procedures are offered

Two Procedures for Relaxation as Self-Control in the Treatment of Communication Apprehension

Science.gov (United States)

Deffenbacher, Jerry L.; Payne, Dennis M.

1977-01-01

An in vivo procedure for relaxation as self-control and a procedure for self-control modification of desensitization were compared to a no-treatment control. Results showed modified desensitization, compared to the control, significantly decreased communication anxiety and fear of negative evaluation and significantly increased assertiveness.…

Mitigating the controller performance bottlenecks in Software Defined Networks

DEFF Research Database (Denmark)

Caba, Cosmin Marius; Soler, José

2016-01-01

The centralization of the control plane decision logic in Software Defined Networking (SDN) has raised concerns regarding the performance of the SDN Controller (SDNC) when the network scales up. A number of solutions have been proposed in the literature to address these concerns. This paper...

Epigenetics and Why Biological Networks are More Controllable than Expected

Science.gov (United States)

Motter, Adilson

2013-03-01

A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behavior or fail. In this talk, I will show that it is possible to exploit this same principle to control network behavior. This approach takes advantage of the nonlinear dynamics inherent to real networks, and allows bringing the system to a desired target state even when this state is not directly accessible or the linear counterpart is not controllable. Applications show that this framework permits both reprogramming a network to a desired task as well as rescuing networks from the brink of failure, which I will illustrate through various biological problems. I will also briefly review the progress our group has made over the past 5 years on related control of complex networks in non-biological domains.

Slave nodes and the controllability of metabolic networks

International Nuclear Information System (INIS)

Kim, Dong-Hee; Motter, Adilson E

2009-01-01

Recent work on synthetic rescues has shown that the targeted deletion of specific metabolic genes can often be used to rescue otherwise non-viable mutants. This raises a fundamental biophysical question: to what extent can the whole-cell behavior of a large metabolic network be controlled by constraining the flux of one or more reactions in the network? This touches upon the issue of the number of degrees of freedom contained by one such network. Using the metabolic network of Escherichia coli as a model system, here we address this question theoretically by exploring not only reaction deletions, but also a continuum of all possible reaction expression levels. We show that the behavior of the metabolic network can be largely manipulated by the pinned expression of a single reaction. In particular, a relevant fraction of the metabolic reactions exhibits canalizing interactions, in that the specification of one reaction flux determines cellular growth as well as the fluxes of most other reactions in optimal steady states. The activity of individual reactions can thus be used as surrogates to monitor and possibly control cellular growth and other whole-cell behaviors. In addition to its implications for the study of control processes, our methodology provides a new approach to study how the integrated dynamics of the entire metabolic network emerges from the coordinated behavior of its component parts.

Time Course of Brain Network Reconfiguration Supporting Inhibitory Control.

Science.gov (United States)

Popov, Tzvetan; Westner, Britta U; Silton, Rebecca L; Sass, Sarah M; Spielberg, Jeffrey M; Rockstroh, Brigitte; Heller, Wendy; Miller, Gregory A

2018-05-02

Hemodynamic research has recently clarified key nodes and links in brain networks implementing inhibitory control. Although fMRI methods are optimized for identifying the structure of brain networks, the relatively slow temporal course of fMRI limits the ability to characterize network operation. The latter is crucial for developing a mechanistic understanding of how brain networks shift dynamically to support inhibitory control. To address this critical gap, we applied spectrally resolved Granger causality (GC) and random forest machine learning tools to human EEG data in two large samples of adults (test sample n = 96, replication sample n = 237, total N = 333, both sexes) who performed a color-word Stroop task. Time-frequency analysis confirmed that recruitment of inhibitory control accompanied by slower behavioral responses was related to changes in theta and alpha/beta power. GC analyses revealed directionally asymmetric exchanges within frontal and between frontal and parietal brain areas: top-down influence of superior frontal gyrus (SFG) over both dorsal ACC (dACC) and inferior frontal gyrus (IFG), dACC control over middle frontal gyrus (MFG), and frontal-parietal exchanges (IFG, precuneus, MFG). Predictive analytics confirmed a combination of behavioral and brain-derived variables as the best set of predictors of inhibitory control demands, with SFG theta bearing higher classification importance than dACC theta and posterior beta tracking the onset of behavioral response. The present results provide mechanistic insight into the biological implementation of a psychological phenomenon: inhibitory control is implemented by dynamic routing processes during which the target response is upregulated via theta-mediated effective connectivity within key PFC nodes and via beta-mediated motor preparation. SIGNIFICANCE STATEMENT Hemodynamic neuroimaging research has recently clarified regional structures in brain networks supporting inhibitory control. However, due to

