WorldWideScience

Sample records for network control snc

  1. Effect of locus of resource control on operational efficiency in distributed operations

    Science.gov (United States)

    Geoffroy, A. L.

    1991-01-01

    The following topics are presented in view graph form: space network control (SNC) usage in the Advanced Tracking and Data Relay Satellite (ATDRSS) era; an acronym and icon list; demands of the SNC; tightness of resources coupling; sharing information and sharing control; potential ways of distributing control; efficiency problems unrelated to distribution of control; efficiency problems related to distribution of control; and recommendations.

  2. Engineering technology for networks

    Science.gov (United States)

    Paul, Arthur S.; Benjamin, Norman

    1991-01-01

    Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling.

  3. 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.

  4. 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.

  5. Compositions of Mars Rocks: SNC Meteorites, Differentiates, and Soils

    Science.gov (United States)

    Rutherford, M. J.; Minitti, M.; Weitz, C. M.

    1999-01-01

    The 13 samples from Mars identified in the terrestrial meteorite collections vary from dunite to pyroxenite to microgabbro or basalt. All of these rocks appear to have formed from primitive melts with similar major element compositional characteristics; i.e., FeO-rich and Al2O3-Poor melts relative to terrestrial basalt compositions. Although all of the SNC rocks can be derived by melting of the same Al-depleted mantle, contamination of SNC's by a Rb-enriched mantle or crustal source is required to explain the different REE characteristics of SNC rocks. Thus, there are indications of an old crustal rocktype on Mars, and this rock does not appear to have been sampled. This paper focuses primarily on the composition of the SNC basalts, however, and on the compositions of rocks which could be derived from SNC basaltic melt by magmatic processes. In particular, we consider the possible compositions which could be achieved through accumulation of early-formed crystals in the SNC primitive magma. Through a set of experiments we have determined (1) melt (magma) compositions which could be produced by melt evolution as crystals are removed from batches of this magma cooling at depth, and (2) which evolved (Si02enriched, MgO-depleted) rock compositions could be produced from the SNC magma, and how these compare with the Pathfinder andesite composition. Finally, we compare the SNC magma compositions to the Mars soil composition in order to determine whether any source other than SNC is required.

  6. Controllability of Complex Networks

    Science.gov (United States)

    Liu, Yang; Slotine, Jean-Jacques; Barabasi, Albert-Laszlo

    2011-03-01

    The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered systems towards a desired state, we lack a general framework to control complex self-organized systems, like the regulatory network of a cell or the Internet. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes whose time-dependent control can guide the system's dynamics. We apply these tools to real and model networks, finding that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control. In contrast, dense and homogeneous networks can be controlled via a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the hubs. We show that the robustness of control to link failure is determined by a core percolation problem, helping us understand why many complex systems are relatively insensitive to link deletion. The developed approach offers a framework to address the controllability of an arbitrary network, representing a key step towards the eventual control of complex systems.

  7. 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.

  8. Broadband accelerator control network

    Energy Technology Data Exchange (ETDEWEB)

    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.

  9. 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....

  10. Controlling Congestion on Complex Networks

    CERN Document Server

    Buzna, Lubos

    2016-01-01

    From the Internet to road networks and the power grid, modern life depends on controlling flows on critical infrastructure networks that often operate in a congested state. Yet, we have a limited understanding of the relative performance of the control mechanisms available to manage congestion and of the interplay between network topology, path layout and congestion control algorithms. Here, we consider two flow algorithms (max-flow and uniform-flow), and two more realistic congestion control schemes (max-min fairness and proportional fairness). We analyse how the algorithms and network topology affect throughput, fairness and the location of bottleneck edges. Our results show that on large random networks a network operator can implement the trade-off (proportional fairness) instead of the fair allocation (max-min fairness) with little sacrifice in throughput. We illustrate how the previously studied uniform-flow approach leaves networks severely underutilised in comparison with congestion control algorithms...

  11. 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 ...

  12. Cybersecurity of Critical Control Networks

    Science.gov (United States)

    2015-07-14

    AFRL-OSR-VA-TR-2015-0173 CONGRESSIONAL) CYBERSECURITY OF CRITICAL CONTROL NETWORKS William Mahoney UNIVERSITY OF NEBRASKA Final Report 07/14/2015...Congressional) Cybersecurity of Critical Control Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0341 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR...FA9550-10-1-0341 Cybersecurity of Critical Control Networks Report Type Final Report Primary Contact E-mail wmahoney@unomaha.edu Primary

  13. Performance of Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yingwei Zhang

    2013-01-01

    Full Text Available Data packet dropout is a special kind of time delay problem. In this paper, predictive controllers for networked control systems (NCSs with dual-network are designed by model predictive control method. The contributions are as follows. (1 The predictive control problem of the dual-network is considered. (2 The predictive performance of the dual-network is evaluated. (3 Compared to the popular networked control systems, the optimal controller of the new NCSs with data packets dropout is designed, which can minimize infinite performance index at each sampling time and guarantee the closed-loop system stability. Finally, the simulation results show the feasibility and effectiveness of the controllers designed.

  14. 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

  15. From the axons of the SNc dopamine neurons to their dendritic processes: further clues to susceptibility in Parkinson’s disease (PD?

    Directory of Open Access Journals (Sweden)

    Eleftheria Kyriaki Pissadaki

    2014-04-01

    shown to facilitate bursting behaviour, we hypothesise that SNc neurons with dendrites in both compartments are more likely to generate bursts. Preliminary results indicate that the temporal latencies of synaptic stimulation in the two sub-cellular compartments can sculpt the output of the model neuron. These findings may represent a driving mechanism that explains how the local ongoing network activity can modulate the activity of SNc dopamine neurons and underlie changes from autonomous to burst firing.

  16. 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...... examined, and it appears that considering 'normal' neural network models with, say, 500 samples, the problem of over-fitting is neglible, and therefore it is not taken into consideration afterwards. Numerous model types, often met in control applications, are implemented as neural network models...... 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...

  17. Positive train control shared network.

    Science.gov (United States)

    2015-05-01

    The Interoperable Train Control (ITC) Positive : Train Control (PTC) Shared Network (IPSN) : project investigated anticipated industry benefits : and the level of support for the development of : a hosted technological platform for PTC : messaging ac...

  18. SNC Meteorites, Organic Matter and a New Look at Viking

    Science.gov (United States)

    Warmflash, David M.; Clemett, Simon J.; McKay, David S.

    2001-01-01

    experiment, a solution containing C-14 labeled organic compounds was injected into soil samples. The detection of radioactivity in the overhead space would indicate that one or more of the substrates had been chemically converted into a carbon-containing gas. To serve as a control, some samples were heated enough to destroy most known terrestrial microbes so that an indication for life would be a positive response from unheated samples and a negative response from heated samples. On Mars, the LR results had met minimum criteria for a biological interpretation but due to the GC-MS results, the LR responses were later attributed to putative soil inorganic oxidants. Since the time of Viking, studies have been carried out with the objective of determining an oxidant or combination of oxidants that might exist on Mars and have produced the observed kinetics of the LR response. To date, no such agent has been found that produces all aspects of the LR results on Mars. While the above considerations in no way imply the existence of life forms at the two Viking landing sites, inorganic and biological explanations for the Viking LR data should now be considered equally plausible until more complete studies of the Martian surface are carried out. Therefore, in light of the SNC meteorites data and their implications for the possibility of organic matter near or on the Martian surface the Viking biology experiments should thus be seen, not as failures for their inability to provide unambiguous evidence for or against Martian life, but as a foundation for the development of future life-detection instruments. Additional information is contained in the original extended abstract.

  19. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    simulated process and compared. The closing chapter describes some practical experiments, where the different control concepts and training methods are tested on the same practical process operating in very noisy environments. All tests confirm that neural networks also have the potential to be trained......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...

  20. HSUPA Transport Network Congestion Control

    Directory of Open Access Journals (Sweden)

    Nádas Szilveszter

    2009-01-01

    Full Text Available The introduction of High Speed Uplink Packet Access (HSUPA greatly improves achievable uplink bitrate but it presents new challenges to be solved in the WCDMA radio access network. In the transport network, bandwidth reservation for HSUPA is not efficient and TCP cannot efficiently resolve congestion because of lower layer retransmissions. This paper proposes an HSUPA transport network flow control algorithm that handles congestion situations efficiently and supports Quality of Service differentiation. In the Radio Network Controller (RNC, transport network congestion is detected. Relying on the standardized control frame, the RNC notifies the Node B about transport network congestion. In case of transport network congestion, the Node B part of the HSUPA flow control instructs the air interface scheduler to reduce the bitrate of the flow to eliminate congestion. The performance analysis concentrates on transport network limited scenarios. It is shown that TCP cannot provide efficient congestion control. The proposed algorithm can achieve high end-user perceived throughput, while maintaining low delay, loss, and good fairness in the transport network.

  1. 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. .

  2. Understanding control of network spreading from network controllability

    Science.gov (United States)

    Sun, Peng Gang; Ma, Xiaoke

    2017-09-01

    How to control the spread of an epidemic or information is a great challenge for us. A dynamic network-based system’s structural controllability provides a new way to control spreading with the minimum input of external signals, and the dynamic system is controllable if the signals can drive it from any initial state to any desired final state in finite time. Therefore, we are motivated to develop a new framework by introducing spreading networks (SNs) to describe the spreading pathways from a global view, and we try to understand the control of the spreading by the structural controllability of the SNs. The SNs are transformed from original networks, in which each node is considered as a single spreading origin. The weights of directed links pointing at its direct contacts in the SNs denote the spreading abilities, which can be determined by a new probability function. Furthermore, we also investigate the impact of the dynamics of network structures on the framework. The results show that sparse homogeneous networks with a higher transmission probability tend to trigger a larger scale of diffusion, which is easier to control. We can also see that an epidemic or information is inclined to diffuse easily on the networks with strong community strengths and heterogeneous community sizes. From the structural controllability of the SNs, we observe that driver nodes for the control of the spread tend not to be the nodes located within the core of original networks or those with high-degree. In addition, the scale of diffusion, the number of driver nodes and positions of nodes are highly associated with the degree distribution of the original networks.

  3. 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...

  4. Regulation of transcription of nucleotide-binding leucine-rich repeat-encoding genes SNC1 and RPP4 via H3K4 trimethylation.

    Science.gov (United States)

    Xia, Shitou; Cheng, Yu Ti; Huang, Shuai; Win, Joe; Soards, Avril; Jinn, Tsung-Luo; Jones, Jonathan D G; Kamoun, Sophien; Chen, She; Zhang, Yuelin; Li, Xin

    2013-07-01

    Plant nucleotide-binding leucine-rich repeat (NB-LRR) proteins serve as intracellular sensors to detect pathogen effectors and trigger immune responses. Transcription of the NB-LRR-encoding Resistance (R) genes needs to be tightly controlled to avoid inappropriate defense activation. How the expression of the NB-LRR R genes is regulated is poorly understood. The Arabidopsis (Arabidopsis thaliana) suppressor of npr1-1, constitutive 1 (snc1) mutant carries a gain-of-function mutation in a Toll/Interleukin1 receptor-like (TIR)-NB-LRR-encoding gene, resulting in the constitutive activation of plant defense responses. A snc1 suppressor screen identified modifier of snc1,9 (mos9), which partially suppresses the autoimmune phenotypes of snc1. Positional cloning revealed that MOS9 encodes a plant-specific protein of unknown function. Expression analysis showed that MOS9 is required for the full expression of TIR-NB-LRR protein-encoding RECOGNITION OF PERONOSPORA PARASITICA 4 (RPP4) and SNC1, both of which reside in the RPP4 cluster. Coimmunoprecipitation and mass spectrometry analyses revealed that MOS9 associates with the Set1 class lysine 4 of histone 3 (H3K4) methyltransferase Arabidopsis Trithorax-Related7 (ATXR7). Like MOS9, ATXR7 is also required for the full expression of SNC1 and the autoimmune phenotypes in the snc1 mutant. In atxr7 mutant plants, the expression of RPP4 is similarly reduced, and resistance against Hyaloperonospora arabidopsidis Emwa1 is compromised. Consistent with the attenuated expression of SNC1 and RPP4, trimethylated H3K4 marks are reduced around the promoters of SNC1 and RPP4 in mos9 plants. Our data suggest that MOS9 functions together with ATXR7 to regulate the expression of SNC1 and RPP4 through H3K4 methylation, which plays an important role in fine-tuning their transcription levels and functions in plant defense.

  5. 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.

  6. 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...... 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...... 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...

  7. 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 ...

  8. Dynamic Network Security Control Using Software Defined Networking

    Science.gov (United States)

    2016-03-24

    not subject to copyright protection in the United States. AFIT-ENG-MS-16-M-049 DYNAMIC NETWORK SECURITY CONTROL USING SOFTWARE DEFINED NETWORKING... software and tools vetted by industry leaders in networking and security. After considering the technologies previously discussed, the four components...DYNAMIC NETWORK SECURITY CONTROL USING SOFTWARE DEFINED NETWORKING THESIS Michael C. Todd, Captain, USAF AFIT-ENG-MS-16-M-049 DEPARTMENT OF THE AIR

  9. Spectral coarse grained controllability of complex networks

    Science.gov (United States)

    Wang, Pei; Xu, Shuang

    2017-07-01

    With the accumulation of interaction data from various systems, a fundamental question in network science is how to reduce the sizes while keeping certain properties of complex networks. Combined the spectral coarse graining theory and the structural controllability of complex networks, we explore the structural controllability of undirected complex networks during coarse graining processes. We evidence that the spectral coarse grained controllability (SCGC) properties for the Erdös-Rényi (ER) random networks, the scale-free (SF) random networks and the small-world (SW) random networks are distinct from each other. The SW networks are very robust, while the SF networks are sensitive during the coarse graining processes. As an emergent properties for the dense ER networks, during the coarse graining processes, there exists a threshold value of the coarse grained sizes, which separates the controllability of the reduced networks into robust and sensitive to coarse graining. Investigations on some real-world complex networks indicate that the SCGC properties are varied among different categories and different kinds of networks, some highly organized social or biological networks are more difficult to be controlled, while many man-made power networks and infrastructure networks can keep the controllability properties during the coarse graining processes. Furthermore, we speculate that the SCGC properties of complex networks may depend on their degree distributions. The associated investigations have potential implications in the control of large-scale complex networks, as well as in the understanding of the organization of complex networks.

  10. 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.

  11. Controllability of the better chosen partial networks

    Science.gov (United States)

    Liu, Xueming; Pan, Linqiang

    2016-08-01

    How to control large complex networks is a great challenge. Recent studies have proved that the whole network can be sufficiently steered by injecting control signals into a minimum set of driver nodes, and the minimum numbers of driver nodes for many real networks are high, indicating that it is difficult to control them. For some large natural and technological networks, it is impossible and not feasible to control the full network. For example, in biological networks like large-scale gene regulatory networks it is impossible to control all the genes. This prompts us to explore the question how to choose partial networks that are easy for controlling and important in networked systems. In this work, we propose a method to achieve this goal. By computing the minimum driver nodes densities of the partial networks of Erdös-Rényi (ER) networks, scale-free (SF) networks and 23 real networks, we find that our method performs better than random method that chooses nodes randomly. Moreover, we find that the nodes chosen by our method tend to be the essential elements of the whole systems, via studying the nodes chosen by our method of a real human signaling network and a human protein interaction network and discovering that the chosen nodes from these networks tend to be cancer-associated genes. The implementation of our method shows some interesting connections between the structure and the controllability of networks, improving our understanding of the control principles of complex systems.

  12. Robustness of network controllability in cascading failure

    Science.gov (United States)

    Chen, Shi-Ming; Xu, Yun-Fei; Nie, Sen

    2017-04-01

    It is demonstrated that controlling complex networks in practice needs more inputs than that predicted by the structural controllability framework. Besides, considering the networks usually faces to the external or internal failure, we define parameters to evaluate the control cost and the variation of controllability after cascades, exploring the effect of number of control inputs on the controllability for random networks and scale-free networks in the process of cascading failure. For different topological networks, the results show that the robustness of controllability will be stronger through allocating different control inputs and edge capacity.

  13. Congestion control in satellite networks

    Science.gov (United States)

    Byun, Do Jun

    Due to exponential increases in internet traffic, Active Queue Management (AQM) has been heavily studied by numerous researchers. However, little is known about AQM in satellite networks. A microscopic examination of queueing behavior in satellite networks is conducted to identify problems with applying existing AQM methods. A new AQM method is proposed to overcome the problems and it is validated using a realistic emulation environment and a mathematical model. Three problems that were discovered during the research are discussed in this dissertation. The first problem is oscillatory queueing, which is caused by high buffering due to Performance Enhancing Proxy (PEP) in satellite networks where congestion control after the PEP buffering does not effectively control traffic senders. Existing AQMs that can solve this problem have tail drop queueing that results in consecutive packet drops (global synchronization). A new AQM method called Adaptive Virtual Queue Random Early Detection (AVQRED) is proposed to solve this problem. The second problem is unfair bandwidth sharing caused by inaccurate measurements of per-flow bandwidth usage. AVQRED is enhanced to accurately measure per-flow bandwidth usage to solve this problem without adding much complexity to the algorithm. The third problem is queueing instability caused by buffer flow control where TCP receive windows are adjusted to flow control traffic senders instead of dropping received packets during congestion. Although buffer flow control is quite attractive to satellite networks, queueing becomes unstable because accepting packets instead of dropping them aggravates the congestion level. Furthermore, buffer flow control has abrupt reductions in the TCP receive window size due to high PEP buffering causing more instability. AVQRED with packet drop is proposed to solve this problem. Networks with scarce bandwidth and high propagation delays can not afford to have an unstable AQM. In this research, three problems

  14. 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.

  15. Opinion control in complex networks

    Science.gov (United States)

    Masuda, Naoki

    2015-03-01

    In many political elections, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, an important goal for a political party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and the effects of peer-to-peer influence. Based on the exact solution of classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method that uses pinning control strategy to maximize the share of a party in a social network of independent voters. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opposing party controls. We show that controlling hubs is generally a good strategy, but the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed (rather than undirected) networks.

  16. Flexible Tube-Based Network Control Project

    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...

  17. Controllability of flow-conservation networks

    Science.gov (United States)

    Zhao, Chen; Zeng, An; Jiang, Rui; Yuan, Zhengzhong; Wang, Wen-Xu

    2017-07-01

    The ultimate goal of exploring complex networks is to control them. As such, controllability of complex networks has been intensively investigated. Despite recent advances in studying the impact of a network's topology on its controllability, a comprehensive understanding of the synergistic impact of network topology and dynamics on controllability is still lacking. Here, we explore the controllability of flow-conservation networks, trying to identify the minimal number of driver nodes that can guide the network to any desirable state. We develop a method to analyze the controllability on flow-conservation networks based on exact controllability theory, transforming the original analysis on adjacency matrix to Laplacian matrix. With this framework, we systematically investigate the impact of some key factors of networks, including link density, link directionality, and link polarity, on the controllability of these networks. We also obtain the analytical equations by investigating the network's structural properties approximatively and design the efficient tools. Finally, we consider some real networks with flow dynamics, finding that their controllability is significantly different from that predicted by only considering the topology. These findings deepen our understanding of network controllability with flow-conservation dynamics and provide a general framework to incorporate real dynamics in the analysis of network controllability.

  18. Constrained target controllability of complex networks

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

    2017-06-01

    It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

  19. 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.

  20. 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...

  1. Synchronizability on complex networks via pinning control

    Indian Academy of Sciences (India)

    pinning strategies have different pinning synchronizability on the same complex network, and the synchronizability with pinning control is consistent with one without pinning control in various complex networks. Keywords. Complex network; the pinning synchronization; synchronizability. PACS Nos 05.45.Xt; 89.75.−k; 05.45.

  2. Opinion control in complex networks

    CERN Document Server

    Masuda, Naoki

    2014-01-01

    In many instances of election, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, a main goal for a party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and effects of peer-to-peer influence. Based on the exact solution of the classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method to maximize the share of the party in a social network of independent voters by pinning control strategy. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opponent party controls. We show that controlling hubs is generally a good strategy, whereas the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the inde...