Chaos Control and Synchronization of Cellular Neural Network with Delays Based on OPNCL Control

International Nuclear Information System (INIS)

Qian, Tang; Xing-Yuan, Wang

2010-01-01

The problem of chaos control and complete synchronization of cellular neural network with delays is studied. Based on the open plus nonlinear closed loop (OPNCL) method, the control scheme and synchronization scheme are designed. Both the schemes can achieve the chaos control and complete synchronization of chaotic neural network respectively, and their validity is further verified by numerical simulation experiments. (general)

Implementing controlled-unitary operations over the butterfly network

Energy Technology Data Exchange (ETDEWEB)

Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S. [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo (Japan); Murao, Mio [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan and NanoQuine, The University of Tokyo, Tokyo (Japan)

2014-12-04

We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

Double-Frame Current Control with a Multivariable PI Controller and Power Compensation for Weak Unbalanced Networks

CERN Document Server

Siemaszko, Daniel

2015-06-15

The handling of weak networks with asymmetric loads and disturbances im- plies the accurate handling of the second-harmonic component that appears in an unbalanced network. This paper proposes a classic vector control approach using a PI-based controller with superior decoupling capabilities for operation in weak networks with unbalanced phase voltages. A synchronization method for weak unbalanced networks is detailed, with dedicated dimensioning rules. The use of a double-frame controller allows a current symmetry or controlled imbalance to be forced for compensation of power oscillations by controlling the negative current sequence. This paper also serves as a useful reminder of the proper way to cancel the inherent coupling effect due to the transformation to the synchronous rotating reference frame, and of basic considerations of the relationship between switching frequency and control bandwidth.

Neural Network Predictive Control for Vanadium Redox Flow Battery

Directory of Open Access Journals (Sweden)

Hai-Feng Shen

2013-01-01

Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

Hierarchical-control-based output synchronization of coexisting attractor networks

International Nuclear Information System (INIS)

Yun-Zhong, Song; Yi-Fa, Tang

2010-01-01

This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

Self-generation of controller of an underwater robot with neural network

International Nuclear Information System (INIS)

Suto, T.; Ura, T.

1994-01-01

A self-organizing controller system is constructed based on artificial neural networks and applied to constant altitude swimming of the autonomous underwater robot PTEROA 150. The system consists of a controller and a forward model which calculates the values for evaluation as a result of control. Some methods are introduced for quick and appropriate adjustment of the controller network. Modification of the controller network is executed based on error-back-propagation method utilizing the forward model network. The forward model is divided into three sub-networks which represent dynamics of the vehicle, estimation of relative position to the seabed and calculation of the altitude. The proposed adaptive system is demonstrated in computer simulations where objective of a vehicle is keeping a constant altitude from seabed which is constituted of triangular ridges

Implementation of a fuzzy logic/neural network multivariable controller

International Nuclear Information System (INIS)

Cordes, G.A.; Clark, D.E.; Johnson, J.A.; Smartt, H.B.; Wickham, K.L.; Larson, T.K.