  3. Regulation of Transcription of Nucleotide-Binding Leucine-Rich Repeat-Encoding Genes SNC1 and RPP4 via H3K4 Trimethylation1[C][W][OA

    Science.gov (United States)

    Xia, Shitou; Cheng, Yu Ti; Huang, Shuai; Win, Joe; Soards, Avril; Jinn, Tsung-Luo; Jones, Jonathan D.G.; Kamoun, Sophien; Chen, She; Zhang, Yuelin; Li, Xin

    2013-01-01

    Plant nucleotide-binding leucine-rich repeat (NB-LRR) proteins serve as intracellular sensors to detect pathogen effectors and trigger immune responses. Transcription of the NB-LRR-encoding Resistance (R) genes needs to be tightly controlled to avoid inappropriate defense activation. How the expression of the NB-LRR R genes is regulated is poorly understood. The Arabidopsis (Arabidopsis thaliana) suppressor of npr1-1, constitutive 1 (snc1) mutant carries a gain-of-function mutation in a Toll/Interleukin1 receptor-like (TIR)-NB-LRR-encoding gene, resulting in the constitutive activation of plant defense responses. A snc1 suppressor screen identified modifier of snc1,9 (mos9), which partially suppresses the autoimmune phenotypes of snc1. Positional cloning revealed that MOS9 encodes a plant-specific protein of unknown function. Expression analysis showed that MOS9 is required for the full expression of TIR-NB-LRR protein-encoding RECOGNITION OF PERONOSPORA PARASITICA 4 (RPP4) and SNC1, both of which reside in the RPP4 cluster. Coimmunoprecipitation and mass spectrometry analyses revealed that MOS9 associates with the Set1 class lysine 4 of histone 3 (H3K4) methyltransferase Arabidopsis Trithorax-Related7 (ATXR7). Like MOS9, ATXR7 is also required for the full expression of SNC1 and the autoimmune phenotypes in the snc1 mutant. In atxr7 mutant plants, the expression of RPP4 is similarly reduced, and resistance against Hyaloperonospora arabidopsidis Emwa1 is compromised. Consistent with the attenuated expression of SNC1 and RPP4, trimethylated H3K4 marks are reduced around the promoters of SNC1 and RPP4 in mos9 plants. Our data suggest that MOS9 functions together with ATXR7 to regulate the expression of SNC1 and RPP4 through H3K4 methylation, which plays an important role in fine-tuning their transcription levels and functions in plant defense. PMID:23690534

  4. Controlling complex networks with conformity behavior

    Science.gov (United States)

    Wang, Xu-Wen; Nie, Sen; Wang, Wen-Xu; Wang, Bing-Hong

    2015-09-01

    Controlling complex networks accompanied by common conformity behavior is a fundamental problem in social and physical science. Conformity behavior that individuals tend to follow the majority in their neighborhood is common in human society and animal communities. Despite recent progress in understanding controllability of complex networks, the existent controllability theories cannot be directly applied to networks associated with conformity. Here we propose a simple model to incorporate conformity-based decision making into the evolution of a network system, which allows us to employ the exact controllability theory to explore the controllability of such systems. We offer rigorous theoretical results of controllability for representative regular networks. We also explore real networks in different fields and some typical model networks, finding some interesting results that are different from the predictions of structural and exact controllability theory in the absence of conformity. We finally present an example of steering a real social network to some target states to further validate our controllability theory and tools. Our work offers a more realistic understanding of network controllability with conformity behavior and can have potential applications in networked evolutionary games, opinion dynamics and many other complex networked systems.

  5. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  6. 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

  7. Controller placement problem in industrial networks

    OpenAIRE

    Macián Ribera, Sergi

    2016-01-01

    SDN is the new trend in networks, for next Mobile and optical networks. Dimensioning, design and optimization of Software Defined Optical Networks. To be done at Technical University Munich (TUM) In this work the Controller Placement Problem (CPP) for SDN architecture is studied when it is applied to industrial networks. En este trabajo se estudia el problema CPP (controller placement problem) para la arquitectura SDN, aplicado a redes industriales. En aquest treball s'estudia el pro...

  8. The Sec1/Munc18 protein Vps45 regulates cellular levels of its SNARE binding partners Tlg2 and Snc2 in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Scott G Shanks

    Full Text Available Intracellular membrane trafficking pathways must be tightly regulated to ensure proper functioning of all eukaryotic cells. Central to membrane trafficking is the formation of specific SNARE (soluble N-ethylmeleimide-sensitive factor attachment protein receptor complexes between proteins on opposing lipid bilayers. The Sec1/Munc18 (SM family of proteins play an essential role in SNARE-mediated membrane fusion, and like the SNAREs are conserved through evolution from yeast to humans. The SM protein Vps45 is required for the formation of yeast endosomal SNARE complexes and is thus essential for traffic through the endosomal system. Here we report that, in addition to its role in regulating SNARE complex assembly, Vps45 regulates cellular levels of its SNARE binding partners: the syntaxin Tlg2 and the v-SNARE Snc2: Cells lacking Vps45 have reduced cellular levels of Tlg2 and Snc2; and elevation of Vps45 levels results in concomitant increases in the levels of both Tlg2 and Snc2. As well as regulating traffic through the endosomal system, the Snc v-SNAREs are also required for exocytosis. Unlike most vps mutants, cells lacking Vps45 display multiple growth phenotypes. Here we report that these can be reversed by selectively restoring Snc2 levels in vps45 mutant cells. Our data indicate that as well as functioning as part of the machinery that controls SNARE complex assembly, Vps45 also plays a key role in determining the levels of its cognate SNARE proteins; another key factor in regulation of membrane traffic.

  9. Advanced systems engineering and network planning support

    Science.gov (United States)

    Walters, David H.; Barrett, Larry K.; Boyd, Ronald; Bazaj, Suresh; Mitchell, Lionel; Brosi, Fred

    1990-01-01

    The objective of this task was to take a fresh look at the NASA Space Network Control (SNC) element for the Advanced Tracking and Data Relay Satellite System (ATDRSS) such that it can be made more efficient and responsive to the user by introducing new concepts and technologies appropriate for the 1997 timeframe. In particular, it was desired to investigate the technologies and concepts employed in similar systems that may be applicable to the SNC. The recommendations resulting from this study include resource partitioning, on-line access to subsets of the SN schedule, fluid scheduling, increased use of demand access on the MA service, automating Inter-System Control functions using monitor by exception, increase automation for distributed data management and distributed work management, viewing SN operational control in terms of the OSI Management framework, and the introduction of automated interface management.

  10. Abnormal thermal shock behavior in electrical conductivity of Ti2SnC

    Directory of Open Access Journals (Sweden)

    Linquan Zhang

    2017-08-01

    Full Text Available Some ternary carbide and nitride ceramics have been demonstrated to exhibit abnormal thermal shock behavior in mechanical properties. However, the influence of thermal shock on other properties is not clear. This work reports on the influence of thermal shock on electrical conductivity of Ti2SnC as a representative member of ternary carbides. Abnormal change in electrical conductivity was first demonstrated during quenching Ti2SnC in water at 500–800 °C. The residual electrical conductivity of the quenched Ti2SnC gradually decreased with increasing temperature, but abnormally increased after quenching at 600 °C. The microstructure of surface cracks was characterized. The main mechanism for the abnormal electrical conductivity recovery is that some narrow branching cracks are filled by metallic Sn precipitating from Ti2SnC.

  11. 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...

  12. 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...

  13. PID Controller Based on Memristive CMAC Network

    Directory of Open Access Journals (Sweden)

    Lidan Wang

    2013-01-01

    Full Text Available Compound controller which consists of CMAC network and PID network is mainly used in control system, especially in robot control. It can realize nonlinear tracking control of the real-time dynamic trajectory and possesses good approximation effect. According to the structure and principle of the compound controller, memristor is introduced to CMAC network to be a compound controller in this paper. The new PID controller based on memristive CMAC network is built up by replacing the synapse in the original controller by memristors. The effect of curve approximation is obtained by MATLAB simulation experiments. This network improves the response and learning speed of the system and processes better robustness and antidisturbance performance.

  14. 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

  15. 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...

  16. 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

  17. Cloud-based Networked Visual Servo Control

    DEFF Research Database (Denmark)

    Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

    2013-01-01

    feedback, ii) a stabilizing control law for the networked visual servo control system with time-varying feedback time delay, and iii) a sending rate scheduling strategy aiming at reducing the communication network load. The performance of the networked visual servo control system with sending rate......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 transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

  18. 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....

  19. 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....

  20. Stress controls the mechanics of collagen networks

    Science.gov (United States)

    Licup, Albert James; Münster, Stefan; Sharma, Abhinav; Sheinman, Michael; Jawerth, Louise M.; Fabry, Ben; Weitz, David A.; MacKintosh, Fred C.

    2015-01-01

    Collagen is the main structural and load-bearing element of various connective tissues, where it forms the extracellular matrix that supports cells. It has long been known that collagenous tissues exhibit a highly nonlinear stress–strain relationship, although the origins of this nonlinearity remain unknown. Here, we show that the nonlinear stiffening of reconstituted type I collagen networks is controlled by the applied stress and that the network stiffness becomes surprisingly insensitive to network concentration. We demonstrate how a simple model for networks of elastic fibers can quantitatively account for the mechanics of reconstituted collagen networks. Our model points to the important role of normal stresses in determining the nonlinear shear elastic response, which can explain the approximate exponential relationship between stress and strain reported for collagenous tissues. This further suggests principles for the design of synthetic fiber networks with collagen-like properties, as well as a mechanism for the control of the mechanics of such networks. PMID:26195769

  1. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    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....... 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...... to solve nonlinear optimal control problems. In the water supply system model, the hydraulic resistance of the valve is estimated by real data and it is considered to be a disturbance. The disturbance in our system is updated every 24 hours based on the amount of water usage by consumers every day. Model...

  2. 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.

  3. 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.

  4. Detecting controlling nodes of boolean regulatory networks.

    Science.gov (United States)

    Schober, Steffen; Kracht, David; Heckel, Reinhard; Bossert, Martin

    2011-10-11

    Boolean models of regulatory networks are assumed to be tolerant to perturbations. That qualitatively implies that each function can only depend on a few nodes. Biologically motivated constraints further show that functions found in Boolean regulatory networks belong to certain classes of functions, for example, the unate functions. It turns out that these classes have specific properties in the Fourier domain. That motivates us to study the problem of detecting controlling nodes in classes of Boolean networks using spectral techniques. We consider networks with unbalanced functions and functions of an average sensitivity less than 23k, where k is the number of controlling variables for a function. Further, we consider the class of 1-low networks which include unate networks, linear threshold networks, and networks with nested canalyzing functions. We show that the application of spectral learning algorithms leads to both better time and sample complexity for the detection of controlling nodes compared with algorithms based on exhaustive search. For a particular algorithm, we state analytical upper bounds on the number of samples needed to find the controlling nodes of the Boolean functions. Further, improved algorithms for detecting controlling nodes in large-scale unate networks are given and numerically studied.

  5. Controlling congestion on complex networks: fairness, efficiency and network structure.

    Science.gov (United States)

    Buzna, Ľuboš; Carvalho, Rui

    2017-08-22

    We consider two elementary (max-flow and uniform-flow) and two realistic (max-min fairness and proportional fairness) congestion control schemes, and analyse how the algorithms and network structure affect throughput, the fairness of flow allocation, and the location of bottleneck edges. The more realistic proportional fairness and max-min fairness algorithms have similar throughput, but path flow allocations are more unequal in scale-free than in random regular networks. Scale-free networks have lower throughput than their random regular counterparts in the uniform-flow algorithm, which is favoured in the complex networks literature. We show, however, that this relation is reversed on all other congestion control algorithms for a region of the parameter space given by the degree exponent γ and average degree 〈k〉. Moreover, the uniform-flow algorithm severely underestimates the network throughput of congested networks, and a rich phenomenology of path flow allocations is only present in the more realistic α-fair family of algorithms. Finally, we show that the number of paths passing through an edge characterises the location of a wide range of bottleneck edges in these algorithms. Such identification of bottlenecks could provide a bridge between the two fields of complex networks and congestion control.

  6. 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...

  7. Emergence of bimodality in controlling complex networks

    CERN Document Server

    Jia, Tao; Csóka, Endre; Pósfai, Márton; Slotine, Jean-Jacques; Barabási, Albert-László

    2015-01-01

    Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achieve full control, predict the existence of multiple control configurations, prompting us to classify each node in a network based on their role in control. Accordingly a node is critical, intermittent or redundant if it acts as a driver node in all, some or none of the control configurations. Here we develop an analytical framework to identify the category of each node, leading to the discovery of two distinct control modes in complex systems: centralized vs distributed control. We predict the control mode for an arbitrary network and show that one can alter it through small structural perturbations. The uncovered bimodality has implications from network security to organizational research and offers new insights into the dynamics and control of complex systems.

  8. Advanced mobile networking, sensing, and controls.

    Energy Technology Data Exchange (ETDEWEB)

    Feddema, John Todd; Kilman, Dominique Marie; Byrne, Raymond Harry; Young, Joseph G.; Lewis, Christopher L.; Van Leeuwen, Brian P.; Robinett, Rush D. III; Harrington, John J.

    2005-03-01

    This report describes an integrated approach for designing communication, sensing, and control systems for mobile distributed systems. Graph theoretic methods are used to analyze the input/output reachability and structural controllability and observability of a decentralized system. Embedded in each network node, this analysis will automatically reconfigure an ad hoc communication network for the sensing and control task at hand. The graph analysis can also be used to create the optimal communication flow control based upon the spatial distribution of the network nodes. Edge coloring algorithms tell us that the minimum number of time slots in a planar network is equal to either the maximum number of adjacent nodes (or degree) of the undirected graph plus some small number. Therefore, the more spread out that the nodes are, the fewer number of time slots are needed for communication, and the smaller the latency between nodes. In a coupled system, this results in a more responsive sensor network and control system. Network protocols are developed to propagate this information, and distributed algorithms are developed to automatically adjust the number of time slots available for communication. These protocols and algorithms must be extremely efficient and only updated as network nodes move. In addition, queuing theory is used to analyze the delay characteristics of Carrier Sense Multiple Access (CSMA) networks. This report documents the analysis, simulation, and implementation of these algorithms performed under this Laboratory Directed Research and Development (LDRD) effort.

  9. Robust Multiobjective Controllability of Complex Neuronal Networks.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Du, Wei; Lu, Jianquan; Vasilakos, Athanasios V; Kurths, Jurgen

    2016-01-01

    This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.

  10. 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

  11. 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.

  12. Self-Control in Sparsely Coded Networks

    Science.gov (United States)

    Dominguez, D. R. C.; Bollé, D.

    1998-03-01

    A complete self-control mechanism is proposed in the dynamics of neural networks through the introduction of a time-dependent threshold, determined in function of both the noise and the pattern activity in the network. Especially for sparsely coded models this mechanism is shown to considerably improve the storage capacity, the basins of attraction, and the mutual information content.

  13. 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.

  14. 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 Engineer......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...

  15. SNC Oxygen Fugacity Recorded in Pyroxenes and its Implications for the Oxidation State of the Martian Interior: An Experimental and Analytical Study

    Science.gov (United States)

    McCanta, M. C.; Rutherford, M. J.

    2003-01-01

    Knowledge of the oxidation state of a magma is critical as it is one of the parameters which controls the nature and composition of the resulting crystals. In terrestrial magmatic systems, oxygen fugacity (fo2) is known to vary by over nine orders of magnitude. With variations of this magnitude, understanding the compositional differences, phase changes, and crystallization sequence variations, caused by the magma fo2, is essential in deciphering the origin of all igneous rocks. Magmatic oxidation state is of great importance in that it reflects the degree of oxidation of the source region and can provide insight into magmatic processes, such as metasomatism, degassing, and assimilation, which may have changed them. Carmichael [1991] argues that most magmas are unlikely to have their redox states altered from those of their source region. This assumption allows for estimation of the oxidation state of planetary interiors. Conversely, it is known that the fo2 of the magma can be affected by other processes, which occur outside of the source region and therefore, the oxidation state may record those too. Processes which could overprint source region fugacities include melt dehydrogenation or other volatile loss, water or melt infiltration, or assimilation of oxidized or reduced wallrock. Understanding which of these processes is responsible for the redox state of a magma can provide crucial information regarding igneous processes and other forces active in the region. The composition of the SNC basalts and their widely varying proposed oxidation states raise some interesting questions. Do the SNC meteorites have an oxidized or reduced signature? What was the oxygen fugacity of the SNC source region at the time of melt generation? Is the fugacity calculated for the various SNC samples the fugacity of the magma source region or was it overprinted by later events? Are there different oxidation states in the Martian interior or a single one? This proposal seeks to

  16. Inferring network connectivity by delayed feedback control.

    Directory of Open Access Journals (Sweden)

    Dongchuan Yu

    Full Text Available We suggest a control based approach to topology estimation of networks with N elements. This method first drives the network to steady states by a delayed feedback control; then performs structural perturbations for shifting the steady states M times; and finally infers the connection topology from the steady states' shifts by matrix inverse algorithm (M = N or l(1-norm convex optimization strategy applicable to estimate the topology of sparse networks from M << N perturbations. We discuss as well some aspects important for applications, such as the topology reconstruction quality and error sources, advantages and disadvantages of the suggested method, and the influence of (control perturbations, inhomegenity, sparsity, coupling functions, and measurement noise. Some examples of networks with Chua's oscillators are presented to illustrate the reliability of the suggested technique.

  17. SncRNA715 Inhibits Schwann Cell Myelin Basic Protein Synthesis.

    Directory of Open Access Journals (Sweden)

    Christina Müller

    Full Text Available Myelin basic proteins (MBP are major constituents of the myelin sheath in the central nervous system (CNS and the peripheral nervous system (PNS. In the CNS Mbp translation occurs locally at the axon-glial contact site in a neuronal activity-dependent manner. Recently we identified the small non-coding RNA 715 (sncRNA715 as a key inhibitor of Mbp translation during transport in oligodendrocytes. Mbp mRNA localization in Schwann cells has been observed, but has not been investigated in much detail. Here we could confirm translational repression of Mbp mRNA in Schwann cells. We show that sncRNA715 is expressed and its levels correlate inversely with MBP in cultured Schwann cells and in the sciatic nerve in vivo. Furthermore we could reduce MBP protein levels in cultured Schwann cells by increasing the levels of the inhibitory sncRNA715. Our findings suggest similarities in sncRNA715-mediated translational repression of Mbp mRNA in oligodendrocytes and Schwann cells.

  18. Next Generation Network Routing and Control Plane

    DEFF Research Database (Denmark)

    Fu, Rong

    proved, the dominating Border Gateway Protocol (BGP) cannot address all the issues that in inter-domain QoS routing. Thus a new protocol or network architecture has to be developed to be able to carry the inter-domain traffic with the QoS and TE consideration. Moreover, the current network control also......-domain. It is a routing component that flexibly supports path computation with different requirements, constraints and areas. It is also can be seen as part of NGN transport control plane, which integrates with the other functions. In the aspect of resource control, an NGN release Resource and Admission Control Functions...... of Service classes. Under the NGN context, there are plenty of proposals intending to accommodate the issues listed above. Path Computation Elements (PCE) proposed by IETF designs suitable network architecture that aiming at compute the QoS based paths for traffic transportation through intra- and inter...

  19. 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...

  20. Tobacco Control Research, Dissemination and Networking in ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Tobacco Control Research, Dissemination and Networking in Lebanon. The Tobacco Control Research Group (TCRG), University of Beirut (AUB), is a multidisciplinary team of professionals from the health sciences, medicine, chemistry and engineering departments. The Group was established in 1999 with IDRC support ...

  1. Neural network topology design for nonlinear control

    Science.gov (United States)

    Haecker, Jens; Rudolph, Stephan

    2001-03-01

    Neural networks, especially in nonlinear system identification and control applications, are typically considered to be black-boxes which are difficult to analyze and understand mathematically. Due to this reason, an in- depth mathematical analysis offering insight into the different neural network transformation layers based on a theoretical transformation scheme is desired, but up to now neither available nor known. In previous works it has been shown how proven engineering methods such as dimensional analysis and the Laplace transform may be used to construct a neural controller topology for time-invariant systems. Using the knowledge of neural correspondences of these two classical methods, the internal nodes of the network could also be successfully interpreted after training. As further extension to these works, the paper describes the latest of a theoretical interpretation framework describing the neural network transformation sequences in nonlinear system identification and control. This can be achieved By incorporation of the method of exact input-output linearization in the above mentioned two transform sequences of dimensional analysis and the Laplace transformation. Based on these three theoretical considerations neural network topologies may be designed in special situations by pure translation in the sense of a structural compilation of the known classical solutions into their correspondent neural topology. Based on known exemplary results, the paper synthesizes the proposed approach into the visionary goals of a structural compiler for neural networks. This structural compiler for neural networks is intended to automatically convert classical control formulations into their equivalent neural network structure based on the principles of equivalence between formula and operator, and operator and structure which are discussed in detail in this work.