1992-01-01

This paper describes a multivariable controller developed at the Idaho National Engineering Laboratory (INEL) that incorporates both fuzzy logic rules and a neural network. The controller was implemented in a laboratory demonstration and was robust, producing smooth temperature and water level response curves with short time constants. In the future, intelligent control systems will be a necessity for optimal operation of autonomous reactor systems located on earth or in space. Even today, there is a need for control systems that adapt to the changing environment and process. Hybrid intelligent control systems promise to provide this adaptive capability. Fuzzy logic implements our imprecise, qualitative human reasoning. The values of system variables (controller inputs) and control variables (controller outputs) are described in linguistic terms and subdivided into fully overlapping value ranges. The fuzzy rule base describes how combinations of input parameter ranges determine the output control values. Neural networks implement our human learning. In this controller, neural networks were embedded in the software to explore their potential for adding adaptability

Structure, function, and control of the human musculoskeletal network.

Directory of Open Access Journals (Sweden)

Andrew C Murphy

2018-01-01

Full Text Available The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We constructed a highly simplified whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrated that, using this simplified model, a muscle's role in this network could offer a theoretical prediction of the susceptibility of surrounding components to secondary injury. Finally, we illustrated that sets of muscles cluster into network communities that mimic the organization of control modules in primary motor cortex. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments.

Adaptive Neural Network Sliding Mode Control for Quad Tilt Rotor Aircraft

Directory of Open Access Journals (Sweden)

Yanchao Yin

2017-01-01

Full Text Available A novel neural network sliding mode control based on multicommunity bidirectional drive collaborative search algorithm (M-CBDCS is proposed to design a flight controller for performing the attitude tracking control of a quad tilt rotors aircraft (QTRA. Firstly, the attitude dynamic model of the QTRA concerning propeller tension, channel arm, and moment of inertia is formulated, and the equivalent sliding mode control law is stated. Secondly, an adaptive control algorithm is presented to eliminate the approximation error, where a radial basis function (RBF neural network is used to online regulate the equivalent sliding mode control law, and the novel M-CBDCS algorithm is developed to uniformly update the unknown neural network weights and essential model parameters adaptively. The nonlinear approximation error is obtained and serves as a novel leakage term in the adaptations to guarantee the sliding surface convergence and eliminate the chattering phenomenon, which benefit the overall attitude control performance for QTRA. Finally, the appropriate comparisons among the novel adaptive neural network sliding mode control, the classical neural network sliding mode control, and the dynamic inverse PID control are examined, and comparative simulations are included to verify the efficacy of the proposed control method.

Implementing self sustained quality control procedures in a clinical laboratory.

Science.gov (United States)

Khatri, Roshan; K C, Sanjay; Shrestha, Prabodh; Sinha, J N

2013-01-01

Quality control is an essential component in every clinical laboratory which maintains the excellence of laboratory standards, supplementing to proper disease diagnosis, patient care and resulting in overall strengthening of health care system. Numerous quality control schemes are available, with combinations of procedures, most of which are tedious, time consuming and can be "too technical" whereas commercially available quality control materials can be expensive especially for laboratories in developing nations like Nepal. Here, we present a procedure performed at our centre with self prepared control serum and use of simple statistical tools for quality assurance. The pooled serum was prepared as per guidelines for preparation of stabilized liquid quality control serum from human sera. Internal Quality Assessment was performed on this sample, on a daily basis which included measurement of 12 routine biochemical parameters. The results were plotted on Levey-Jennings charts and analysed with quality control rules, for a period of one month. The mean levels of biochemical analytes in self prepared control serum were within normal physiological range. This serum was evaluated every day along with patients' samples. The results obtained were plotted on control charts and analysed using common quality control rules to identify possible systematic and random errors. Immediate mitigation measures were taken and the dispatch of erroneous reports was avoided. In this study we try to highlight on a simple internal quality control procedure which can be performed by laboratories, with minimum technology, expenditure, and expertise and improve reliability and validity of the test reports.

Virtualized Network Control. Final Report

Energy Technology Data Exchange (ETDEWEB)

Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States)

2013-02-01

This document is the final report for the Virtualized Network Control (VNC) project, which was funded by the United States Department of Energy (DOE) Office of Science. This project was also informally referred to as Advanced Resource Computation for Hybrid Service and TOpology NEtworks (ARCHSTONE). This report provides a summary of the project's activities, tasks, deliverable, and accomplishments. It also provides a summary of the documents, software, and presentations generated as part of this projects activities. Namely, the Appendix contains an archive of the deliverables, documents, and presentations generated a part of this project.