  2. Somatic surveillance: corporeal control through information networks

    OpenAIRE

    Monahan, Torin; Wall, Tyler

    2007-01-01

    Somatic surveillance is the increasingly invasive technological monitoring of and intervention into body functions. Within this type of surveillance regime, bodies are recast as nodes on vast information networks, enabling corporeal control through remote network commands, automated responses, or self-management practices. In this paper, we investigate three developments in somatic surveillance: nanotechnology systems for soldiers on the battlefield, commercial body-monitoring systems for hea...

  3. Social Network Privacy via Evolving Access Control

    Science.gov (United States)

    di Crescenzo, Giovanni; Lipton, Richard J.

    We study the problem of limiting privacy loss due to data shared in a social network, where the basic underlying assumptions are that users are interested in sharing data and cannot be assumed to constantly follow appropriate privacy policies. Note that if these two assumptions do not hold, social network privacy is theoretically very easy to achieve; for instance, via some form of access control and confidentiality transformation on the data.

  4. Decentralized control of ecological and biological networks through Evolutionary Network Control

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2016-09-01

    Full Text Available Evolutionary Network Control (ENC has been recently introduced to allow the control of any kind of ecological and biological networks, with an arbitrary number of nodes and links, acting from inside and/or outside. To date, ENC has been applied using a centralized approach where an arbitrary number of network nodes and links could be tamed. This approach has shown to be effective in the control of ecological and biological networks. However a decentralized control, where only one node and the correspondent input/output links are controlled, could be more economic from a computational viewpoint, in particular when the network is very large (i.e. big data. In this view, ENC is upgraded here to realize the decentralized control of ecological and biological nets.

  5. Scheduled Controller Design of Congestion Control Considering Network Resource Constraints

    Science.gov (United States)

    Naito, Hiroyuki; Azuma, Takehito; Fujita, Masayuki

    In this paper, we consider a dynamical model of computer networks and derive a synthesis method for congestion control. First, we show a model of TCP/AQM (Transmission Control Protocol/Active Queue Management) as a dynamical model of computer networks. The dynamical model of TCP/AQM networks consists of models of TCP window size, queue length and AQM mechanisms. Second, we propose to describe the dynamical model of TCP/AQM networks as linear systems with self-scheduling parameters, which also depend on information delay. Here we focus on the constraints on the maximum queue length and TCP window-size, which are the network resources in TCP/AQM networks. We derive TCP/AQM networks as the LPV system (linear parameter varying system) with information delay and self-scheduling parameter. We design a memoryless state feedback controller of the LPV system based on a gain-scheduling method. Finally, the effectiveness of the proposed method is evaluated by using MATLAB and the well-known ns-2 (Network Simulator Ver.2) simulator.

  6. [The network of official medicines control laboratories].

    Science.gov (United States)

    Buchheit, K-H; Wanko, R

    2014-10-01

    Licensing, control and surveillance by competent authorities is the basis for ensuring efficacy, safety and quality of medicines in Europe. The control of the quality of medicines by national control laboratories, known as Official Medicines Control Laboratories (OMCLs) is an essential step in this process; it encompasses controls before and after granting a marketing authorisation. For certain groups of biomedical medicines (vaccines for human and veterinary use, medicines derived from human plasma) even each batch is controlled before it can be placed on the market. As single OMCLs would not be able to cope with their task, given the large number and diversity of medicines, in 1994 the OMCL network was founded upon initiative of the European Directorate for the Quality of Medicines & HealthCare, in close collaboration with the Commission of the European Union. Currently 68 OMCLs from 39 countries are part of the network. Prerequisite for the smooth operation of the OMCL network is the harmonisation of the quality management system of the individual OMCLs, based on the ISO 17025 standard, internal guidelines and the European Pharmacopoeia. Compliance with these standards is checked through regular audits, thus creating the basis for mutual recognition of test results. The collaboration in the OMCL network for the surveillance of the medicines market, the official control authority batch release and the fight against counterfeiting and illegal medicines enables OMCLs to keep pace with the developments in the field of medicines and to control the broad spectrum of medicines. In the 20 years since its start, the OMCL network has become a European success story.

  7. NONLINEAR SYSTEM MODELING USING SINGLE NEURON CASCADED NEURAL NETWORK FOR REAL-TIME APPLICATIONS

    Directory of Open Access Journals (Sweden)

    S. Himavathi

    2012-04-01

    Full Text Available Neural Networks (NN have proved its efficacy for nonlinear system modeling. NN based controllers and estimators for nonlinear systems provide promising alternatives to the conventional counterpart. However, NN models have to meet the stringent requirements on execution time for its effective use in real time applications. This requires the NN model to be structurally compact and computationally less complex. In this paper a parametric method of analysis is adopted to determine the compact and faster NN model among various neural network architectures. This work proves through analysis and examples that the Single Neuron Cascaded (SNC architecture is distinct in providing compact and simpler models requiring lower execution time. The unique structural growth of SNC architecture enables automation in design. The SNC Network is shown to combine the advantages of both single and multilayer neural network architectures. Extensive analysis on selected architectures and their models for four benchmark nonlinear theoretical plants and a practical application are tested. A performance comparison of the NN models is presented to demonstrate the superiority of the single neuron cascaded architecture for online real time applications.

  8. 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.

  9. Controllable Buoys and Networked Buoy Systems

    Science.gov (United States)

    Davoodi, Faranak (Inventor); Davoudi, Farhooman (Inventor)

    2017-01-01

    Buoyant sensor networks are described, comprising floating buoys with sensors and energy harvesting capabilities. The buoys can control their buoyancy and motion, and can organize communication in a distributed fashion. Some buoys may have tethered underwater vehicles with a smart spooling system that allows the vehicles to dive deep underwater while remaining in communication and connection with the buoys.

  10. Distributed control network for optogenetic experiments

    Science.gov (United States)

    Kasprowicz, G.; Juszczyk, B.; Mankiewicz, L.

    2014-11-01

    Nowadays optogenetic experiments are constructed to examine social behavioural relations in groups of animals. A novel concept of implantable device with distributed control network and advanced positioning capabilities is proposed. It is based on wireless energy transfer technology, micro-power radio interface and advanced signal processing.

  11. 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

  12. 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.

  13. Plug & Play Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Jensen, Tom Nørgaard

    2012-01-01

    Process Control research program, which the work presented here is a part of. An industrial case study involving a large-scale hydraulic network with non-linear dynamics is studied. The hydraulic network underlies a district heating system, which provides heating water to a number of end-users in a city...... district. The case study considers a novel approach to the design of district heating systems in which the diameter of the pipes used in the system is reduced in order to reduce the heat losses in the system, thereby making it profitable to provide district heating to areas with low energy demands. The new...

  14. Flexible body control using neural networks

    Science.gov (United States)

    Mccullough, Claire L.

    1992-01-01

    Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

  15. Evolution of Controllability in Interbank Networks

    Science.gov (United States)

    Delpini, Danilo; Battiston, Stefano; Riccaboni, Massimo; Gabbi, Giampaolo; Pammolli, Fabio; Caldarelli, Guido

    2013-04-01

    The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected ``hub'' institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.

  16. Networked control of microgrid system of systems

    Science.gov (United States)

    Mahmoud, Magdi S.; Rahman, Mohamed Saif Ur; AL-Sunni, Fouad M.

    2016-08-01

    The microgrid has made its mark in distributed generation and has attracted widespread research. However, microgrid is a complex system which needs to be viewed from an intelligent system of systems perspective. In this paper, a network control system of systems is designed for the islanded microgrid system consisting of three distributed generation units as three subsystems supplying a load. The controller stabilises the microgrid system in the presence of communication infractions such as packet dropouts and delays. Simulation results are included to elucidate the effectiveness of the proposed control strategy.

  17. Neural network controller for underwater work ROV. Suichu sagyoyo ROV no neural network controller

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Y.; Kidoshi, H.; Arahata, M.; Shoji, K.; Takahashi, Y. (Ishikawajima-Harima Heavy Industries, Co. Ltd., Tokyo (Japan))

    1993-07-01

    The previous underwater work ROV (remotely operated vehicle) has been controlled manually because its dynamic properties are changeable underwater. Ishikawajima-Harima Heavy Industries (IHI) has applied a neural network to an adaptive controller for the ROV. This paper describes objectives of the research, design of control logic, and tank experiments on a model ROV. For the neural network, manual operation was used to provide the initial learning data for the neural network in order to initialize control parameters for optimization. The model ROV was designed to achieve and maintain constant depth in normal operation. As a consequence of the tank experiments, it was demonstrated that the controller can acquire skill of operators, can further improve the acquired skill of operators, and can construct an automatic control system autonomically even if any dynamic properties are not known. 6 refs., 8 figs.

  18. Improving Control Mechanism at Routers in TCP/IP Network

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2014-09-01

    Full Text Available The existing control mechanisms at the network nodes have a good active and very effective at each local router, but they do not still strong enough to control nonlinear and dynamical behaviour of the network. Therefore, the control system requirements must be designed to be flexible to fully grasp the important status information of the variation and intelligent control methods to control network congestion in nonlinear network. To solve this problem, we propose a solution combined fuzzy reasoning with neural network control put on active queue management mechanisms at the network nodes.

  19. Call Admission Control in Mobile Cellular Networks

    CERN Document Server

    Ghosh, Sanchita

    2013-01-01

    Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently.      CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators.  The second approach is concerned with formulation of CAC ...

  20. Coordinated Voltage Control of Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Xie Jiang

    2016-01-01

    Full Text Available This paper presents a centralized coordinated voltage control method for active distribution network to solve off-limit problem of voltage after incorporation of distributed generation (DG. The proposed method consists of two parts, it coordinated primal-dual interior point method-based voltage regulation schemes of DG reactive powers and capacitors with centralized on-load tap changer (OLTC controlling method which utilizes system’s maximum and minimum voltages, to improve the qualified rate of voltage and reduce the operation numbers of OLTC. The proposed coordination has considered the cost of capacitors. The method is tested using a radial edited IEEE-33 nodes distribution network which is modelled using MATLAB.

  1. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  2. Stochastic modelling and control of communication networks

    OpenAIRE

    Zuraniewski, P.W.

    2011-01-01

    The unprecedented growth of the Information Technologies sector observed within the past years creates an excellent opportunity to conduct new, exciting and interdisciplinary research. Increasing complexity of the communication networks calls for incorporating rigorously developed and reliable methods for traffic control and management. Mathematics may offer extremely valuable tools to achieve these goals but transforming an engineering problem into the mathematical one requires a good unders...

  3. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  4. 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.

  5. Analysis and design of networked control systems

    CERN Document Server

    You, Keyou; Xie, Lihua

    2015-01-01

    This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: ·         minimum data rate for stabilization of linear systems over noisy channels; ·         minimum network requirement for stabilization of linear systems over fading channels; and ·         stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are de...

  6. neural network based load frequency control for restructuring power

    African Journals Online (AJOL)

    2012-03-01

    Mar 1, 2012 ... Abstract. In this study, 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. The comparison between a conventional Proportional Integral (PI) controller and the proposed artificial neural networks ...

  7. Efficient Access Control in Multimedia Social Networks

    Science.gov (United States)

    Sachan, Amit; Emmanuel, Sabu

    Multimedia social networks (MMSNs) have provided a convenient way to share multimedia contents such as images, videos, blogs, etc. Contents shared by a person can be easily accessed by anybody else over the Internet. However, due to various privacy, security, and legal concerns people often want to selectively share the contents only with their friends, family, colleagues, etc. Access control mechanisms play an important role in this situation. With access control mechanisms one can decide the persons who can access a shared content and who cannot. But continuously growing content uploads and accesses, fine grained access control requirements (e.g. different access control parameters for different parts in a picture), and specific access control requirements for multimedia contents can make the time complexity of access control to be very large. So, it is important to study an efficient access control mechanism suitable for MMSNs. In this chapter we present an efficient bit-vector transform based access control mechanism for MMSNs. The proposed approach is also compatible with other requirements of MMSNs, such as access rights modification, content deletion, etc. Mathematical analysis and experimental results show the effectiveness and efficiency of our proposed approach.

  8. Identification and Position Control of Marine Helm using Artificial Neural Network Neural Network

    Directory of Open Access Journals (Sweden)

    Hui ZHU

    2008-02-01

    Full Text Available If nonlinearities such as saturation of the amplifier gain and motor torque, gear backlash, and shaft compliances- just to name a few - are considered in the position control system of marine helm, traditional control methods are no longer sufficient to be used to improve the performance of the system. In this paper an alternative approach to traditional control methods - a neural network reference controller - is proposed to establish an adaptive control of the position of the marine helm to achieve the controlled variable at the command position. This neural network controller comprises of two neural networks. One is the plant model network used to identify the nonlinear system and the other the controller network used to control the output to follow the reference model. The experimental results demonstrate that this adaptive neural network reference controller has much better control performance than is obtained with traditional controllers.

  9. Neural Network Control of Asymmetrical Multilevel Converters

    Directory of Open Access Journals (Sweden)

    Patrice WIRA

    2009-12-01

    Full Text Available This paper proposes a neural implementation of a harmonic eliminationstrategy (HES to control a Uniform Step Asymmetrical Multilevel Inverter(USAMI. The mapping between the modulation rate and the requiredswitching angles is learned and approximated with a Multi-Layer Perceptron(MLP neural network. After learning, appropriate switching angles can bedetermined with the neural network leading to a low-computational-costneural controller which is well suited for real-time applications. Thistechnique can be applied to multilevel inverters with any number of levels. Asan example, a nine-level inverter and an eleven-level inverter are consideredand the optimum switching angles are calculated on-line. Comparisons to thewell-known sinusoidal pulse-width modulation (SPWM have been carriedout in order to evaluate the performance of the proposed approach. Simulationresults demonstrate the technical advantages of the proposed neuralimplementation over the conventional method (SPWM in eliminatingharmonics while controlling a nine-level and eleven-level USAMI. Thisneural approach is applied for the supply of an asynchronous machine andresults show that it ensures a highest quality torque by efficiently cancelingthe harmonics generated by the inverters.

  10. Further Evaluation of Delta Opioid Agonists as Candidate Adjuncts to Mu Opioid Analgesics: A Comparison of Interactions between Fentanyl and either Ketamine or the Delta Agonist SNC162 in Rhesus Monkeys

    Science.gov (United States)

    Banks, Matthew L.; Folk, John E.; Rice, Kenner C.; Negus, S. Stevens

    2010-01-01

    Mu-opioid receptor agonists such as fentanyl are effective analgesics, but their clinical use is limited by untoward effects. Adjunct medications may improve the effectiveness and/or safety of opioid analgesics. This study compared interactions between fentanyl and either the noncompetitive N-methyl-D-aspartate (NMDA) glutamate receptor antagonist ketamine or the delta-opioid receptor agonist SNC162 [(+)-4-[(alphaR)-alpha-[(2S,5R)-2,5-dimethyl-4-(2-propenyl)-1-piperazinyl]-(3-phenyl)methyl]-N,N-diethylbenzamide] in two behavioral assays in rhesus monkeys. An assay of thermal nociception evaluated tail-withdrawal latencies from water heated to 50 and 54°C. An assay of schedule-controlled responding evaluated response rates maintained under a fixed-ratio 30 schedule of food presentation. Effects of each drug alone and of three mixtures of ketamine +fentanyl (22:1, 65:1, 195:1 ketamine/fentanyl) or SNC162+fentanyl (59:1, 176:1, 528:1 SNC162/fentanyl) were evaluated in each assay. All drugs and mixtures dose-dependently decreased rates of food-maintained responding, and drug proportions in the mixtures were based on relative potencies in this assay. Ketamine and SNC162 were inactive in the assay of thermal antinociception, but fentanyl and all mixtures produced dose-dependent antinociception. Drug interactions were evaluated using dose-addition and dose-ratio analysis. Dose-addition analysis revealed that interactions for all ketamine/fentanyl mixtures were additive in both assays. SNC162/fentanyl interactions were usually additive, but one mixture (176:1) produced synergistic antinociception at 50°C. Dose-ratio analysis indicated that ketamine failed to improve the relative potency of fentanyl to produce antinociception vs. rate suppression, whereas two SNC162/fentanyl mixtures (59:1 and 176:1) increased the relative potency of fentanyl to produce antinociception. These results suggest that delta agonists may produce more selective enhancement than ketamine of mu

  11. Genesis of the Mars Pathfinder ''sulfur-free'' rock from SNC parental liquids

    Science.gov (United States)

    Minitti, M. E.; Rutherford, M. J.

    2000-07-01

    Combined rock and soil measurements from the Mars Pathfinder APXS established the composition of the "sulfur-free" rock whose chemical characteristics suggest it is an igneous andesite. We experimentally investigated the formation of the sulfur-free rock through equilibrium crystallization of a primitive SNC basalt under hydrous (1.0-1.5 wt% H 2O) and dry conditions at the QFM oxygen buffer. The experiments determined crystallization sequences and liquid lines of descent for a basalt with a high-FeO, low-Al 2O 3 (relative to tholeiitic magma) composition characteristic of SNC magmas. In the hydrous experiments, the crystallization sequence between ˜1090°C and 950°C is pigeonite → sub-calcic augite → Ti-magnetite → plagioclase → ilmenite + fayalite. The crystallization sequence of dry experiments between ˜1130°C and 980°C resembles that of the hydrous experiments except for the appearance of plagioclase and fayalite before Ti-magnetite. The liquid lines of descent reveal that fractionation of a hydrous, primitive SNC basalt can produce a melt equivalent to the sulfur-free rock composition whereas fractionation of a dry SNC basalt fails to produce such a melt. The effect of water on the timing and amount of phenocryst growth, particularly Fe-Ti oxide crystallization, is critical in achieving the observed SiO 2 enrichment in the hydrous experiments. The hydrous basalt reaches andesitic residual melt compositions at ˜40% crystallization and the dry basalt eventually produces a minimum andesitic composition melt at ˜90% crystallization. The low degree of crystallization necessary to reach andesitic residual melt compositions in the hydrous experiments would greatly facilitate the extraction of this andesitic melt (and more evolved melts) from associated crystals. Further experiments at other oxygen fugacities reveal that oxidizing fO 2's (MnO-Mn 3O 4) encourage silicic melt formation by enhancing oxide crystallization; conversely, reducing fO 2's (GCH

  12. 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.

  13. 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.

  14. 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.

  15. An Efficient Congestion Control Protocol for Wired/Wireless Networks

    OpenAIRE

    Hanaa Torkey; Gamal ATTIYA; Ahmed Abdel Nabi

    2014-01-01

    Recently, wide spectrum of heterogeneous wireless access networks integrate with high speed wired networks to deliver Internet services. End-to-end service delivery with satisfactory quality is challenging issue in such network architectures. Although the Internet transport control protocol (TCP) addresses such challenge, it has poor performance with high speed wired networks (i.e. high bandwidth-delay product). Moreover, it behaves badly with wireless access networks (i.e. misinterpretation ...

  16. Intelligent Joint Admission Control for Next Generation Wireless Networks

    OpenAIRE

    Abdulqader M. Mohsen; Al-Akwaa, Fadhl M.; Mohammed M. Alkhawlani

    2012-01-01

    The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initia...

  17. 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...

  18. 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....

  19. Network resource control for grid workflow management systems

    NARCIS (Netherlands)

    Strijkers, R.J.; Cristea, M.; Korkhov, V.; Marchal, D.; Belloum, A.; Laat, C.de; Meijer, R.J.

    2010-01-01

    Grid workflow management systems automate the orchestration of scientific applications with large computational and data processing needs, but lack control over network resources. Consequently, the management system cannot prevent multiple communication intensive applications to compete for network

  20. Control and estimation methods over communication networks

    CERN Document Server

    Mahmoud, Magdi S

    2014-01-01

    This book provides a rigorous framework in which to study problems in the analysis, stability and design of networked control systems. Four dominant sources of difficulty are considered: packet dropouts, communication bandwidth constraints, parametric uncertainty, and time delays. Past methods and results are reviewed from a contemporary perspective, present trends are examined, and future possibilities proposed. Emphasis is placed on robust and reliable design methods. New control strategies for improving the efficiency of sensor data processing and reducing associated time delay are presented. The coverage provided features: ·        an overall assessment of recent and current fault-tolerant control algorithms; ·        treatment of several issues arising at the junction of control and communications; ·        key concepts followed by their proofs and efficient computational methods for their implementation; and ·        simulation examples (including TrueTime simulations) to...

  1. Controllability of giant connected components in a directed network

    Science.gov (United States)

    Liu, Xueming; Pan, Linqiang; Stanley, H. Eugene; Gao, Jianxi

    2017-04-01

    When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p =pm . We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree and that it is determined by pm . In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

  2. Fault Detection for Quantized Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Wei-Wei Che

    2013-01-01

    Full Text Available The fault detection problem in the finite frequency domain for networked control systems with signal quantization is considered. With the logarithmic quantizer consideration, a quantized fault detection observer is designed by employing a performance index which is used to increase the fault sensitivity in finite frequency domain. The quantized measurement signals are dealt with by utilizing the sector bound method, in which the quantization error is treated as sector-bounded uncertainty. By using the Kalman-Yakubovich-Popov (GKYP Lemma, an iterative LMI-based optimization algorithm is developed for designing the quantized fault detection observer. And a numerical example is given to illustrate the effectiveness of the proposed method.

  3. Urgent epidemic control mechanism for aviation networks

    KAUST Repository

    Peng, Chengbin

    2011-01-01

    In the current century, the highly developed transportation system can not only boost the economy, but also greatly accelerate the spreading of epidemics. While some epidemic diseases may infect quite a number of people ahead of our awareness, the health care resources such as vaccines and the medical staff are usually locally or even globally insufficient. In this research, with the network of major aviation routes as an example, we present a method to determine the optimal locations to allocate the medical service in order to minimize the impact of the infectious disease with limited resources. Specifically, we demonstrate that when the medical resources are insufficient, we should concentrate our efforts on the travelers with the objective of effectively controlling the spreading rate of the epidemic diseases. © 2011 Springer-Verlag Berlin Heidelberg.

  4. Application framework for programmable network control

    NARCIS (Netherlands)

    Strijkers, R.; Cristea, M.; de Laat, C.; Meijer, R.; Clemm, A.; Wolter, R.

    2011-01-01

    We present a framework that enables application developers to create complex and application specific network services. The essence of our approach is to utilize programmable network elements to create a software representation of network elements in the application. We show that the typical pattern

  5. MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage

    Science.gov (United States)

    2015-10-19

    Design, Implementation and Evaluation of Congestion Control for Multipath TCP ,” in Proc. of USENIX Conference on Networked Systems Design and...MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage Scott Pudlewski, Brooke Shrader, Laura Herrera, Nathaniel M. Jones...queue-based (MQCC) congestion control algorithm. MQCC uses average buffer occupancy as a measure of the congestion in a network (as opposed to packet

  6. Near-Minimal Node Control of Networked Evolutionary Games

    NARCIS (Netherlands)

    Riehl, James Robert; Cao, Ming

    2014-01-01

    We investigate a problem related to the controllability of networked evolutionary games, first presenting an algorithm that computes a near-minimal set of nodes to drive all nodes in a tree network to a desired strategy, and then briefly discussing an algorithm that works for arbitrary networks

  7. CFO finance network centrality, errors and internal control material weaknessess

    NARCIS (Netherlands)

    Schabus, M.

    2015-01-01

    CFOs finance networks matter in determining certain accounting and reporting outcomes. Drawing on social network theory, this study shows that CFO centrality in a network of financial experts is inversely related to the occurrence of restatements due to errors and disclosure of internal control

  8. An improved method for network congestion control

    Science.gov (United States)

    Qiao, Xiaolin

    2013-03-01

    The rapid progress of the wireless network technology has great convenience on the people's life and work. However, because of its openness, the mobility of the terminal and the changing topology, the wireless network is more susceptible to security attacks. Authentication and key agreement is the base of the network security. The authentication and key agreement mechanism can prevent the unauthorized user from accessing the network, resist malicious network to deceive the lawful user, encrypt the session data by using the exchange key and provide the identification of the data origination. Based on characteristics of the wireless network, this paper proposed a key agreement protocol for wireless network. The authentication of protocol is based on Elliptic Curve Cryptosystems and Diffie-Hellman.

  9. 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 ...

  10. Implementing controlled-unitary operations over the butterfly network

    Science.gov (United States)

    Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.; Murao, Mio

    2014-12-01

    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.

  11. 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.

  12. Adaptive bridge control strategy for opinion evolution on social networks.

    Science.gov (United States)

    Qian, Cheng; Cao, Jinde; Lu, Jianquan; Kurths, Jürgen

    2011-06-01

    In this paper, we present an efficient opinion control strategy for complex networks, in particular, for social networks. The proposed adaptive bridge control (ABC) strategy calls for controlling a special kind of nodes named bridge and requires no knowledge of the node degrees or any other global or local knowledge, which are necessary for some other immunization strategies including targeted immunization and acquaintance immunization. We study the efficiency of the proposed ABC strategy on random networks, small-world networks, scale-free networks, and the random networks adjusted by the edge exchanging method. Our results show that the proposed ABC strategy is efficient for all of these four kinds of networks. Through an adjusting clustering coefficient by the edge exchanging method, it is found out that the efficiency of our ABC strategy is closely related with the clustering coefficient. The main contributions of this paper can be listed as follows: (1) A new high-order social network is proposed to describe opinion dynamic. (2) An algorithm, which does not require the knowledge of the nodes' degree and other global∕local network structure information, is proposed to control the "bridges" more accurately and further control the opinion dynamics of the social networks. The efficiency of our ABC strategy is illustrated by numerical examples. (3) The numerical results indicate that our ABC strategy is more efficient for networks with higher clustering coefficient.

  13. Arabidopsis snc2-1D Activates Receptor-Like Protein-Mediated Immunity Transduced through WRKY70[C][W

    Science.gov (United States)

    Zhang, Yaxi; Yang, Yuanai; Fang, Bin; Gannon, Patrick; Ding, Pingtao; Li, Xin; Zhang, Yuelin

    2010-01-01

    Plant immune receptors belonging to the receptor-like protein (RLP) family contain extracellular leucine-rich repeats (LRRs) and a short cytoplasmic tail linked by a single transmembrane motif. Here, we report the identification of snc2-1D (for suppressor of npr1-1, constitutive 2), a semidominant Arabidopsis thaliana mutant with constitutively activated defense responses. Map-based cloning of snc2-1D showed that it encodes an RLP. The point mutation in snc2-1D leads to substitution of the second Gly for Arg in the conserved GXXXG motif of the transmembrane helix, suggesting that this residue is important for negative regulation of the protein. Epistasis analysis revealed that the snc2-1D mutant phenotype is not affected by mutations in genes known to be required for the nucleotide binding (NB)-LRR Resistance (R) protein signaling. A suppressor screen of snc2-1D was performed, and map-based cloning of one suppressor revealed that mutations in WRKY70 suppress the constitutive defense responses in snc2-1D, suggesting that WRKY70 functions downstream of snc2-1D. The identification of snc2-1D provides us with a unique system for genetic analysis of resistance pathways downstream of RLPs, which may be distinct from those downstream of NB-LRR type R proteins. PMID:20841424

  14. QTL list: snc3.1 [PGDBj Registered plant list, Marker list, QTL list, Plant DB link and Genome analysis methods[Archive

    Lifescience Database Archive (English)

    Full Text Available QT77161 Solanum lycopersicum Solanaceae snc3.1 Logarithmic Na+ concentrations in s...tems under saliniy conditions logarithmic SNC (the Na+ concentrations in stems) 3 ... Chr03 11.91 10 ... 10.1007/s00122-008-0720-8 18251001

  15. QTL list: snc6.1 [PGDBj Registered plant list, Marker list, QTL list, Plant DB link and Genome analysis methods[Archive

    Lifescience Database Archive (English)

    Full Text Available QT77162 Solanum lycopersicum Solanaceae snc6.1 Logarithmic Na+ concentrations in s...tems under saliniy conditions logarithmic SNC (the Na+ concentrations in stems) 3 ... Chr06 21.67 9.44 ... 10.1007/s00122-008-0720-8 18251001

  16. QTL list: snc7.1 [PGDBj Registered plant list, Marker list, QTL list, Plant DB link and Genome analysis methods[Archive

    Lifescience Database Archive (English)

    Full Text Available QT77163 Solanum lycopersicum Solanaceae snc7.1 Logarithmic Na+ concentrations in s...tems under saliniy conditions logarithmic SNC (the Na+ concentrations in stems) 3 ... Chr07 41.67 47.72 ... 10.1007/s00122-008-0720-8 18251001

  17. 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.

  18. Adaptive Dynamics, Control, and Extinction in Networked Populations

    Science.gov (United States)

    2015-07-09

    Adaptive Dynamics, Control, and Extinction in Networked Populations Ira B. Schwartz US Naval Research Laboratory Code 6792 Nonlinear System Dynamics...theory of large deviations to stochastic network extinction to predict extinction times. In particular, we use the theory to find the most probable...paths leading to extinction . We then apply the methodology to network models and discover how mean extinction times scale with network parameters in Erdos

  19. Dynamics of nonergodic ferromagnetic/antiferromagnetic ordering and magnetocalorics in antiperovskite Mn3SnC

    Science.gov (United States)

    Ćakır, Ö.; Cugini, F.; Solzi, M.; Priolkar, K.; Acet, M.; Farle, M.

    2017-07-01

    We investigated the time dependence of the magnetic configuration at the mixed magnetic magnetostructural transition in Mn3SnC . The nonergodic nature of the transition involves the stabilization of a final magnetic configuration that involves additional AF ordering which is not present when the transition is initiated and develops only in time. We show the presence of the nonergodicity over a time scale of about 1 hour by field and time-dependent magnetization studies. Two characteristic times related to the transition are observed. We also study the equilibrium thermodynamics under ergodic conditions by heat capacity studies and determine the entropy-change and the adiabatic temperature change around the transition. We find agreement between the indirect and direct methods in determining the adiabatic temperature change and discuss the influence of nonergodic properties on the magnetocaloric effects.

  20. Intelligent Control of Urban Road Networks: Algorithms, Systems and Communications

    Science.gov (United States)

    Smith, Mike

    This paper considers control in road networks. Using a simple example based on the well-known Braess network [1] the paper shows that reducing delay for traffic, assuming that the traffic distribution is fixed, may increase delay when travellers change their travel choices in light of changes in control settings and hence delays. It is shown that a similar effect occurs within signal controlled networks. In this case the effect appears at first sight to be much stronger: the overall capacity of a network may be substantially reduced by utilising standard responsive signal control algorithms. In seeking to reduce delays for existing flows, these policies do not allow properly for consequent routeing changes by travellers. Control methods for signal-controlled networks that do take proper account of the reactions of users are suggested; these require further research, development, and careful real-life trials.

  1. 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

    we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network......% 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...

  2. Gene networks controlling Arabidopsis thaliana flower development.

    Science.gov (United States)

    Ó'Maoiléidigh, Diarmuid Seosamh; Graciet, Emmanuelle; Wellmer, Frank

    2014-01-01

    The formation of flowers is one of the main models for studying the regulatory mechanisms that underlie plant development and evolution. Over the past three decades, extensive genetic and molecular analyses have led to the identification of a large number of key floral regulators and to detailed insights into how they control flower morphogenesis. In recent years, genome-wide approaches have been applied to obtaining a global view of the gene regulatory networks underlying flower formation. Furthermore, mathematical models have been developed that can simulate certain aspects of this process and drive further experimentation. Here, we review some of the main findings made in the field of Arabidopsis thaliana flower development, with an emphasis on recent advances. In particular, we discuss the activities of the floral organ identity factors, which are pivotal for the specification of the different types of floral organs, and explore the experimental avenues that may elucidate the molecular mechanisms and gene expression programs through which these master regulators of flower development act. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  3. 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.

  4. Deterministic learning enhanced neutral network control of unmanned helicopter

    Directory of Open Access Journals (Sweden)

    Yiming Jiang

    2016-11-01

    Full Text Available In this article, a neural network–based tracking controller is developed for an unmanned helicopter system with guaranteed global stability in the presence of uncertain system dynamics. Due to the coupling and modeling uncertainties of the helicopter systems, neutral networks approximation techniques are employed to compensate the unknown dynamics of each subsystem. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is also integrated into the control design, such that the resulted neural controller is always valid without any concern on either initial conditions or range of state variables. In addition, deterministic learning is applied to the neutral network learning control, such that the adaptive neutral networks are able to store the learned knowledge that could be reused to construct neutral network controller with improved control performance. Simulation studies are carried out on a helicopter model to illustrate the effectiveness of the proposed control design.

  5. Positive train control interoperability and networking research : final report.

    Science.gov (United States)

    2015-12-01

    This document describes the initial development of an ITC PTC Shared Network (IPSN), a hosted : environment to support the distribution, configuration management, and IT governance of Interoperable : Train Control (ITC) Positive Train Control (PTC) s...

  6. Smart Control of Energy Distribution Grids over Heterogeneous Communication Networks

    DEFF Research Database (Denmark)

    Schwefel, Hans-Peter; Silva, Nuno; Olsen, Rasmus Løvenstein

    2018-01-01

    Off-the shelf wireless communication technologies reduce infrastructure deployment costs and are thus attractive for distribution system control. Wireless communication however may lead to variable network performance. Hence the impact of this variability on overall distribution system control be...

  7. 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.

  8. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  9. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

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

    1999-01-01

    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...

  10. 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...

  11. 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

  12. Distributed Estimation and Control for Robotic Networks

    NARCIS (Netherlands)

    Simonetto, A.

    2012-01-01

    Mobile robots that communicate and cooperate to achieve a common task have been the subject of an increasing research interest in recent years. These possibly heterogeneous groups of robots communicate locally via a communication network and therefore are usually referred to as robotic networks.

  13. Projection learning algorithm for threshold - controlled neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Reznik, A.M.

    1995-03-01

    The projection learning algorithm proposed in [1, 2] and further developed in [3] substantially improves the efficiency of memorizing information and accelerates the learning process in neural networks. This algorithm is compatible with the completely connected neural network architecture (the Hopfield network [4]), but its application to other networks involves a number of difficulties. The main difficulties include constraints on interconnection structure and the need to eliminate the state uncertainty of latent neurons if such are present in the network. Despite the encouraging preliminary results of [3], further extension of the applications of the projection algorithm therefore remains problematic. In this paper, which is a continuation of the work begun in [3], we consider threshold-controlled neural networks. Networks of this type are quite common. They represent the receptor neuron layers in some neurocomputer designs. A similar structure is observed in the lower divisions of biological sensory systems [5]. In multilayer projection neural networks with lateral interconnections, the neuron layers or parts of these layers may also have the structure of a threshold-controlled completely connected network. Here the thresholds are the potentials delivered through the projection connections from other parts of the network. The extension of the projection algorithm to the class of threshold-controlled networks may accordingly prove to be useful both for extending its technical applications and for better understanding of the operation of the nervous system in living organisms.

  14. Design and Simulation Analysis for Integrated Vehicle Chassis-Network Control System Based on CAN Network

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2016-01-01

    Full Text Available Due to the different functions of the system used in the vehicle chassis control, the hierarchical control strategy also leads to many kinds of the network topology structure. According to the hierarchical control principle, this research puts forward the integrated control strategy of the chassis based on supervision mechanism. The purpose is to consider how the integrated control architecture affects the control performance of the system after the intervention of CAN network. Based on the principle of hierarchical control and fuzzy control, a fuzzy controller is designed, which is used to monitor and coordinate the ESP, AFS, and ARS. And the IVC system is constructed with the upper supervisory controller and three subcontrol systems on the Simulink platform. The network topology structure of IVC is proposed, and the IVC communication matrix based on CAN network communication is designed. With the common sensors and the subcontrollers as the CAN network independent nodes, the network induced delay and packet loss rate on the system control performance are studied by simulation. The results show that the simulation method can be used for designing the communication network of the vehicle.

  15. 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.

  16. Transient and permanent error control for networks-on-chip

    CERN Document Server

    Yu, Qiaoyan

    2012-01-01

    This book addresses reliability and energy efficiency of on-chip networks using a configurable error control coding (ECC) scheme for datalink-layer transient error management. The method can adjust both error detection and correction strengths at runtime by varying the number of redundant wires for parity-check bits. Methods are also presented to tackle joint transient and permanent error correction, exploiting the redundant resources already available on-chip. A parallel and flexible network simulator is also introduced, which facilitates examining the impact of various error control methods on network-on-chip performance. Includes a complete survey of error control methods for reliable networks-on-chip, evaluated for reliability, energy and performance metrics; Provides analysis of error control in various network-on-chip layers, as well as presentation of an innovative multi-layer error control coding technique; Presents state-of-the-art solutions to address simultaneously reliability, energy and performan...

  17. 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.

  18. Control Strategy on Worms Spread in Complex Networks

    Science.gov (United States)

    Xianmei, Fang

    First, a preliminary understanding of what is meant by complex network and its features, and network worm virus that understanding and analysis of the emergence and development of the worm, the worm to understand the current situation, focus on the worm propagation model (simple propagation model, Kermack-Mckendrick model, SIS model, two-factor model, BCM model - network worms against the model). Contact the characteristics of complex networks and the worm theory, detection and prevention of worms and an important node in the network-based control strategy (target immunity, virus containment) for a simple discussion.

  19. VNEC - A Virtual Network Experiment Controller

    Science.gov (United States)

    Gagnon, François; Dej, Tomas; Esfandiari, Babak

    This paper presents VNEC, a tool to specify and execute network experiments in a virtual environment. The user first formulates the network topology and then provides the tasks that should be performed by the computers together with their execution. Next, VNEC initializes the environment by powering up and configuring the virtual machines to match the desired network topology. Finally, commands are dispatched to the right virtual machines in the specified order. VNEC provides an environment for several types of research experiments such as virus propagation patterns and reactions of different targets against a given attack.

  20. Stochastic modelling and control of communication networks

    NARCIS (Netherlands)

    Zuraniewski, P.W.

    2011-01-01

    The unprecedented growth of the Information Technologies sector observed within the past years creates an excellent opportunity to conduct new, exciting and interdisciplinary research. Increasing complexity of the communication networks calls for incorporating rigorously developed and reliable

  1. Dynamics and control of diseases in networks with community structure.

    Directory of Open Access Journals (Sweden)

    Marcel Salathé

    2010-04-01

    Full Text Available The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc. depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.

  2. Performance evaluation of power control algorithms in wireless cellular networks

    Science.gov (United States)

    Temaneh-Nyah, C.; Iita, V.

    2014-10-01

    Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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...... Identification, Prediction, Simulation and Control of a dynamic, non-linear and noisy process. Further, the difficulties to control a practical non-linear laboratory process in a satisfactory way by using a traditional controller are overcomed by using a trained neural network to perform non-linear 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...

  7. Alterações no SNC e morfometria cerebelar de bovinos intoxicados experimentalmente por Solanum paniculatum

    Directory of Open Access Journals (Sweden)

    Rafael O. Rego

    2012-11-01

    Full Text Available Algumas espécies de Solanum causam intoxicações em ruminantes caracterizadas clinicamente por desordens cerebelares e microscopicamente como doença do depósito lisossomal. Não há lesões de necropsia específicas e microscopicamente ocorrem vacuolização e perda de neurônios de Purkinje. Por ser Solanum paniculatum a espécie de ocorrência na região Nordeste, sendo responsável pelos surtos de intoxicação espontânea descrito no Estado de Pernambuco foi realizado um delineamento experimental para caracterizar o quadro clínico-patológico da intoxicação. Foram usados cinco bovinos, sendo quatro no grupo experimental (GE e um animal no controle (GC, de seis meses de idade, sem raça definida, com peso de 120 Kg, mantidos em baias durante cinco meses na Clínica de Bovinos de Garanhuns/UFRPE. Os animais receberam a planta, colhida nas propriedades em que ocorreram os surtos naturais, na dosagem de 5g/kg/PV/dia da planta dessecada misturada na ração por ingestão natural. Semanalmente realizou-se o Head Raising Test para determinar os sinais cerebelares e quando positivo os animais foram submetidos à colheita de sangue e do líquido céfalo-raquidiano e em seguida foi feito à eutanásia. O SNC e a rete mirabile foram fixados em formol a 10% tamponado, processados rotineiramente e corados pela hematoxilina e eosina para avaliação histopatológica. Foi realizada análise morfométrica das lesões cerebelares. Para avaliação dos resultados laboratoriais utilizou-se análise descritiva e em relação à morfometria, empregou-se o teste T de Student (p<0.05 na contagem de células de Purkinje e para a espessura da camada molecular do cerebelo o teste de Mann Whitney, com nível de 5% de significância. Três animais apresentaram sinais de intoxicação com tempo em média de 90 dias e um com 155 dias. Os sinais clínicos observados foram ataques convulsivos transitórios, e distúrbios do equilíbrio. Na necropsia não foram

  8. Operational predictive optimal control of Barcelona water transport network

    OpenAIRE

    Pascual, J.; Romera, J.; Puig, V.; Cembrano, G.; Creus, R.; Minoves, M.