[Exploration of the design of media access control layer of wireless body area network for medical healthcare].

Science.gov (United States)

Liu, Xuemei; Ge, Baofeng

2012-04-01

This paper proposes a media access control (MAC) layer design for wireless body area network (WBAN) systems. WBAN is a technology that targets for wireless networking of wearable and implantable body sensors which monitor vital body signs, such as heart-rate, body temperature, blood pressure, etc. It has been receiving attentions from international organizations, e. g. the Institute of Electrical and Electronics Engineers (IEEE), due to its capability of providing efficient healthcare services and clinical management. This paper reviews the standardization procedure of WBAN and summarizes the challenge of the MAC layer design. It also discusses the methods of improving power consumption performance, which is one of the major issues of WBAN systems.

Adaptive control of call acceptance in WCDMA network

Directory of Open Access Journals (Sweden)

Milan Manojle Šunjevarić

2013-10-01

Full Text Available In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probability of blocking.. Introduction We are witnessing a steady increase in the number of demands placed upon modern wireless networks. New applications and an increasing number of users as well as user activities growth in recent years reinforce the need for an efficient use of the spectrum and its proper distribution among different applications and classes of services. Besides humans, the last few years saw different computers, machines, applications, and, in the future, many other devices, RFID applications, and finally networked objects, as a new kind of wireless networks "users". Because of the exceptional rise in the number of users, the demands placed upon modern wireless networks are becoming larger, and spectrum management plays an important role. For these reasons, choosing an appropriate call admission control algorithm is of great importance. Multiple access and resource management in wireless networks Radio resource management of mobile networks is a set of algorithms to manage the use of radio resources with the aim is to maximize the total capacity of wireless systems with equal distribution of resources to users. Management of radio resources in cellular networks is usually located in the base station controller, the base station and the mobile terminal, and is based on decisions made on appropriate measurement and feedback. It is often defined as the maximum volume of traffic load that the system can provide for some of the requirements for the

Simulation of time-control procedures for terminal area flow management

Science.gov (United States)

Alcabin, M.; Erzberger, H.; Tobias, L.; Obrien, P. J.

1985-01-01

Simulations of a terminal area traffic-management system incorporating automated scheduling and time-control (four-dimensional) techniques conducted at NASA Ames Research Center jointly with the Federal Aviation Administration, have shown that efficient procedures can be developed for handling a mix of 4D-equipped and conventionally equipped aircraft. A crucial role in this system is played by an ATC host computer algorithm, referred to as a speed advisory, that allows controllers to maintain accurate time schedules of the conventionally equipped aircraft in the traffic mix. Results are of the most recent simulations in which two important special cases were investigated. First, the effects of a speed advisory on touchdown time scheduling are examined, when unequipped aircraft are constrained to follow fuel-optimized profiles in the near-terminal area, and rescheduling procedures are developed to handle missed approaches of 4D-equipped aircraft. Various performance measures, including controller opinion, are used to evaluate the effectiveness of the procedures.

The design and implementation of access control management system in IHEP network

International Nuclear Information System (INIS)

Wang Yanming; An Dehai; Qi Fazhi

2010-01-01

In campus network environment of Institute of High Energy Physics, because of the number of Network devices and computers are large scale, ensuring the access validity of network devices and user's computer, and aiming at effective control the exceptional network communication are technological means to achieve network normal running. The access control system of Campus network of institute of High Energy Physics using MySQL database in the behind, and using CGI PHP HTML language to develop the front interface. The System achieves user information management, user computer access control, cutting down the exceptional network communication and alarm function. Increasing the management effective of network, to ensure campus network safety and reliable running. (authors)

Application of neural networks to seismic active control

International Nuclear Information System (INIS)

Tang, Yu.

1995-01-01

An exploratory study on seismic active control using an artificial neural network (ANN) is presented in which a singledegree-of-freedom (SDF) structural system is controlled by a trained neural network. A feed-forward neural network and the backpropagation training method are used in the study. In backpropagation training, the learning rate is determined by ensuring the decrease of the error function at each training cycle. The training patterns for the neural net are generated randomly. Then, the trained ANN is used to compute the control force according to the control algorithm. The control strategy proposed herein is to apply the control force at every time step to destroy the build-up of the system response. The ground motions considered in the simulations are the N21E and N69W components of the Lake Hughes No. 12 record that occurred in the San Fernando Valley in California on February 9, 1971. Significant reduction of the structural response by one order of magnitude is observed. Also, it is shown that the proposed control strategy has the ability to reduce the peak that occurs during the first few cycles of the time history. These promising results assert the potential of applying ANNs to active structural control under seismic loads

Global efficiency of structural networks mediates cognitive control in Mild Cognitive Impairment

Directory of Open Access Journals (Sweden)

Rok Berlot

2016-12-01

Full Text Available Background: Cognitive control has been linked to both the microstructure of individual tracts and the structure of whole-brain networks, but their relative contributions in health and disease remain unclear. Objective: To determine the contribution of both localised white matter tract damage and disruption of global network architecture to cognitive control, in older age and Mild Cognitive Impairment (MCI.Methods: 25 patients with MCI and 20 age, sex and intelligence-matched healthy volunteers were investigated with 3 Tesla structural magnetic resonance imaging (MRI. Cognitive control and episodic memory were evaluated with established tests. Structural network graphs were constructed from diffusion MRI-based whole-brain tractography. Their global measures were calculated using graph theory. Regression models utilized both global network metrics and microstructure of specific connections, known to be critical for each domain, to predict cognitive scores. Results: Global efficiency and the mean clustering coefficient of networks were reduced in MCI. Cognitive control was associated with global network topology. Episodic memory, in contrast, correlated with individual temporal tracts only. Relationships between cognitive control and network topology were attenuated by addition of single tract measures to regression models, consistent with a partial mediation effect. The mediation effect was stronger in MCI than healthy volunteers, explaining 23-36% of the effect of cingulum microstructure on cognitive control performance. Network clustering was a significant mediator in the relationship between tract microstructure and cognitive control in both groups. Conclusions: The status of critical connections and large-scale network topology are both important for maintenance of cognitive control in MCI. Mediation via large-scale networks is more important in patients with MCI than healthy volunteers. This effect is domain-specific, and true for cognitive

Nonlinear adaptive inverse control via the unified model neural network

Science.gov (United States)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Design of energy efficient optical networks with software enabled integrated control plane

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2015-01-01

energy consumption by proposing a new integrated control plane structure utilising Software Defined Networking technologies. The integrated control plane increases the efficiencies of exchanging control information across different network domains, while introducing new possibilities to the routing...... methods and the control over quality of service (QoS). The structure is defined as an overlay generalised multi-protocol label switching (GMPLS) control model. With the defined structure, the integrated control plane is able to gather information from different domains (i.e. optical core network......'s) routing behaviours. With the flexibility of the routing structure, results show that the energy efficiency of the network can be improved without compromising the QoS for delay/blocking sensitive services....

Neural networks and orbit control in accelerators

International Nuclear Information System (INIS)

Bozoki, E.; Friedman, A.

1994-01-01

An overview of the architecture, workings and training of Neural Networks is given. We stress the aspects which are important for the use of Neural Networks for orbit control in accelerators and storage rings, especially its ability to cope with the nonlinear behavior of the orbit response to 'kicks' and the slow drift in the orbit response during long-term operation. Results obtained for the two NSLS storage rings with several network architectures and various training methods for each architecture are given

Context-Based Topology Control for Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Pragasen Mudali