    2013-01-01

    This paper describes the application of model-based predictive control (MPC) techniques to the supervisory flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC is used to generate flow control strategies (set-points for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, safety storage volumes in the network and smoothness...

  9. 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.

  10. 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... control balances the number of links utilized to achieve fewer collisions while maintaining robust network connectivity. In this work, we discuss the

  11. IDENTIFICATION AND CONTROL OF AN ASYNCHRONOUS MACHINE USING NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    A ZERGAOUI

    2000-06-01

    Full Text Available In this work, we present the application of artificial neural networks to the identification and control of the asynchronous motor, which is a complex nonlinear system with variable internal dynamics.  We show that neural networks can be applied to control the stator currents of the induction motor.  The results of the different simulations are presented to evaluate the performance of the neural controller proposed.

  12. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  13. AUTOMATIC CONTROL OF INTELLECTUAL RIGHTS IN THE GLOBAL COMPUTER NETWORKS

    OpenAIRE

    Anatoly P. Yakimaho; Victoriya V. Bessarabova

    2013-01-01

    The problems of use of subjects of intellectual property in the global computer networks are stated. The main attention is focused on the ways of problems solutions arising during the work in computer networks. Legal problems of information society are considered. The analysis of global computer networks as places for the organization of collective management by copyrights in the world scale is carried out. Issues of creation of a system of automatic control of property rights of authors and ...

  14. Mission-Aware Medium Access Control in Random Access Networks

    OpenAIRE

    Park, Jaeok; Van Der Schaar, Mihaela

    2009-01-01

    We study mission-critical networking in wireless communication networks, where network users are subject to critical events such as emergencies and crises. If a critical event occurs to a user, the user needs to send necessary information for help as early as possible. However, most existing medium access control (MAC) protocols are not adequate to meet the urgent need for information transmission by users in a critical situation. In this paer, we propose a novel class of MAC protocols that u...

  15. Resource Allocation and Cross Layer Control in Wireless Networks

    Science.gov (United States)

    2006-08-25

    Modiano , and J. Tsitsiklis, �Optimal energy allocation and admis- sion control for communication satellites,�IEEE Transactions on Networking, vol. 11...E. Modiano , �Improving delay in ad-hoc mobile networks via redundant packet transfers,�in Proceedings of Conference on Information Sciences and...M. J. Neely, E. Modiano , and C.-P. Li, �Fairness and optimal stochastic con- trol for heterogeneous networks,�in Proceedings of IEEE INFOCOM, Miami

  16. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  17. 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...

  18. Input graph: the hidden geometry in controlling complex networks

    Science.gov (United States)

    Zhang, Xizhe; Lv, Tianyang; Pu, Yuanyuan

    2016-11-01

    The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input nodes? Here we introduce input graph, a simple geometry that reveals the complex relationship between all control schemes and input nodes. We prove that the node adjacent to an input node in the input graph will appear in another control scheme, and the connected nodes in input graph have the same type in control, which they are either all possible input nodes or not. Furthermore, we find that the giant components emerge in the input graphs of many real networks, which provides a clear topological explanation of bifurcation phenomenon emerging in dense networks and promotes us to design an efficient method to alter the node type in control. The findings provide an insight into control principles of complex networks and offer a general mechanism to design a suitable control scheme for different purposes.

  19. 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.

  20. 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.

  1. Analysis of Basic Transmission Networks for Integrated Ship Control Systems

    DEFF Research Database (Denmark)

    Hansen, T.N.; Granum-Jensen, M.

    1993-01-01

    Description of a computer network for Integrated Ship Control Systems which is going to be developed as part of an EC-project. Today equipment of different make are not able to communicate with each other because most often each supplier of ISC systems has got their own proprietary network.....

  2. Analysis and control of flows in pressurized hydraulic networks

    NARCIS (Netherlands)

    Gupta, R.K.

    2006-01-01

    Analysis, design and flow control problems in pressurized hydraulic networks such as water transmission and distribution systems consisting of pipes and other appurtenant components such as reservoirs, pumps, valves and surge devices are dealt with from the prospective of network synthesis aiming at

  3. Distributed control of networked Lur’e systems

    NARCIS (Netherlands)

    Zhang, Fan

    2015-01-01

    In this thesis we systematically study distributed control of networked Lur'e systems, specifically, robust synchronization problems and cooperative robust output regulation problems. In such nonlinear multi-agent networks, the model of each agent dynamics is taken as a Lur'e system that consists of

  4. 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.

  5. Public authority control strategy for opinion evolution in social networks

    Science.gov (United States)

    Chen, Xi; Xiong, Xi; Zhang, Minghong; Li, Wei

    2016-08-01

    This paper addresses the need to deal with and control public opinion and rumors. Existing strategies to control public opinion include degree, random, and adaptive bridge control strategies. In this paper, we use the HK model to present a public opinion control strategy based on public authority (PA). This means utilizing the influence of expert or high authority individuals whose opinions we control to obtain the optimum effect in the shortest time possible and thus reach a consensus of public opinion. Public authority (PA) is only influenced by individuals' attributes (age, economic status, and education level) and not their degree distribution; hence, in this paper, we assume that PA complies with two types of public authority distribution (normal and power-law). According to the proposed control strategy, our experiment is based on random, degree, and public authority control strategies in three different social networks (small-world, scale-free, and random) and we compare and analyze the strategies in terms of convergence time (T), final number of controlled agents (C), and comprehensive efficiency (E). We find that different network topologies and the distribution of the PA in the network can influence the final controlling effect. While the effect of PA strategy differs in different network topology structures, all structures achieve comprehensive efficiency with any kind of public authority distribution in any network. Our findings are consistent with several current sociological phenomena and show that in the process of public opinion/rumor control, considerable attention should be paid to high authority individuals.

  6. Public authority control strategy for opinion evolution in social networks.

    Science.gov (United States)

    Chen, Xi; Xiong, Xi; Zhang, Minghong; Li, Wei

    2016-08-01

    This paper addresses the need to deal with and control public opinion and rumors. Existing strategies to control public opinion include degree, random, and adaptive bridge control strategies. In this paper, we use the HK model to present a public opinion control strategy based on public authority (PA). This means utilizing the influence of expert or high authority individuals whose opinions we control to obtain the optimum effect in the shortest time possible and thus reach a consensus of public opinion. Public authority (PA) is only influenced by individuals' attributes (age, economic status, and education level) and not their degree distribution; hence, in this paper, we assume that PA complies with two types of public authority distribution (normal and power-law). According to the proposed control strategy, our experiment is based on random, degree, and public authority control strategies in three different social networks (small-world, scale-free, and random) and we compare and analyze the strategies in terms of convergence time (T), final number of controlled agents (C), and comprehensive efficiency (E). We find that different network topologies and the distribution of the PA in the network can influence the final controlling effect. While the effect of PA strategy differs in different network topology structures, all structures achieve comprehensive efficiency with any kind of public authority distribution in any network. Our findings are consistent with several current sociological phenomena and show that in the process of public opinion/rumor control, considerable attention should be paid to high authority individuals.

  7. The Life-Changing Magic of Nonlinearity in Network Control

    Science.gov (United States)

    Cornelius, Sean

    The proper functioning and reliability of many man-made and natural systems is fundamentally tied to our ability to control them. Indeed, applications as diverse as ecosystem management, emergency response and cell reprogramming all, at their heart, require us to drive a system to--or keep it in--a desired state. This process is complicated by the nonlinear dynamics inherent to most real systems, which has traditionally been viewed as the principle obstacle to their control. In this talk, I will discuss two ways in which nonlinearity turns this view on its head, in fact representing an asset to the control of complex systems. First, I will show how nonlinearity in the form of multistability allows one to systematically design control interventions that can deliberately induce ``reverse cascading failures'', in which a network spontaneously evolves to a desirable (rather than a failed) state. Second, I will show that nonlinearity in the form of time-varying dynamics unexpectedly makes temporal networks easier to control than their static counterparts, with the former enjoying dramatic and simultaneous reductions in all costs of control. This is true despite the fact that temporality tends to fragment a network's structure, disrupting the paths that allow the directly-controlled or ``driver'' nodes to communicate with the rest of the network. Taken together, these studies shed new light on the crucial role of nonlinearity in network control, and provide support to the idea we can control nonlinearity, rather than letting nonlinearity control us.

  8. Energy scaling and reduction in controlling complex networks

    Science.gov (United States)

    Chen, Yu-Zhong; Wang, Le-Zhi; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-01-01

    Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks. PMID:27152220

  9. 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.

  10. Integrated control platform for converged optical and wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying

    rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... high data rate services and connectivity at anytime and anywhere. One major challenge in the interworking is how to achieve seamless integration. There are many aspects involved in designing an integrated control platform, such as QoS provisioning, mobility, and resiliency. This dissertation introduces...

  11. Intelligent Servo Drives Control Based on a Single Fieldbus Network

    Directory of Open Access Journals (Sweden)

    D. Puiu

    2010-11-01

    Full Text Available Due to the quick evolution of manufacturing processes, the demand for more flexible automation systems is on the rise. To answer these requirements, distributed motion control architecture based on intelligent drives tends more and more to replace the traditional solutions. This paper presents the control of an articulated arm robot with two local intelligent servo drives connected on a CAN network to a motion controller which receives the trajectory of the robot from a computer. The control structure is based on a single CAN network where local intelligent servo drives, a motion controller and a computer are connected.

  12. Coactivation of Cognitive Control Networks During Task Switching.

    Science.gov (United States)

    Yin, Shouhang; Deák, Gedeon; Chen, Antao

    2017-12-14

    The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. Smart Home: Controlling and Monitoring Households Appliances Using Gsm Network

    National Research Council Canada - National Science Library

    Budi Rahmadya; Fahrul Ghazi; Derisma

    2016-01-01

    This study discussed about using the smart home automation systems for household appliances such as lights and fans, by utilizing the GSM network as a communication medium to control and monitor the household appliances...

  14. The value of peripheral nodes in controlling multilayer networks

    CERN Document Server

    Zhang, Yan; Schweitzer, Frank

    2015-01-01

    We analyze the controllability of a two-layer network, where driver nodes can be chosen only from one layer. Each layer contains a scale-free network with directed links. The dynamics of nodes depends on the incoming links from other nodes (reputation dynamics). We find that the controllable part of the network is larger when choosing peripherial nodes to connect the two layers. The control is as efficient for peripherial nodes as driver nodes as it is for more central nodes. If we assume a cost to utilize nodes which is proportional to their degree, utilizing peripherial nodes to connect the two layers or to act as driver nodes is not only the most cost-efficient solution, it is also the one that gives us the best performance in controlling the two-layer network.

  15. Neighbor-friendly autonomous power control in wireless heterogeneous networks

    National Research Council Canada - National Science Library

    Torrea-Duran, Rodolfo; Tsiaflakis, Paschalis; Vandendorpe, Luc; Moonen, Marc

    2014-01-01

    .... To solve this problem, we propose a neighbor-friendly autonomous algorithm for power control in wireless heterogeneous networks that protects victim users from neighboring cells through a penalty...

  16. 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.

  17. 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 ...

  18. STIMULUS: End-System Network Interface Controller for 100 Gb/s Wide Area Networks

    Energy Technology Data Exchange (ETDEWEB)

    Zarkesh-Ha, Payman [University of New Mexico

    2014-09-12

    The main goal of this research grant is to develop a system-level solution leveraging novel technologies that enable network communications at 100 Gb/s or beyond. University of New Mexico in collaboration with Acadia Optronics LLC has been working on this project to develop the 100 Gb/s Network Interface Controller (NIC) under this Department of Energy (DOE) grant.

  19. Electrochemical properties of Sn/C nanoparticles fabricated by redox treatment and pulsed wire evaporation method

    Science.gov (United States)

    Song, Ju-Seok; Cho, Gyu-Bong; Ahn, Jou-Hyeon; Cho, Kwon-Koo

    2017-09-01

    Tin (Sn) based anode materials are the most promising anode materials for lithium-ion batteries due to their high theoretical capacity corresponding to the formation of Li4.4Sn composition (Li4.4Sn, 994 mAh/g). However, the applications of tin based anodes to lithium-ion battery system are generally limited by a large volume change (>260%) during lithiation and delithiation cycle, which causes pulverize and poor cycling stability. In order to overcome this shortcoming, we fabricate a Sn/C nanoparticle with a yolk-shell structure (Sn/void/C) by using pulsed wire evaporation process and oxidation/reduction heat treatment. Sn nanoparticles are encapsulated by a conductive carbon layer with structural buffer that leaves enough room for expansion and contraction during lithium insertion/desertion. We expect that the yolk-shell structure has the ability to accommodate the volume changes of tin and leading to an improved cycle performance. The Sn/Void/C anode with yolk-shell structure shows a high specific capacity of 760 mAh/g after 50 cycles.

  20. The Vital Network: An Algorithmic Milieu of Communication and Control

    Directory of Open Access Journals (Sweden)

    Sandra Robinson

    2016-09-01

    Full Text Available The biological turn in computing has influenced the development of algorithmic control and what I call the vital network: a dynamic, relational, and generative assemblage that is self-organizing in response to the heterogeneity of contemporary network processes, connections, and communication. I discuss this biological turn in computation and control for communication alongside historically significant developments in cybernetics that set out the foundation for the development of self-regulating computer systems. Control is shifting away from models that historically relied on the human-animal model of cognition to govern communication and control, as in early cybernetics and computer science, to a decentred, nonhuman model of control by algorithm for communication and networks. To illustrate the rise of contemporary algorithmic control, I outline a particular example, that of the biologically-inspired routing algorithm known as a ‘quorum sensing’ algorithm. The increasing expansion of algorithms as a sense-making apparatus is important in the context of social media, but also in the subsystems that coordinate networked flows of information. In that domain, algorithms are not inferring categories of identity, sociality, and practice associated with Internet consumers, rather, these algorithms are designed to act on information flows as they are transmitted along the network. The development of autonomous control realized through the power of the algorithm to monitor, sort, organize, determine, and transmit communication is the form of control emerging as a postscript to Gilles Deleuze’s ‘postscript on societies of control.’

  1. Graphs for information security control in software defined networks

    Science.gov (United States)

    Grusho, Alexander A.; Abaev, Pavel O.; Shorgin, Sergey Ya.; Timonina, Elena E.

    2017-07-01

    Information security control in software defined networks (SDN) is connected with execution of the security policy rules regulating information accesses and protection against distribution of the malicious code and harmful influences. The paper offers a representation of a security policy in the form of hierarchical structure which in case of distribution of resources for the solution of tasks defines graphs of admissible interactions in a networks. These graphs define commutation tables of switches via the SDN controller.

  2. Impact of SDN Controllers Deployment on Network Availability

    OpenAIRE

    Nencioni, Gianfranco; Helvik, Bjarne Emil; Gonzalez, Andres Javier; Heegaard, Poul Einar; Kamisinski, Andrzej

    2016-01-01

    Software-defined networking (SDN) promises to improve the programmability and flexibility of networks, but it may bring also new challenges that need to be explored. The purpose of this technical report is to assess how the deployment of the SDN controllers affects the overall availability of SDN. For this, we have varied the number, homing and location of SDN controllers. A two-level modelling approach that is used to evaluate the availability of the studied scenarios. Our results show how n...

  3. A hyperstable neural network for the modelling and control of ...

    Indian Academy of Sciences (India)

    A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other ...

  4. Brain and cognitive reserve: Translation via network control theory.

    Science.gov (United States)

    Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H; Thompson-Schill, Sharon L; Bassett, Danielle S

    2017-04-01

    Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. The application of neural network PID controller to control the light gasoline etherification

    Science.gov (United States)

    Cheng, Huanxin; Zhang, Yimin; Kong, Lingling; Meng, Xiangyong

    2017-06-01

    Light gasoline etherification technology can effectively improve the quality of gasoline, which is environmental- friendly and economical. By combining BP neural network and PID control and using BP neural network self-learning ability for online parameter tuning, this method optimizes the parameters of PID controller and applies this to the Fcc gas flow control to achieve the control of the final product- heavy oil concentration. Finally, through MATLAB simulation, it is found that the PID control based on BP neural network has better controlling effect than traditional PID control.

  6. Controlling technology costs as integrated networks expand.

    Science.gov (United States)

    Halverson, K

    1995-01-01

    The expansion of integrated healthcare networks is changing the way radiology technology should be acquired and maintained. Some significant effects are that utilization will decline with managed care; the radiology department is now a cost center, not a source of revenue; and integrated networks find themselves with redundant technology and excess radiology equipment. While hospitals shoulder additional financial risk associated with managed care, responsibility for finding solutions to new problems falls to the radiology administrator. Administrators can take the following steps to effectively reduce expense and risk: Understand current usage. Eliminate redundancies. Prioritize modalities. Find new financing opportunities. Lease equipment. Purchase reconditioned equipment. Redeploy assets instead of buying new. Radiology administrators who view these problems as a challenging puzzle will naturally explore creative options. They will provide the greatest flexibility and best position for their department's contributions to the hospital's overall strategic goals.

  7. Controlling Intervention Hazards in the Network MNC

    OpenAIRE

    Foss, Kirsten; Foss, Nicolai J.; Nell, Phillip C.

    2011-01-01

    The MNC literature treats the (parent) HQ as entirely benevolent with respect to their perceived and actual intentions when they intervene at lower levels of the MNC. However, HQ may intervene in subsidiaries in ways that demotivate subsidiary employees and managers (and therefore harm value-creation). This may happen even if such intervention is benevolent in its intentions. We argue that the movement away from more traditional hierarchical forms of the MNC and towards network MNCs placed in...

  8. Wireless sensor network for streetlight monitoring and control

    Science.gov (United States)

    Huang, Xin-Ming; Ma, Jing; Leblanc, Lawrence E.

    2004-08-01

    Wireless sensor network has attracted considerable research attention as the world becomes more information oriented. This technology provides an opportunity of innovations in traditional industries. Management and control of streetlight system is a labor-intensive high-cost task for public facility operations. This paper applies wireless sensor network technology in streetlight monitoring and control. Wireless sensor networks are employed to replace traditional physical patrol maintenance and manual switching on every lamp in the street or along the highway at the aim of reducing the maintenance and management expense. Active control is used to preserve energy cost while ensuring public safety. A proof-of-concept network architecture operated at 900 MHz industrial, scientific, and medical (ISM) band is designed for a two-way wireless telemetry system in streetlight remote control and monitoring. The radio architecture, multi-hop protocol and system interface are discussed in detail. MOTES sensor nodes are used in simulation and experimental tests. Simulation results show that the sensor network approach provides an efficient solution to monitor and control lighting infrastructures through wireless links. The unique application in this paper addresses an immediate need in streetlight control and monitoring, the architecture developed in this research could also serve as a platform for many other applications and researches in wireless sensor network.

  9. 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.

  10. The Tris(pentafluoroethyl)stannate(II) Anion, [Sn(C2 F5 )3 ]- -Synthesis and Reactivity.

    Science.gov (United States)

    Wiesemann, Markus; Klösener, Johannes; Niemann, Mark; Neumann, Beate; Stammler, Hans-Georg; Hoge, Berthold

    2017-10-17

    Syntheses of salts containing the tris(pentafluoroethyl)stannate(II) ion, [Sn(C2 F5 )3 ]- , were achieved through deprotonation of the corresponding stannane, HSn(C2 F5 )3 , as well as by direct pentafluoroethylation of SnCl2 with LiC2 F5 . The electron-withdrawing substituents have substantial influence on the stability and reactivity of the anion as documented by its treatment with main group halides. Alkyl halides (R-X) underwent nucleophilic substitutions to afford RSn(C2 F5 )3 , whereas Si, Ge, Sn, P halides gave rise to oxidation processes yielding hypervalent [SnX2 (C2 F5 )3 ]- salts (X=Cl, Br, I). Moreover the unsymmetrical distannane, nBu3 SnSn(C2 F5 )3 , was disclosed as an alternative precursor for the Sn(C2 F5 )3 moiety. Although neither the solid state structure nor its spectra in alkane solution reveal unexpected peculiarities, unusual dissociation of the compound in coordinating solvents into [nBu3 Sn(D)n ]+ and [Sn(C2 F5 )3 ]- ions was observed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Fluid Limits of Optimally Controlled Queueing Networks

    OpenAIRE

    Guodong Pang; Day, Martin V.