2016-01-01

Full Text Available Topology Control has been shown to provide several benefits to wireless ad hoc and mesh networks. However these benefits have largely been demonstrated using simulation-based evaluations. In this paper, we demonstrate the negative impact that the PlainTC Topology Control prototype has on topology stability. This instability is found to be caused by the large number of transceiver power adjustments undertaken by the prototype. A context-based solution is offered to reduce the number of transceiver power adjustments undertaken without sacrificing the cumulative transceiver power savings and spatial reuse advantages gained from employing Topology Control in an infrastructure wireless mesh network. We propose the context-based PlainTC+ prototype and show that incorporating context information in the transceiver power adjustment process significantly reduces topology instability. In addition, improvements to network performance arising from the improved topology stability are also observed. Future plans to add real-time context-awareness to PlainTC+ will have the scheme being prototyped in a software-defined wireless mesh network test-bed being planned.

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

Science.gov (United States)

1996-01-01

An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

A control model for district heating networks with storage

NARCIS (Netherlands)

Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

2014-01-01

In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and

Risk Control Through the Use of Procedures - A Method for Evaluating the Change in Risk

Science.gov (United States)

Praino, Gregory; Sharit, Joseph

2010-01-01

Organizations use procedures to influence or control the behavior of their workers, but often have no basis for determining whether an additional rule, or procedural control will be beneficial. This paper outlines a proposed method for determining if the addition or removal of procedural controls will impact the occurrences of critical consequences. The proposed method focuses on two aspects: how valuable the procedural control is, based on the inevitability of the consequence and the opportunity to intervene; and how likely the control is to fail, based on five procedural design elements that address how well the rule or control has been Defined, Assigned, Trained, Organized and Monitored-referred to as the DATOM elements

Artificial neural networks in variable process control: application in particleboard manufacture

Energy Technology Data Exchange (ETDEWEB)

Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

2009-07-01

Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

Functional brain networks associated with cognitive control, cocaine dependence, and treatment outcome.

Science.gov (United States)

Worhunsky, Patrick D; Stevens, Michael C; Carroll, Kathleen M; Rounsaville, Bruce J; Calhoun, Vince D; Pearlson, Godfrey D; Potenza, Marc N

2013-06-01

Individuals with cocaine dependence often evidence poor cognitive control. The purpose of this exploratory study was to investigate networks of functional connectivity underlying cognitive control in cocaine dependence and examine the relationship of the networks to the disorder and its treatment. Independent component analysis (ICA) was applied to fMRI data to investigate if regional activations underlying cognitive control processes operate in functional networks, and whether these networks relate to performance and treatment outcome measures in cocaine dependence. Twenty patients completed a Stroop task during fMRI prior to entering outpatient treatment and were compared to 20 control participants. ICA identified five distinct functional networks related to cognitive control interference events. Cocaine-dependent patients displayed differences in performance-related recruitment of three networks. Reduced involvement of a "top-down" fronto-cingular network contributing to conflict monitoring correlated with better treatment retention. Greater engagement of two "bottom-up" subcortical and ventral prefrontal networks related to cue-elicited motivational processing correlated with abstinence during treatment. The identification of subcortical networks linked to cocaine abstinence and cortical networks to treatment retention suggests that specific circuits may represent important, complementary targets in treatment development for cocaine dependence. 2013 APA, all rights reserved

Frontal Parietal Control Network Regulates the Anti-Correlated Default and Dorsal Attention Networks

OpenAIRE

Gao, Wei; Lin, Weili

2011-01-01

Recent reports demonstrate the anti-correlated behaviors between the default and the dorsal attention (DA) networks. We aimed to investigate the roles of the frontal parietal control (FPC) network in regulating the two anti-correlated networks through three experimental conditions, including resting, continuous self-paced/attended sequential finger tapping (FT), and natural movie watching (MW), respectively. The two goal-directed tasks were chosen to engage either one of the two competing net...

Applying neural networks to control the TFTR neutral beam ion sources

International Nuclear Information System (INIS)

Lagin, L.

1992-01-01

This paper describes the application of neural networks to the control of the neutral beam long-pulse positive ion source accelerators on the Tokamak Fusion Test Reactor (TFTR) at Princeton University. Neural networks were used to learn how the operators adjust the control setpoints when running these sources. The data sets used to train these networks were derived from a large database containing actual setpoints and power supply waveform calculations for the 1990 run period. The networks learned what the optimum control setpoints should initially be set based uon desired accel voltage and perveance levels. Neural networks were also used to predict the divergence of the ion beam

Implementation of neural network based non-linear predictive control

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1999-01-01

This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

Intrusion Detection in Networked Control Systems: From System Knowledge to Network Security

NARCIS (Netherlands)

Caselli, M.

2016-01-01

“Networked control system‿ (NCS) is an umbrella term encompassing a broad variety of infrastructures such as industrial control systems (ICSs) and building automation systems (BASs). Nowadays, all these infrastructures play an important role in several aspects of our daily life, from managing

Feature-based comparison and selection of software defined networking (SDN) controllers

OpenAIRE

Khondoker, Rahamatullah; Zaalouk, Adel; Marx, Ronald; Bayarou, Kpatcha

2014-01-01

Software Defined Networking (SDN) is seen as one way to solve some problems of the Internet including security, managing complexity, multi-casting, load balancing, and energy efficiency. SDN is an architectural paradigm that separates the control plane of a networking device (e.g., a switch / router) from its data plane, making it feasible to control, monitor, and manage a network from a centralized node (the SDN controller). However, today there exists many SDN controllers including POX, Flo...

Broadband accelerator control network

International Nuclear Information System (INIS)

Skelly, J.; Clifford, T.; Frankel, R.

1983-01-01

A broadband data communications network has been implemented at BNL for control of the Alternating Gradient Synchrotron (AG) proton accelerator, using commercial CATV hardware, dual coaxial cables as the communications medium, and spanning 2.0 km. A 4 MHz bandwidth Digital Control channel using CSMA-CA protocol is provided for digital data transmission, with 8 access nodes available over the length of the RELWAY. Each node consists of an rf modem and a microprocessor-based store-and-forward message handler which interfaces the RELWAY to a branch line implemented in GPIB. A gateway to the RELWAY control channel for the (preexisting) AGS Computerized Accelerator Operating system has been constructed using an LSI-11/23 microprocessor as a device in a GPIB branch line. A multilayer communications protocol has been defined for the Digital Control Channel, based on the ISO Open Systems Interconnect layered model, and a RELWAY Device Language defined as the required universal language for device control on this channel

Active Queue Management in TCP Networks Based on Fuzzy-Pid Controller

Directory of Open Access Journals (Sweden)

Hossein ASHTIANI

2012-01-01

Full Text Available We introduce a novel and robust active queue management (AQM scheme based on a fuzzy controller, called hybrid fuzzy-PID controller. In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In this paper a novel Fuzzy-based proportional-integral derivative (PID controller, which acts as an active queue manager (AQM for Internet routers, is proposed. These controllers are used to reduce packet loss and improve network utilization in TCP/IP networks. A new hybrid controller is proposed and compared with traditional RED based controller. Simulations are carried out to demonstrate the effectiveness of the proposed method and show that, the new hybrid fuzzy PID controller provides better performance than random early detection (RED and PID controllers

Methodology for neural networks prototyping. Application to traffic control

Energy Technology Data Exchange (ETDEWEB)

Belegan, I.C.

1998-07-01

The work described in this report was carried out in the context of the European project ASTORIA (Advanced Simulation Toolbox for Real-World Industrial Application in Passenger Management and Adaptive Control), and concerns the development of an advanced toolbox for complex transportation systems. Our work was focused on the methodology for prototyping a set of neural networks corresponding to specific strategies for traffic control and congestion management. The tool used for prototyping is SNNS (Stuggart Neural Network Simulator), developed at the University of Stuggart, Institute for Parallel and Distributed High Performance Systems, and the real data from the field were provided by ZELT. This report is structured into six parts. The introduction gives some insights about traffic control and its approaches. The second chapter discusses the various control strategies existing. The third chapter is an introduction to the field of neural networks. The data analysis and pre-processing is described in the fourth chapter. In the fifth chapter, the methodology for prototyping the neural networks is presented. Finally, conclusions and further work are presented. (author) 14 refs.