    2007-01-01

    We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes. Peer Reviewed

  12. Fluid Limits of Optimally Controlled Queueing Networks

    Directory of Open Access Journals (Sweden)

    Guodong Pang

    2007-01-01

    Full Text Available We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes.

  13. 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.

  14. Can We Control Contaminant Transport In Hydrologic Networks? Application Of Control Theory Concepts To Watershed Management

    Science.gov (United States)

    Yeghiazarian, L.; Riasi, M. S.

    2016-12-01

    Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.

  15. Role extraction in complex networks and its application in control of networks

    Science.gov (United States)

    Zhou, Mingyang; He, Xingsheng; Fu, Zhongqian; Zhuo, Zhao

    2016-01-01

    Given a large network, dynamics of the network are determined by both nodes' features and network connections. Some features could be extracted from node labels and other kinds of priori knowledge. But how to perform the feature classification without priori knowledge is a challenge. This paper addresses the key problem: how do we conduct role extraction in networks with only edge connections known? On the basis of behavior differences in dynamics, nodes are classified into three role groups: Leaders(L), Communicators(C) and Members(M). Unlike traditional community detections, we detect overlapping communities by link clustering first and then classify nodes according to the community entropy, which describes the disorder of how many different communities a node connects to. We propose a time saving and unsupervised learning approach for automatically discovering nodes' roles based solely on network topology. The effectiveness of this method is demonstrated on six real-world networks through pinning control. By controlling communicator nodes, the controllability is enhanced and the cost for control is reduced obviously in networks with strong community structure.

  16. Control Plane Strategies for Elastic Optical Networks

    DEFF Research Database (Denmark)

    Turus, Ioan

    Networks (EONs) concept is proposed as a solution to enable a more flexible handling of the optical capacity and allows an increase of available capacity over the existing optical infrastructure. One main requirement for enabling EONs is to have a flexible spectrum structure (i.e.Flex-Grid) which allows...... consumption. EONs offer the opportunity of deploying energy efficiency strategies, which benefit from the flexible nature of elastic optoelectronic devices. This thesis proposes and investigates different approaches for reducing power consumption based on EONs in realistic dynamic traffic scenarios....

  17. FIPA agent based network distributed control system

    Energy Technology Data Exchange (ETDEWEB)

    D. Abbott; V. Gyurjyan; G. Heyes; E. Jastrzembski; C. Timmer; E. Wolin

    2003-03-01

    A control system with the capabilities to combine heterogeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents' engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  18. Controllability of Boolean networks via input controls under Harvey's update scheme

    Science.gov (United States)

    Luo, Chao; Zhang, Xiaolin; Shao, Rui; Zheng, YuanJie

    2016-02-01

    In this article, the controllability of Boolean networks via input controls under Harvey's update scheme is investigated. First, the model of Boolean control networks under Harvey's stochastic update is proposed, by means of semi-tensor product approach, which is converted into discrete-time linear representation. And, a general formula of control-depending network transition matrix is provided. Second, based on discrete-time dynamics, controllability of the proposed model is analytically discussed by revealing the necessary and sufficient conditions of the reachable sets, respectively, for three kinds of controls, i.e., free Boolean control sequence, input control networks, and close-loop control. Examples are showed to demonstrate the effectiveness and feasibility of the proposed scheme.

  19. A Network Scheduling Model for Distributed Control Simulation

    Science.gov (United States)

    Culley, Dennis; Thomas, George; Aretskin-Hariton, Eliot

    2016-01-01

    Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

  20. Noise Control for a Moving Evaluation Point Using Neural Networks

    Science.gov (United States)

    Maeda, Toshiki; Shiraishi, Toshihiko

    2016-09-01

    This paper describes the noise control for a moving evaluation point using neural networks by making the best use of its learning ability. Noise control is a technology which is effective on low-frequency noise. Based on the principle of superposition, a primary sound wave can be cancelled at an evaluation point by emitting a secondary opposite sound wave. To obtain good control performance, it is important to precisely identify the characteristics of all the sound paths. One of the most popular algorithms of noise control is filtered-x LMS algorithm. This algorithm can deliver a good result while all the sound paths do not change. However, the control system becomes uncontrollable while the evaluation point is moving. To solve the problem, the characteristics of all the paths are must be identified at all time. In this paper, we applied neural networks with the learning ability to the noise control system to follow the time-varying paths and verified its control performance by numerical simulations. Then, dropout technique for the networks is also applied. Dropout is a technique that prevent the network from overfitting and enables better control performance. By applying dropout for noise control, it prevents the system from diverging.

  1. A source-controlled data center network model.

    Directory of Open Access Journals (Sweden)

    Yang Yu

    Full Text Available 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.

  2. 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.

  3. 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

  4. Microcontroller Protocol for Secure Broadcast in Controller Area Networks

    OpenAIRE

    B Vijayalakshmi; Kumar, K

    2014-01-01

    Controller Area Network is a bus commonly used by controllers inside vehicles and in various industrial control applications. In the past controllers were assumed to operate in secure perimeters, but today these environments are well connected to the outside world and recent incidents showed them extremely vulnerable to cyber-attacks. To withstand such threats, one can implement security in the application layer of CAN. Here we design, refine and implement a broadcast authenti...

  5. A Network Access Control Framework for 6LoWPAN Networks

    Science.gov (United States)

    Oliveira, Luís M. L.; Rodrigues, Joel J. P. C.; de Sousa, Amaro F.; Lloret, Jaime

    2013-01-01

    Low power over wireless personal area networks (LoWPAN), in particular wireless sensor networks, represent an emerging technology with high potential to be employed in critical situations like security surveillance, battlefields, smart-grids, and in e-health applications. The support of security services in LoWPAN is considered a challenge. First, this type of networks is usually deployed in unattended environments, making them vulnerable to security attacks. Second, the constraints inherent to LoWPAN, such as scarce resources and limited battery capacity, impose a careful planning on how and where the security services should be deployed. Besides protecting the network from some well-known threats, it is important that security mechanisms be able to withstand attacks that have not been identified before. One way of reaching this goal is to control, at the network access level, which nodes can be attached to the network and to enforce their security compliance. This paper presents a network access security framework that can be used to control the nodes that have access to the network, based on administrative approval, and to enforce security compliance to the authorized nodes. PMID:23334610

  6. Constraints on the Martian cratering rate imposed by the SNC meteorites and Vallis Marineris layered deposits

    Science.gov (United States)

    Brandenburg, J. E.

    1993-01-01

    Following two independent lines of evidence -- estimates of the age and formation time of a portion of the Martian geologic column exposed in the layered deposits and the crystallization and ejection ages of the SNC meteorites -- it appears that the Martian cratering rate must be double the lunar rate or even higher. This means models such as NHII or NHIII (Neukum and Hiller models II and III), which estimate the Martian cratering rate as being several times lunar are probably far closer to reality on Mars than lunar rates. The effect of such a shift is profound: Mars is transformed from a rather Moon-like place into a planet with vigorous dynamics, multiple large impacts, erosion, floods, and volcanism throughout its history. A strong shift upward in cratering rates on Mars apparently solves some glaring problems; however, it creates others. The period of time during which Earth-like atmospheric conditions existed, the liquid water era on Mars, persists in NHIII up to only 0.5 b.y. ago. Scenarios of extended Earth-like conditions on Mars have been discounted in the past because they would have removed many of the craters from the early bombardment era found in the south. It does appear that some process of crater removal was quite vigorous in the north during Mars' past. Evidence exists that the northern plains may have been the home of long-lived seas or perhaps even a paleo-ocean, so models exist for highly localized destruction of craters in the north. However, the question of how the ancient crater population could be preserved in the south under a long liquid-water era found in any high-cratering-rate models is a serious question that must be addressed. It does appear to be a higher-order problem because it involves low-energy dynamics acting in localized areas, i.e., erosion of craters in the south of Mars, whereas the two problems with the low-cratering-rate models involve high-energy events acting over large areas: the formation of the Vallis Marineris

  7. Digitally Controlled Linear Four-Port Network

    Directory of Open Access Journals (Sweden)

    V. Michalek

    1994-09-01

    Full Text Available The paper deals with the design of a universal linear multipart. The circuit is based on digitally controlled multiple voltage-controlled voltage sources (MVCVSs. The main advantages of this control are accuracy, invariability, and very small area requirements. The whole system is simply connected to a PC via its parallel port. This multipart can generally be used as a building block for any model of a nonlinear dynamic system, namely for the piecewise-linear (PWL model in both explicit and implicit forms.

  8. Some thoughts on the control of network systems

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2011-12-01

    Full Text Available The controllability of network-like systems is becoming a trendy key-issue in many disciplines, including ecology and biology. To control a biological, ecological or economic system is to make it behave according to our wishes, at the least possible cost. In this paper, I propose some ideas on networks control that do not precisely follow recent papers on the argument. By the way, since this scientific topic is still in open evolution, discordant thoughts might be helpful to the debate.

  9. 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.

  10. Practical Application of Neural Networks in State Space Control

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon

    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....... Then the controller is shown to work on a simulation example. We also address the potential problem of too rapidly fluctuating parameters by including regularization in the learning rule. Next we develop a direct adaptive certainty-equivalence controller based on neurofuzzy models. The control loop is proven...

  11. Contrasting network and modular perspectives on inhibitory control.

    Science.gov (United States)

    Hampshire, Adam; Sharp, David J

    2015-08-01

    A prominent theory proposes that the right inferior frontal cortex of the human brain houses a dedicated region for motor response inhibition. However, there is growing evidence to support the view that this inhibitory control hypothesis is incorrect. Here, we discuss evidence in favour of our alternative hypothesis, which states that response inhibition is one example of a broader class of control processes that are supported by the same set of frontoparietal networks. These domain-general networks exert control by modulating local lateral inhibition processes, which occur ubiquitously throughout the cortex. We propose that to fully understand the neural basis of behavioural control requires a more holistic approach that considers how common network mechanisms support diverse cognitive processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Dual adaptive dynamic control of mobile robots using neural networks.

    Science.gov (United States)

    Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

    2009-02-01

    This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

  13. Structure-based control of complex networks with nonlinear dynamics

    CERN Document Server

    Zañudo, Jorge G T; Albert, Réka

    2016-01-01

    Given the network of interactions underlying a complex system, what can we learn about controlling such a system solely from its structure? Over a century of research in control theory has given us tools to answer this question, which were widely applied in science and engineering. Yet the current tools do not always consider the inherently nonlinear dynamics of real systems and the naturally occurring system states in their definition of "control", a term whose interpretation varies across disciplines. Here we use a new mathematical framework for structure-based control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors and which are guaranteed to be effective regardless of the dynamic details and parameters of the underlying system. We use this framework on several real networks, compar...

  14. Representational Similarity Analysis Reveals Heterogeneous Networks Supporting Speech Motor Control

    DEFF Research Database (Denmark)

    Zheng, Zane; Cusack, Rhodri; Johnsrude, Ingrid

    The everyday act of speaking involves the complex processes of speech motor control. One important feature of such control is regulation of articulation when auditory concomitants of speech do not correspond to the intended motor gesture. While theoretical accounts of speech monitoring posit...... is supported by a complex neural network that is involved in linguistic, motoric and sensory processing. With the aid of novel real-time acoustic analyses and representational similarity analyses of fMRI signals, our data show functionally differentiated networks underlying auditory feedback control of speech....... multiple functional components required for detection of errors in speech planning (e.g., Levelt, 1983), neuroimaging studies generally indicate either single brain regions sensitive to speech production errors, or small, discrete networks. Here we demonstrate that the complex system controlling speech...

  15. An artificial neural network controller for intelligent transportation systems applications

    Energy Technology Data Exchange (ETDEWEB)

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

    1996-04-01

    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 applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.

  16. 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...

  17. Trust-Based Collaborative Control for Teams on Communication Networks

    Science.gov (United States)

    2012-02-11

    year only [1] S. Ferrari, S. Jagannathan , and F.L. Lewis, “Special Issue on Approximate Dynamic Programming and Reinforcement Learning,” Journal of...to appear, 2012. [17] H. Xu, S. Jagannathan , and F.L. Lewis, “Stochastic Optimal Control of Unknown Linear Networked Control System in the Presence

  18. Neural Network Based Load Frequency Control for Restructuring ...

    African Journals Online (AJOL)

    Electric load variations can happen independently in both units. Both neural controllers are trained with the back propagation-through-time algorithm. Use of a neural network to model the dynamic system is avoided by introducing the Jacobian matrices of the system in the back propagation chain used in controller training.

  19. Synchronization of general complex networks via adaptive control ...

    Indian Academy of Sciences (India)

    2014-03-07

    Mar 7, 2014 ... 3Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science &. Engineering, Zigong, Sichuan, 643000, People's Republic of China ...... inputs ui(t) (i = 1, 2, 3) and the values of control inputs are acceptable. From figures 1–5, it is easy to see that the controlled complex network ...

  20. Distributed MPC for controlling mu-CHPs in a network

    NARCIS (Netherlands)

    Larsen, Gunn; Trip, Sebastian; van Foreest, Nicky; Scherpen, Jacquelien M.A.

    2012-01-01

    This paper describes a dynamic price mechanism to coordinate electricity generation from micro Combined Heat and Power (mu-CHP) systems in a network of households. The control is done on household level in a completely distributed manner. Distributed Model Predictive control is applied to the

  1. Four Degree Freedom Robot Arm with Fuzzy Neural Network Control

    Directory of Open Access Journals (Sweden)

    Şinasi Arslan

    2013-01-01

    Full Text Available In this study, the control of four degree freedom robot arm has been realized with the computed torque control method.. It is usually required that the four jointed robot arm has high precision capability and good maneuverability for using in industrial applications. Besides, high speed working and external applied loads have been acting as important roles. For those purposes, the computed torque control method has been developed in a good manner that the robot arm can track the given trajectory, which has been able to enhance the feedback control together with fuzzy neural network control. The simulation results have proved that the computed torque control with the neural network has been so successful in robot control.

  2. On the Need of Novel Medium Access Control Schemes for Network Coding enabled Wireless Mesh Networks

    DEFF Research Database (Denmark)

    Paramanathan, Achuthan; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani

    2013-01-01

    This paper advocates for a new Medium Access Control (MAC) strategy for wireless meshed networks by identifying overload scenarios in order to provide additional channel access priority to the relay. The key behind our MAC protocol is that the relay will adjust its back off window size according...... that network coding will improve the throughput in such systems, but our novel medium access scheme improves the performance in the cross topology by another 66 % for network coding and 150 % for classical forwarding in theory. These gains translate in a theoretical gain of 33 % of network coding over...... classical forwarding when both systems implement the improved MAC. However, our measurement results show an even larger gain for network coding, namely, up to 65 % over forwarding, as it copes better with channel losses under high load scenarios....

  3. Evolution of networks and sequences in eukaryotic cell cycle control.

    Science.gov (United States)

    Cross, Frederick R; Buchler, Nicolas E; Skotheim, Jan M

    2011-12-27

    The molecular networks regulating the G1-S transition in budding yeast and mammals are strikingly similar in network structure. However, many of the individual proteins performing similar network roles appear to have unrelated amino acid sequences, suggesting either extremely rapid sequence evolution, or true polyphyly of proteins carrying out identical network roles. A yeast/mammal comparison suggests that network topology, and its associated dynamic properties, rather than regulatory proteins themselves may be the most important elements conserved through evolution. However, recent deep phylogenetic studies show that fungal and animal lineages are relatively closely related in the opisthokont branch of eukaryotes. The presence in plants of cell cycle regulators such as Rb, E2F and cyclins A and D, that appear lost in yeast, suggests cell cycle control in the last common ancestor of the eukaryotes was implemented with this set of regulatory proteins. Forward genetics in non-opisthokonts, such as plants or their green algal relatives, will provide direct information on cell cycle control in these organisms, and may elucidate the potentially more complex cell cycle control network of the last common eukaryotic ancestor.

  4. 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.

  5. X-ray photoelectron spectroscopy studies of the electronic structure of superconducting Nb{sub 2}SnC and Nb{sub 2}SC

    Energy Technology Data Exchange (ETDEWEB)

    Romero, M.; Huerta, L.; Akachi, T. [Instituto de Investigaciones en Materiales, Universidad Nacional Autónoma de México, Apartado Postal 70-360, México D.F. 04510 (Mexico); Llamazares, J.L. Sánchez [Instituto Potosino de Investigación Científica y Tecnológica, Camino a la Presa San José 2055, Col. Lomas 4a, San Luis Potosí, S.L.P. 78216 (Mexico); Escamilla, R., E-mail: rauleg@unam.mx [Instituto de Investigaciones en Materiales, Universidad Nacional Autónoma de México, Apartado Postal 70-360, México D.F. 04510 (Mexico)

    2013-12-05

    Highlights: •XPS was used to investigate chemical shift in the Nb{sub 2}SnC and Nb{sub 2}SC compounds. •Valence band of the Nb{sub 2}SnC and Nb{sub 2}SC compounds was studied by XPS. •Positive and negative chemical shift are observed in the Nb{sub 2}SnC and Nb{sub 2}SC. •The charge transfer model can be applicable to the Nb{sub 2}SnC and Nb{sub 2}SC compounds. •The decrease of the N(E{sub F}) of Nb{sub 2}SC respect to Nb{sub 2}SnC explain the decrease of T{sub c}. -- Abstract: X-ray photoelectron spectroscopy (XPS) was used to investigate the binding energies and valence band of the Nb{sub 2}SnC and Nb{sub 2}SC compounds. The Nb 3d{sub 5/2}, Sn 3d{sub 5/2}, S 2p{sub 3/2} and C 1s core levels associated with the chemical states of Nb{sub 2}SnC and Nb{sub 2}SC were identified. The spectra for Nb{sub 2}SnC revealed Nb and Sn oxides on the surface of the sample, mainly Nb{sub 2}O{sub 5} and SnO{sub 2}, while the Nb{sub 2}SC only Nb{sub 2}O{sub 5} oxide. After Ar{sup +} ion etching the intensity of the oxides decreased in both samples. Comparing the Nb 3d, Sn 3d, S 2p and C 1s core levels with metallic Nb, Sn, S and C reference materials, we observed a positive chemical shift for Nb 3d{sub 5/2} and a negative chemical shift for C 1s in both samples. These results suggest that the charge transfer model can be applicable to the Nb{sub 2}SnC and Nb{sub 2}SC compounds. Finally, the decrease in the T{sub c} in the Nb{sub 2}SC compound respect to Nb{sub 2}SnC might be associated to decrease in the density of states N(E{sub F})

  6. 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...

  7. 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

    architecture. The approaches to QoS mapping, label distribution and connection and admission control (CAC) are specified here. At last, a simple T-MPLS based Carrier Ethernet network model with three kinds of users (VoIP, VoD and HTTP) and a RACE based control module is simulated in OPNET. The model is aiming...

  8. 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

  9. 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.

  10. Wireless Sensor/Actuator Network Design for Mobile Control Applications

    Directory of Open Access Journals (Sweden)

    Youxian Sung

    2007-10-01

    Full Text Available Wireless sensor/actuator networks (WSANs are emerging as a new generationof sensor networks. Serving as the backbone of control applications, WSANs will enablean unprecedented degree of distributed and mobile control. However, the unreliability ofwireless communications and the real-time requirements of control applications raise greatchallenges for WSAN design. With emphasis on the reliability issue, this paper presents anapplication-level design methodology for WSANs in mobile control applications. Thesolution is generic in that it is independent of the underlying platforms, environment,control system models, and controller design. To capture the link quality characteristics interms of packet loss rate, experiments are conducted on a real WSAN system. From theexperimental observations, a simple yet efficient method is proposed to deal withunpredictable packet loss on actuator nodes. Trace-based simulations give promisingresults, which demonstrate the effectiveness of the proposed approach.

  11. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  12. Expanding the NATO Movement Control Network

    Science.gov (United States)

    2016-05-17

    mander of the 624th Movement Con- trol Team, 39th Transportation Battalion (Movement Control), 16th Sustainment Brigade, at Kleber Kaserne, Germany . He...Philip Stephens) 31 Army Sustainment November–December 2015 Challenges of Moving in Europe...have been operating in Germany and Italy since the end of World War II and understand those nations’ requirements well, but recent changes in

  13. Controlling high speed automated transport network operations

    NARCIS (Netherlands)

    de Feijter, R.

    2006-01-01

    This thesis presents a framework for the control of automated guided vehicles (AGVs). The framework implements the transport system as a community of cooperating agents. Besides the architecture and elements of the framework a wide range of infrastructure scene templates is described. These scene

  14. Modelling and control of cell reaction networks

    NARCIS (Netherlands)

    S. Jha; J.H. van Schuppen (Jan)

    2001-01-01

    textabstractThe project aims at a study of the nonlinear systems arising in the biochemical processes occuring inside a cell. The cellular regulation has been formulated in the more familiar framework used in control and system theory in terms of inputs as the variables which can be influenced

  15. Control of a hybrid compensator in a power network by an artificial neural network

    Directory of Open Access Journals (Sweden)

    I. S. Shaw

    1998-07-01

    Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

  16. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  17. Adaptive Reference Control for Pressure Management in Water Networks

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal

    2015-01-01

    Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....

  18. Probabilistic Priority Message Checking Modeling Based on Controller Area Networks

    Science.gov (United States)

    Lin, Cheng-Min

    Although the probabilistic model checking tool called PRISM has been applied in many communication systems, such as wireless local area network, Bluetooth, and ZigBee, the technique is not used in a controller area network (CAN). In this paper, we use PRISM to model the mechanism of priority messages for CAN because the mechanism has allowed CAN to become the leader in serial communication for automobile and industry control. Through modeling CAN, it is easy to analyze the characteristic of CAN for further improving the security and efficiency of automobiles. The Markov chain model helps us to model the behaviour of priority messages.

  19. Adaptive nonlinear control of missiles using neural networks

    Science.gov (United States)

    McFarland, Michael Bryan

    Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear

  20. ACTS TDMA network control. [Advanced Communication Technology Satellite

    Science.gov (United States)

    Inukai, T.; Campanella, S. J.

    1984-01-01

    This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

  1. Connection adaption for control of networked mobile chaotic agents.

    Science.gov (United States)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S

    2017-11-22

    In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.

  2. An architecture for designing fuzzy logic controllers using neural networks

    Science.gov (United States)

    Berenji, Hamid R.

    1991-01-01

    Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

  3. Discrete-event control of stochastic networks multimodularity and regularity

    CERN Document Server

    Altman, Eitan; Hordijk, Arie

    2003-01-01

    Opening new directions in research in both discrete event dynamic systems as well as in stochastic control, this volume focuses on a wide class of control and of optimization problems over sequences of integer numbers. This is a counterpart of convex optimization in the setting of discrete optimization. The theory developed is applied to the control of stochastic discrete-event dynamic systems. Some applications are admission, routing, service allocation and vacation control in queueing networks. Pure and applied mathematicians will enjoy reading the book since it brings together many disciplines in mathematics: combinatorics, stochastic processes, stochastic control and optimization, discrete event dynamic systems, algebra.

  4. Networked vision system using a Prolog controller

    Science.gov (United States)

    Batchelor, B. G.; Caton, S. J.; Chatburn, L. T.; Crowther, R. A.; Miller, J. W. V.

    2005-11-01

    Prolog offers a very different style of programming compared to conventional languages; it can define object properties and abstract relationships in a way that Java, C, C++, etc. find awkward. In an accompanying paper, the authors describe how a distributed web-based vision systems can be built using elements that may even be located on different continents. One particular system of this general type is described here. The top-level controller is a Prolog program, which operates one, or more, image processing engines. This type of function is natural to Prolog, since it is able to reason logically using symbolic (non-numeric) data. Although Prolog is not suitable for programming image processing functions directly, it is ideal for analysing the results derived by an image processor. This article describes the implementation of two systems, in which a Prolog program controls several image processing engines, a simple robot, a pneumatic pick-and-place arm), LED illumination modules and a various mains-powered devices.

  5. Experimental determination of group flux control coefficients in metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G. [Massachusetts Inst. of Tech., Cambridge, MA (United States). Dept. of Chemical Engineering

    1998-04-20

    Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmental perturbations are used to determine the group flux control coefficients for three reaction groups formed around the phosphoenolpyruvate/pyruvate branch point. The consistency of the obtained group flux control coefficient estimates is systematically analyzed to ensure that all necessary conditions are satisfied. The magnitudes of the determined control coefficients suggest that the control of lysine production flux in Corynebacterium glutamicum cells at a growth base state resides within the lysine biosynthetic pathway that begins with the PEP/PYR carboxylation anaplorotic pathway.

  6. Spiking neural network-based control chart pattern recognition

    Directory of Open Access Journals (Sweden)

    Medhat H.A. Awadalla

    2012-03-01

    Full Text Available Due to an increasing competition in products, consumers have become more critical in choosing products. The quality of products has become more important. Statistical Process Control (SPC is usually used to improve the quality of products. Control charting plays the most important role in SPC. Control charts help to monitor the behavior of the process to determine whether it is stable or not. Unnatural patterns in control charts mean that there are some unnatural causes for variations in SPC. Spiking neural networks (SNNs are the third generation of artificial neural networks that consider time as an important feature for information representation and processing. In this paper, a spiking neural network architecture is proposed to be used for control charts pattern recognition (CCPR. Furthermore, enhancements to the SpikeProp learning algorithm are proposed. These enhancements provide additional learning rules for the synaptic delays, time constants and for the neurons thresholds. Simulated experiments have been conducted and the achieved results show a remarkable improvement in the overall performance compared with artificial neural networks.

  7. Steam turbine stress control using NARX neural network

    Science.gov (United States)

    Dominiczak, Krzysztof; Rzadkowski, Romuald; Radulski, Wojciech

    2015-11-01

    Considered here is concept of steam turbine stress control, which is based on Nonlinear AutoRegressive neural networks with eXogenous inputs. Using NARX neural networks,whichwere trained based on experimentally validated FE model allows to control stresses in protected thickwalled steam turbine element with FE model quality. Additionally NARX neural network, which were trained base on FE model, includes: nonlinearity of steam expansion in turbine steam path during transients, nonlinearity of heat exchange inside the turbine during transients and nonlinearity of material properties during transients. In this article NARX neural networks stress controls is shown as an example of HP rotor of 18K390 turbine. HP part thermodynamic model as well as heat exchange model in vicinity of HP rotor,whichwere used in FE model of the HP rotor and the HP rotor FE model itself were validated based on experimental data for real turbine transient events. In such a way it is ensured that NARX neural network behave as real HP rotor during steam turbine transient events.

  8. The Adaptive Neural Network Control of Quadrotor Helicopter

    Directory of Open Access Journals (Sweden)

    A. S. Yushenko

    2017-01-01

    Full Text Available The current steady-rising interest in using the unmanned multi-rotor aerial vehicles (UMAV designed to solve a wide range of tasks is, mainly, due to their simple design and high weight-carrying capacity as compared to classical helicopter options. Unfortunately, to solve a problem of multi-copter control is complicated because of essential nonlinearity and environmental perturbations. The most widely spread PID controllers and linear-quadratic regulators do not quite well cope with this task. The need arises for the prompt adjustment of PID controller coefficients in the course of operation or their complete re-tuning in cases of changing parameters of the control object.One of the control methods under changing conditions is the use of the sliding mode. This technology enables us to reach the stabilization and proper operation of the controlled system even under accidental external exposures and when there is a lack of the reasonably accurate mathematical model of the control object. The sliding principle is to ensure the system motion in the immediate vicinity of the sliding surface in the phase space. On the other hand, the sliding mode has some essential disadvantages. The most significant one is the high-frequency jitter of the system near the sliding surface. The sliding mode also implies the complete knowledge of the system dynamics. Various methods have been proposed to eliminate these drawbacks. For example, A.G. Aissaoui’s, H. Abid’s and M. Abid’s paper describes the application of fuzzy logic to control a drive and in Lon-Chen Hung’s and Hung-Yuan Chung’s paper an artificial neural network is used for the manipulator control.This paper presents a method of the quad-copter control with the aid of a neural network controller. This method enables us to control the system without a priori information on parameters of the dynamic model of the controlled object. The main neural network is a MIMO (“Multiple Input Multiple

  9. 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

  10. Modificaciones epigenéticas asociadas a los efectos de la morfina en el SNC del pez cebra

    OpenAIRE

    Jiménez González, Ada

    2016-01-01

    [ES] La morfina es en la actualidad el tratamiento de primera línea para el dolor crónico y para el dolor padecido por pacientes terminales (Bauer y cols., 2016). Además, junto a otros opioides, como la heroína, causa problemas en el desarrollo temprano del SNC. Estos daños son comunes dado que la exposición prenatal a opioides es muy frecuente en relación al alto número de mujeres gestantes que los consumen (Kremer y Arora, 2015). Con el fin de controlar estos efectos, es necesaria una clara...

  11. 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

  12. Formation control for a network of small-scale robots.

    Science.gov (United States)

    Kim, Yoonsoo

    2014-10-01

    In this paper, a network of small-scale robots (typically centimeter-scale robots) equipped with artificial actuators such as electric motors is considered. The purpose of this network is to have the robots keep a certain formation shape (or change to another formation shape) during maneuvers. The network has a fixed communication topology in the sense that robots have a fixed group of neighbors to communicate during maneuvers. Assuming that each robot and its actuator can be modeled as a linear system, a decentralized control law (such that each robot activates its actuator based on the information from its neighbors only) is introduced to achieve the purpose of formation keeping or change. A linear matrix inequality (LMI) for deriving the upper bound on the actuator's time constant is also presented. Simulation results are shown to demonstrate the merit of the introduced control law.

  13. Sparse Packetized Predictive Control for Networked Control over Erasure Channels

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel E.; Østergaard, Jan

    2014-01-01

    We study feedback control over erasure channels with packet-dropouts. To achieve robustness with respect to packet-dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. To reduce the data size of packets, we propose...... to adopt sparsity-promoting optimizations, namely, l1 - l2 and l2-constrained l0 optimizations, for which efficient algorithms exist. We show how to design the tuning parameters to ensure (practical) stability of the resulting feedback control systems when the number of consecutive packet...

  14. High Resolution Sensing and Control of Urban Water Networks

    Science.gov (United States)

    Bartos, M. D.; Wong, B. P.; Kerkez, B.

    2016-12-01

    We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

  15. H∞ Guaranteed Cost Control for Networked Control Systems under Scheduling Policy Based on Predicted Error

    Directory of Open Access Journals (Sweden)

    Qixin Zhu

    2014-01-01

    Full Text Available Scheduling policy based on model prediction error is presented to reduce energy consumption and network conflicts at the actuator node, where the characters of networked control systems are considered, such as limited network bandwidth, limited node energy, and high collision probability. The object model is introduced to predict the state of system at the sensor node. And scheduling threshold is set at the controller node. Control signal is transmitted only if the absolute value of prediction error is larger than the threshold value. Furthermore, the model of networked control systems under scheduling policy based on predicted error is established by taking uncertain parameters and long time delay into consideration. The design method of H∞ guaranteed cost controller is presented by using the theory of Lyapunov and linear matrix inequality (LMI. Finally, simulations are included to demonstrate the theoretical results.

  16. Converging Redundant Sensor Network Information for Improved Building Control

    Energy Technology Data Exchange (ETDEWEB)

    Dale Tiller; D. Phil; Gregor Henze; Xin Guo

    2007-09-30

    This project investigated the development and application of sensor networks to enhance building energy management and security. Commercial, industrial and residential buildings often incorporate systems used to determine occupancy, but current sensor technology and control algorithms limit the effectiveness of these systems. For example, most of these systems rely on single monitoring points to detect occupancy, when more than one monitoring point could improve system performance. Phase I of the project focused on instrumentation and data collection. During the initial project phase, a new occupancy detection system was developed, commissioned and installed in a sample of private offices and open-plan office workstations. Data acquisition systems were developed and deployed to collect data on space occupancy profiles. Phase II of the project demonstrated that a network of several sensors provides a more accurate measure of occupancy than is possible using systems based on single monitoring points. This phase also established that analysis algorithms could be applied to the sensor network data stream to improve the accuracy of system performance in energy management and security applications. In Phase III of the project, the sensor network from Phase I was complemented by a control strategy developed based on the results from the first two project phases: this controller was implemented in a small sample of work areas, and applied to lighting control. Two additional technologies were developed in the course of completing the project. A prototype web-based display that portrays the current status of each detector in a sensor network monitoring building occupancy was designed and implemented. A new capability that enables occupancy sensors in a sensor network to dynamically set the 'time delay' interval based on ongoing occupant behavior in the space was also designed and implemented.

  17. Control of Resources for Economic Development in Food Networks

    DEFF Research Database (Denmark)

    Brink, Tove

    2010-01-01

    of preferences on the control of resources, the significant benefit of oral instructions and the significant negative impact from supervising product quality on economic development in the context of the food networking SMEs. Previous level of knowledge has no significant influence on their economic development...... to control resources for innovation to add value and economic development. This paper reveals how crossing dynamic composite underlying boundaries can have an impact on control of resources for economic development in food networking SMEs .The analyses in this paper shows the broad and significant impact......The challenge of economic development in the 21st century is linked to innovation. Enabling innovation contains a wide span from the new idea to learning how to provide value through the new idea and continuing to how to control resources to perform at prime. The focus in this paper is set on how...

  18. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2017-11-02

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Neural networks for process control and optimization: two industrial applications.

    Science.gov (United States)

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  20. Handling uncertainty and networked structure in robot control

    CERN Document Server

    Tamás, Levente

    2015-01-01

    This book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describes learning control to address environmental uncertainty. Part II discusses state estimation, active sensing, and complex scenario perception to tackle sensing uncertainty. Part III completes the book with control of networked robots and multi-robot teams. Each chapter features in-depth technical coverage and case studies highlighting the applicability of the techniques, with real robots or in simulation. Platforms include mobile ground, aerial, and underwater robots, as well as humanoid robots and robot arms. Source code and experimental data are available at http://extras.springer.com. The text gathers contributions from academic and industry experts, and offers a valuable resource for researchers or graduate students in robot control and perception. It also benefits researchers in related areas, such as computer...

  1. On-board congestion control for satellite packet switching networks

    Science.gov (United States)

    Chu, Pong P.

    1991-01-01

    It is desirable to incorporate packet switching capability on-board for future communication satellites. Because of the statistical nature of packet communication, incoming traffic fluctuates and may cause congestion. Thus, it is necessary to incorporate a congestion control mechanism as part of the on-board processing to smooth and regulate the bursty traffic. Although there are extensive studies on congestion control for both baseband and broadband terrestrial networks, these schemes are not feasible for space based switching networks because of the unique characteristics of satellite link. Here, we propose a new congestion control method for on-board satellite packet switching. This scheme takes into consideration the long propagation delay in satellite link and takes advantage of the the satellite's broadcasting capability. It divides the control between the ground terminals and satellite, but distributes the primary responsibility to ground terminals and only requires minimal hardware resource on-board satellite.

  2. Controlling self-organized criticality in complex networks

    CERN Document Server

    Cajueiro, Daniel O

    2013-01-01

    A control scheme to reduce the size of avalanches of the Bak-Tang-Wiesenfeld model on complex networks is proposed. Three network types are considered: those proposed by Erd\\H{o}s-Renyi, Goh-Kahng-Kim, and a real network representing the main connections of the electrical power grid of the western United States. The control scheme is based on the idea of triggering avalanches in the highest degree nodes that are near to become critical. We show that this strategy works in the sense that the dissipation of mass occurs most locally avoiding larger avalanches. We also compare this strategy with a random strategy where the nodes are chosen randomly. Although the random control has some ability to reduce the probability of large avalanches, its performance is much worse than the one based on the choice of the highest degree nodes. Finally, we argue that the ability of the proposed control scheme is related to its ability to reduce the concentration of mass on the network.

  3. Model-based Compositional Design of Networked Control Systems

    Science.gov (United States)

    2013-12-01

    systems such as tele- robots for surgery , implanted heart monitors, nanoscale di- agnostic instruments, digital protheses and other medical devices, as...exploration, surgery , search and rescue missions, hazardous environment and other various military applications. An n-degrees of freedom robotic manipulator...lives. Examples of these systems include process control, automotive systems, networked robotics , medical systems, electrical power grids and

  4. Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Fafoutis, Xenofon; Dragoni, Nicola

    2012-01-01

    ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever...

  5. Ubiquitous access control and policy management in personal networks

    DEFF Research Database (Denmark)

    Kyriazanos, Dimitris M.; Stassinopoulos, George I.; Prasad, Neeli R.

    2006-01-01

    In this paper the authors present the challenges for enabling Security Policies Management and subsequent Ubiquitous Access Control on the Personal Network (PN) environment. A solution based on Security Profiles is proposed, supporting both partially distributed architectures-having in this case...

  6. Specification Mining for Intrusion Detection in Networked Control Systems

    NARCIS (Netherlands)

    Caselli, M.; Zambon, Emmanuele; Amann, Johanna; Sommer, Robin; Kargl, Frank

    2016-01-01

    This paper discusses a novel approach to specification-based intrusion detection in the field of networked control systems. Our approach reduces the substantial human effort required to deploy a specification-based intrusion detection system by automating the development of its specification rules.

  7. Structure and Controls of the Global Virtual Water Trade Network

    Science.gov (United States)

    Suweis, S. S.

    2011-12-01

    Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e. the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model, the fitness model, that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened. Our results show the importance of incorporating a network framework in the study of virtual water trades and provide a model to study the structure and resilience of the GVWTN under future scenarios for social, economic and climate change.

  8. Adaptive PID control based on orthogonal endocrine neural networks.

    Science.gov (United States)

    Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D

    2016-12-01

    A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Equipment to Support Development of Neuronal Network Controlled Robots

    Science.gov (United States)

    2016-06-25

    Equipment to Support Development of Neuronal Network Controlled Robots With this award, our team purchased an ALA 2-channel stimulus generator, an...34 laser cutter, and a Rethink Robotics Baxter Robot . This equipment supported two ARO awards, a DARPA award and two NSF-funded projects. The views...Controlled Robots Report Title With this award, our team purchased an ALA 2-channel stimulus generator, an ALA 60-channel amplifier with pre-filter

  10. Controllable Soluble Protein Concentration Gradients in Hydrogel Networks**

    OpenAIRE

    Peret, Brian J.; William L Murphy

    2008-01-01

    Here we report controlled formation of sustained, soluble protein concentration gradients within hydrated polymer networks. The approach involves spatially localizing proteins or biodegradable, protein-loaded microspheres within hydrogels to form a protein-releasing “depot”. Soluble protein concentration gradients are then formed as the released protein diffuses away from the localized source. Control over key gradient parameters, including maximum concentration, gradient magnitude, slope, an...

  11. Scalable Harmonization of Complex Networks With Local Adaptive Controllers

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Herzallah, R.

    2017-01-01

    Roč. 47, č. 3 (2017), s. 394-404 ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Feedback * Feedforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.350, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf

  12. Piecewise-linear artificial neural networks for PID controller tuning

    Directory of Open Access Journals (Sweden)

    Petr Doležel

    2012-12-01

    Full Text Available A new algorithm of PID controller tuning is presented in this paper. It is well known that there have been introduced manytechniques for PID controller tuning, both theoretical and experimental ones. However, this algorithm is suitable especially forhighly nonlinear processes. It uses a model of the controlled process in the shape of piecewise-linear neural network which islinearized continuously and resulting linearized model is used for PID controller online tuning. While at the beginning of the paperthe algorithm is described in theory, at the end there are mentioned some practical applications

  13. Linear Matrix Inequalities in Multirate Control over Networks

    Directory of Open Access Journals (Sweden)

    Ángel Cuenca

    2012-01-01

    Full Text Available This paper faces two of the main drawbacks in networked control systems: bandwidth constraints and timevarying delays. The bandwidth limitations are solved by using multirate control techniques. The resultant multirate controller must ensure closed-loop stability in the presence of time-varying delays. Some stability conditions and a state feedback controller design are formulated in terms of linear matrix inequalities. The theoretical proposal is validated in two different experimental environments: a crane-based test-bed over Ethernet, and a maglev based platform over Profibus.