Performance verification of network function virtualization in software defined optical transport networks

Science.gov (United States)

Zhao, Yongli; Hu, Liyazhou; Wang, Wei; Li, Yajie; Zhang, Jie

2017-01-01

With the continuous opening of resource acquisition and application, there are a large variety of network hardware appliances deployed as the communication infrastructure. To lunch a new network application always implies to replace the obsolete devices and needs the related space and power to accommodate it, which will increase the energy and capital investment. Network function virtualization1 (NFV) aims to address these problems by consolidating many network equipment onto industry standard elements such as servers, switches and storage. Many types of IT resources have been deployed to run Virtual Network Functions (vNFs), such as virtual switches and routers. Then how to deploy NFV in optical transport networks is a of great importance problem. This paper focuses on this problem, and gives an implementation architecture of NFV-enabled optical transport networks based on Software Defined Optical Networking (SDON) with the procedure of vNFs call and return. Especially, an implementation solution of NFV-enabled optical transport node is designed, and a parallel processing method for NFV-enabled OTN nodes is proposed. To verify the performance of NFV-enabled SDON, the protocol interaction procedures of control function virtualization and node function virtualization are demonstrated on SDON testbed. Finally, the benefits and challenges of the parallel processing method for NFV-enabled OTN nodes are simulated and analyzed.

Power Control in Wireless Sensor Networks with Variable Interference

Directory of Open Access Journals (Sweden)

Michele Chincoli

2016-01-01

Full Text Available Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counterproductive effects to network performance. Yet, indiscriminate power boosting may detrimentally affect interference. We are interested in understanding the conditions under which coordinated power reduction may lead to better spectrum efficiency and interference mitigation and, thus, have beneficial effects on network performance. Through simulations, we analyze the performance of sensor nodes in an environment with variable interference. Then we study the relation between transmission power and communication efficiency, particularly in the context of Adaptive and Robust Topology (ART control, showing how appropriate power reduction can benefit both energy and spectrum efficiency. We also identify critical limitations in ART, discussing the potential of more cooperative power control approaches.

Using Cognitive Control in Software Defined Networking for Port Scan Detection

Science.gov (United States)

2017-07-01

ARL-TR-8059 ● July 2017 US Army Research Laboratory Using Cognitive Control in Software -Defined Networking for Port Scan...Cognitive Control in Software -Defined Networking for Port Scan Detection by Vinod K Mishra Computational and Information Sciences Directorate, ARL...Technical Report 3. DATES COVERED (From - To) 15 June–31 July 2016 4. TITLE AND SUBTITLE Using Cognitive Control in Software -Defined Networking for

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

International Nuclear Information System (INIS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-01-01

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

Science.gov (United States)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-07-01

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Ortiz-Rodriguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solis Sanches, L. O.; Miranda, R. Castaneda; Cervantes Viramontes, J. M. [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica. Av. Ramon Lopez Velarde 801. Col. Centro Zacatecas, Zac (Mexico); Vega-Carrillo, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica. Av. Ramon Lopez Velarde 801. Col. Centro Zacatecas, Zac., Mexico. and Unidad Academica de Estudios Nucleares. C. Cip (Mexico)

2013-07-03

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in

Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

Science.gov (United States)

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.

Network Based Building Lighting Design and Fuzzy Logic via Remote Control

Directory of Open Access Journals (Sweden)

Cemal YILMAZ

2009-02-01

Full Text Available In this paper, a network based building lighting system is implemented. Profibus-DP network structure is used in the design and Fuzzy Logic Controller (FLC is used on control of the building lighting. Informations received from sensors which measures level of the building illumination is used on FLC and they are transferred to the system by Profibus-DP network. Control of lighting luminaries are made via Profibus-DP network. The illuminance inside the bulding is fitted required level. Energy saving and healthy lighting facilities have been obtained by the design.

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li

2013-06-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2013-01-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.