  14. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network

    Directory of Open Access Journals (Sweden)

    Kazuhiko Hiramoto

    2018-01-01

    Full Text Available We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN. Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA. The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.

  15. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  16. Tuning RED parameters in satellite networks using control theory

    Science.gov (United States)

    Sridharan, Mukundan; Durresi, Arjan; Chellappan, Sriram; Ozbay, Hitay; Jain, Raj

    2003-08-01

    Congestion in the Internet results in wasted bandwidth and also stands in the way of guaranteeing QoS. The effect of congestion is multiplied many fold in Satellite networks, where the resources are very expensive. Thus congestion control has a special significance in the performance of Satellite networks. In today's Internet, congestion control is implemented mostly using some form of the de facto standard, RED. But tuning of parameters in RED has been a major problem throughout. Achieving high throughput with corresponding low delays is the main goal in parameter setting. It is also desired to keep the oscillations in the queue low to reduce jitter, so that the QoS guarantees can be improved. In this paper, we use a previously linearized fluid flow model of TCP-RED to study the performance and stability of the Queue in the router. We use classical control tools like Tracking Error minimization and Delay Margin to study the performance, stability of the system. We use the above-mentioned tools to provide guidelines for setting the parameters in RED, such that the throughput, delay and jitter of the system are optimized. Thus we provide guidelines for optimizing satellite IP networks. We apply our results exclusively for optimizing the performance of satellite networks, where the effects of congestion are much pronounced and need for optimization is much important. We use ns simulator to validate our results to support our analysis.

  17. 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.

  18. Controllable Reconfiguration of Polymer-grafted Nanoparticle Networks Under Torsion

    Science.gov (United States)

    Zhang, Tao; Mbanga, Badel; Yashin, Victor; Balazs, Anna

    We use 3D computational modeling to study mechanically-induced changes in the structure of networks formed from polymer-grafted nanoparticles (PGNs). The nanoparticles rigid cores are decorated with a corona of grafted polymers, which contain reactive functional groups at the chain ends. With the overlap of the grafted polymers, these reactive groups can form labile bonds, which can reform after breakage. These PGN networks consist of two types of nanoparticles, which differ in the reactive functional groups at the chain ends. The energy of the labile bonds that are formed depends on the nature of these reactive groups. We demonstrate that the application of a rotational deformation results in a controllable reconfiguration of the network. Depending on the labile bond energies, the PGN networks are shown to exhibit a deformation-induced phase separation. The restructuring process can be controlled by boundary conditions. We can create complicated morphology such as spiral, with enhanced mechanical properties. Our results provide guidelines for designing mechano-mutable PGN-based materials whose nanoscale structures can be controllably changed under an applied mechanical action.

  19. Network efficient power control for wireless communication systems.

    Science.gov (United States)

    Campos-Delgado, Daniel U; Luna-Rivera, Jose Martin; Martinez-Sánchez, C J; Gutierrez, Carlos A; Tecpanecatl-Xihuitl, J L

    2014-01-01

    We introduce a two-loop power control that allows an efficient use of the overall power resources for commercial wireless networks based on cross-layer optimization. This approach maximizes the network's utility in the outer-loop as a function of the averaged signal to interference-plus-noise ratio (SINR) by considering adaptively the changes in the network characteristics. For this purpose, the concavity property of the utility function was verified with respect to the SINR, and an iterative search was proposed with guaranteed convergence. In addition, the outer-loop is in charge of selecting the detector that minimizes the overall power consumption (transmission and detection). Next the inner-loop implements a feedback power control in order to achieve the optimal SINR in the transmissions despite channel variations and roundtrip delays. In our proposal, the utility maximization process and detector selection and feedback power control are decoupled problems, and as a result, these strategies are implemented at two different time scales in the two-loop framework. Simulation results show that substantial utility gains may be achieved by improving the power management in the wireless network.

  20. Iterative Learning Control with Forgetting Factor for Urban Road Network

    Directory of Open Access Journals (Sweden)

    Tianyi Lan

    2017-01-01

    Full Text Available In order to improve the traffic condition, a novel iterative learning control (ILC algorithm with forgetting factor for urban road network is proposed by using the repeat characteristics of traffic flow in this paper. Rigorous analysis shows that the proposed ILC algorithm can guarantee the asymptotic convergence. Through iterative learning control of the traffic signals, the number of vehicles on each road in the network can gradually approach the desired level, thereby preventing oversaturation and traffic congestion. The introduced forgetting factor can effectively adjust the control input according to the states of the system and filter along the direction of the iteration. The results show that the forgetting factor has an important effect on the robustness of the system. The theoretical analysis and experimental simulations are given to verify the validity of the proposed method.

  1. Spontaneous centralization of control in a network of company ownerships.

    Directory of Open Access Journals (Sweden)

    Sebastian M Krause

    Full Text Available We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is marked by a central, tightly connected "core" made of a small number of large companies which control a significant part of the global economy. Here we show how a simple, adaptive "rich get richer" dynamics can account for this characteristic, which incorporates the increased buying power of more influential companies, and in turn results in even higher control. We conclude that this kind of centralized structure can emerge without it being an explicit goal of these companies, or as a result of a well-organized strategy.

  2. Control of Stochastic and Induced Switching in Biophysical Networks

    Science.gov (United States)

    Wells, Daniel K.; Kath, William L.; Motter, Adilson E.

    2015-07-01

    Noise caused by fluctuations at the molecular level is a fundamental part of intracellular processes. While the response of biological systems to noise has been studied extensively, there has been limited understanding of how to exploit it to induce a desired cell state. Here we present a scalable, quantitative method based on the Freidlin-Wentzell action to predict and control noise-induced switching between different states in genetic networks that, conveniently, can also control transitions between stable states in the absence of noise. We apply this methodology to models of cell differentiation and show how predicted manipulations of tunable factors can induce lineage changes, and further utilize it to identify new candidate strategies for cancer therapy in a cell death pathway model. This framework offers a systems approach to identifying the key factors for rationally manipulating biophysical dynamics, and should also find use in controlling other classes of noisy complex networks.

  3. Predictive Closed-Loop Power Control for CDMA Cellular Networks

    Science.gov (United States)

    Choe, Sangho; Uysal, Murat

    In this paper, we present and analyze a predictive closedloop power control (CLPC) scheme which employs a comb-type sample arrangement to effectively compensate multiple power control group (PCG) delays over mobile fading channels. We consider both least squares and recursive least squares filters in our CLPC scheme. The effects of channel estimation error, prediction filter error, and power control bit transmission error on the performance of the proposed CLPC method along with competing non-predictive and predictive CLPC schemes are thoroughly investigated. Our results clearly indicate the superiority of the proposed scheme with its improved robustness under non-ideal conditions. Furthermore, we carry out a Monte-Carlo simulation study of a 5×5 square grid cellular network and evaluate the user capacity. Capacity improvements up to 90% are observed for a typical cellular network scenario.

  4. Camera Control and Geo-Registration for Video Sensor Networks

    Science.gov (United States)

    Davis, James W.

    With the use of large video networks, there is a need to coordinate and interpret the video imagery for decision support systems with the goal of reducing the cognitive and perceptual overload of human operators. We present computer vision strategies that enable efficient control and management of cameras to effectively monitor wide-coverage areas, and examine the framework within an actual multi-camera outdoor urban video surveillance network. First, we construct a robust and precise camera control model for commercial pan-tilt-zoom (PTZ) video cameras. In addition to providing a complete functional control mapping for PTZ repositioning, the model can be used to generate wide-view spherical panoramic viewspaces for the cameras. Using the individual camera control models, we next individually map the spherical panoramic viewspace of each camera to a large aerial orthophotograph of the scene. The result provides a unified geo-referenced map representation to permit automatic (and manual) video control and exploitation of cameras in a coordinated manner. The combined framework provides new capabilities for video sensor networks that are of significance and benefit to the broad surveillance/security community.

  5. TCP flow control using link layer information in mobile networks

    Science.gov (United States)

    Koga, Hiroyuki; Kawahara, Kenji; Oie, Yuji

    2002-07-01

    Mobile Networks have been expanding and IMT-2000 further increases their available bandwidth over wireless links. However, TCP, which is a reliable end-to-end transport protocol, is tuned to perform well in wired networks where bit error rates are very low and packet loss occurs mostly because of congestion. Although a TCP sender can execute flow control to utilize as much available bandwidth as possible in wired networks, it cannot work well in wireless networks characterized by high bit error rates. In the next generation mobile systems, sophisticated error recovery technologies of FEC and ARQ are indeed employed over wireless links, i.e., over Layer 2, to avoid performance degradation of upper layers. However, multiple retransmissions by Layer 2 ARQ can adversely increase transmission delay of TCP segments, which will further make TCP unnecessarily increase RTO (Retransmission TimeOut). Furthermore, a link bandwidth assigned to TCP flows can change in response to changing air conditions to use wireless links efficiently. TCP thus has to adapt its transmission rate according to the changing available bandwidth. The major goal of this study is to develop a receiver-based effective TCP flow control without any modification on TCP senders, which are probably connected with wired networks. For this end, we propose a TCP flow control employing some Layer 2 information on a wireless link at the mobile station. Our performance evaluation of the proposed TCP shows that the receiver-based TCP flow control can moderate the performance degradation very well even if FER on Layer 2 is high.

  6. Microwave Plasma Chemical Vapor Deposition of Nano-Structured Sn/C Composite Thin-Film Anodes for Li-ion Batteries

    Energy Technology Data Exchange (ETDEWEB)

    Stevenson, Cynthia; Marcinek, M.; Hardwick, L.J.; Richardson, T.J.; Song, X.; Kostecki, R.

    2008-02-01

    In this paper we report results of a novel synthesis method of thin-film composite Sn/C anodes for lithium batteries. Thin layers of graphitic carbon decorated with uniformly distributed Sn nanoparticles were synthesized from a solid organic precursor Sn(IV) tert-butoxide by a one step microwave plasma chemical vapor deposition (MPCVD). The thin-film Sn/C electrodes were electrochemically tested in lithium half cells and produced a reversible capacity of 440 and 297 mAhg{sup -1} at C/25 and 5C discharge rates, respectively. A long term cycling of the Sn/C nanocomposite anodes showed 40% capacity loss after 500 cycles at 1C rate.

  7. The network control system of high-bay warehouse

    Directory of Open Access Journals (Sweden)

    Malaka Julian

    2017-01-01

    Full Text Available Presentation of developing a method of automation of the storage process using electric drives with frequency converters, logic control and communication in industrial networks was the main purpose of this article. A connection structure was proposed to exchange information between devices that are part of a high-storage warehouse. It was assumed that modern communication protocols are used to synchronize the drives and to create a central control and information center in the PLC. The results of theoretical considerations were applied in practice by performing a laboratory model of a high storage warehouse with a developed automatic control system. Benefits of the proposed solutions was shown in the conclusions.

  8. A novel excitatory network for the control of breathing

    Science.gov (United States)

    Anderson, Tatiana M.; Garcia, Alfredo J.; Baertsch, Nathan A.; Pollak, Julia; Bloom, Jacob C.; Wei, Aguan D.; Rai, Karan G.; Ramirez, Jan-Marino

    2017-01-01

    Breathing must be tightly coordinated with other behaviors such as vocalization, swallowing, and coughing. These behaviors occur after inspiration, during a respiratory phase termed postinspiration1. Failure to coordinate postinspiration with inspiration can result in aspiration pneumonia, the leading cause of death in Alzheimer’s disease, Parkinson’s disease, dementia, and other neurodegenerative diseases2. Here we describe an excitatory network that generates the neuronal correlate for postinspiratory activity. Glutamatergic-cholinergic neurons form the basis of this network, while GABAergic inhibition establishes the timing and coordination with inspiration. We refer to this novel network as the postinspiratory complex (PiCo). PiCo has autonomous rhythm generating properties and is necessary and sufficient for postinspiratory activity in vivo. PiCo also has distinct responses to neuromodulators when compared with other excitatory brainstem networks. Based on the discovery of PiCo we propose that each of the three phases of breathing is generated by a distinct excitatory network: The preBötzinger complex, which has been linked to inspiration3,4, the PiCo as described here for the neuronal control of postinspiration, and the Lateral parafacial region (pFL) which has been associated with active expiration, a respiratory phase recruited during high metabolic demand4,5,. PMID:27462817

  9. Evaluating network-level predictors of behavior change among injection networks enrolled in the HPTN 037 randomized controlled trial.

    Science.gov (United States)

    Smith, Laramie R; Strathdee, Steffanie A; Metzger, David; Latkin, Carl

    2017-06-01

    Little is known about ways network-level factors that may influence the adoption of combination prevention behaviors among injection networks, or how network-oriented interventions might moderate this behavior change process. A total of 232 unique injection risk networks in Philadelphia, PA, were randomized to a peer educator network-oriented intervention or standard of care control arm. Network-level aggregates reflecting the injection networks' baseline substance use dynamics, social interactions, and the networks exposure to gender- and structural-related vulnerabilities were calculated and used to predict changes in the proportion of network members adopting safer injection practices at 6-month follow-up. At follow-up, safer injection practices were observed among 46.31% of a network's members on average. In contrast, 25.7% of networks observed no change. Controlling for the effects of the intervention, significant network-level factors influencing network-level behavior change reflected larger sized injection networks (b=2.20, p=0.013) with a greater proportion of members who shared needles (b=0.29, pnetwork's safer injection practices were also observed for networks with fewer new network members (b=-0.31, p=0.008), and for networks whose members were proportionally less likely to have experienced incarceration (b=-0.20, p=0.012) or more likely to have been exposed to drug treatment (b=0.17, p=0.034) in the 6-months prior to baseline. A significant interaction suggested the intervention uniquely facilitated change in safer injection practices among female-only networks (b=-0.32, p=0.046). Network-level factors offer insights into ways injection networks might be leveraged to promote combination prevention efforts. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Network-Cognizant Voltage Droop Control for Distribution Grids

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Kyri; Bernstein, Andrey; Dall' Anese, Emiliano; Zhao, Changhong

    2017-01-01

    This paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on the effect of DER power adjustments on the overall voltage profile. A robust approach is pursued to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.

  11. Analog neural network control method proposed for use in a backup satellite control mode

    Energy Technology Data Exchange (ETDEWEB)

    Frigo, J.R.; Tilden, M.W.

    1998-03-01

    The authors propose to use an analog neural network controller implemented in hardware, independent of the active control system, for use in a satellite backup control mode. The controller uses coarse sun sensor inputs. The field of view of the sensors activate the neural controller, creating an analog dead band with respect to the direction of the sun on each axis. This network controls the orientation of the vehicle toward the sunlight to ensure adequate power for the system. The attitude of the spacecraft is stabilized with respect to the ambient magnetic field on orbit. This paper develops a model of the controller using real-time coarse sun sensor data and a dynamic model of a prototype system based on a satellite system. The simulation results and the feasibility of this control method for use in a satellite backup control mode are discussed.

  12. A Survey of Access Control Models in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Htoo Aung Maw

    2014-06-01

    Full Text Available Wireless sensor networks (WSNs have attracted considerable interest in the research community, because of their wide range of applications. However, due to the distributed nature of WSNs and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. Resource constraints in sensor nodes mean that security mechanisms with a large overhead of computation and communication are impractical to use in WSNs; security in sensor networks is, therefore, a challenge. Access control is a critical security service that offers the appropriate access privileges to legitimate users and prevents illegitimate users from unauthorized access. However, access control has not received much attention in the context of WSNs. This paper provides an overview of security threats and attacks, outlines the security requirements and presents a state-of-the-art survey on access control models, including a comparison and evaluation based on their characteristics in WSNs. Potential challenging issues for access control schemes in WSNs are also discussed.

  13. Level Controlled Gossip Based Tsunami Warning Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Santosh BHIMA

    2009-07-01

    Full Text Available This paper deals with a warning system based on distributed sensor networks employing level controlled gossip. Level controlled gossip is a technique that is being proposed which employs leveling and gossiping together. This technique reduces the number of messages by transmitting messages in the direction of base station and thereby increasing the life time of sensor network. By using various power levels at base station the sensor field is hierarchically partitioned into levels of increasing radius (containing various sensor nodes. The algorithm divides the entire sensor network into logical concentric zones based on proximity from the base station, whereby the packet is transmitted from a node of higher depth to nodes in the next zone with lesser depth. The transmission probability increases with the proximity of the Tsunami wave to the base station. The primary advantage of the protocol is transmitting a critical event with higher probability and at the same time conserving life time of the network for future monitoring.

  14. Towards resolving the transcription factor network controlling myelin gene expression.

    Science.gov (United States)

    Fulton, Debra L; Denarier, Eric; Friedman, Hana C; Wasserman, Wyeth W; Peterson, Alan C

    2011-10-01

    In the central nervous system (CNS), myelin is produced from spirally-wrapped oligodendrocyte plasma membrane and, as exemplified by the debilitating effects of inherited or acquired myelin abnormalities in diseases such as multiple sclerosis, it plays a critical role in nervous system function. Myelin sheath production coincides with rapid up-regulation of numerous genes. The complexity of their subsequent expression patterns, along with recently recognized heterogeneity within the oligodendrocyte lineage, suggest that the regulatory networks controlling such genes drive multiple context-specific transcriptional programs. Conferring this nuanced level of control likely involves a large repertoire of interacting transcription factors (TFs). Here, we combined novel strategies of computational sequence analyses with in vivo functional analysis to establish a TF network model of coordinate myelin-associated gene transcription. Notably, the network model captures regulatory DNA elements and TFs known to regulate oligodendrocyte myelin gene transcription and/or oligodendrocyte development, thereby validating our approach. Further, it links to numerous TFs with previously unsuspected roles in CNS myelination and suggests collaborative relationships amongst both known and novel TFs, thus providing deeper insight into the myelin gene transcriptional network.

  15. Automated large-scale control of gene regulatory networks.

    Science.gov (United States)

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

    Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem (FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.

  16. 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.

  17. Application of Fuzzy-Logic Controller and Neural Networks Controller in Gas Turbine Speed Control and Overheating Control and Surge Control on Transient Performance

    Science.gov (United States)

    Torghabeh, A. A.; Tousi, A. M.

    2007-08-01

    This paper presents Fuzzy Logic and Neural Networks approach to Gas Turbine Fuel schedules. Modeling of non-linear system using feed forward artificial Neural Networks using data generated by a simulated gas turbine program is introduced. Two artificial Neural Networks are used , depicting the non-linear relationship between gas generator speed and fuel flow, and turbine inlet temperature and fuel flow respectively . Off-line fast simulations are used for engine controller design for turbojet engine based on repeated simulation. The Mamdani and Sugeno models are used to expression the Fuzzy system . The linguistic Fuzzy rules and membership functions are presents and a Fuzzy controller will be proposed to provide an Open-Loop control for the gas turbine engine during acceleration and deceleration . MATLAB Simulink was used to apply the Fuzzy Logic and Neural Networks analysis. Both systems were able to approximate functions characterizing the acceleration and deceleration schedules . Surge and Flame-out avoidance during acceleration and deceleration phases are then checked . Turbine Inlet Temperature also checked and controls by Neural Networks controller. This Fuzzy Logic and Neural Network Controllers output results are validated and evaluated by GSP software . The validation results are used to evaluate the generalization ability of these artificial Neural Networks and Fuzzy Logic controllers.

  18. Capacity Limit, Link Scheduling and Power Control in Wireless Networks

    Science.gov (United States)

    Zhou, Shan

    2013-01-01

    The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…

  19. 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.

  20. Active defense scheme against DDoS based on mobile agent and network control in network confrontation

    Science.gov (United States)

    Luo, Rong; Li, Junshan; Ye, Xia; Wang, Rui

    2013-03-01

    In order to effective defend DDoS attacks in network confrontation, an active defense scheme against DDoS is built based on Mobile Agent and network control. A distributed collaborative active defense model is constructed by using mobile agent technology and encapsulating a variety of DDoS defense techniques. Meanwhile the network control theory is applied to establish a network confrontation's control model for DDoS to control the active defense process. It provides a new idea to solve the DDoS problem.

  1. Neural Network Control for a Batch Distillation Column

    Directory of Open Access Journals (Sweden)

    Duraid Fadhil Ahmed

    2016-07-01

    Full Text Available The  present  work  deals  with  studying  the  dynamic  behavior  of  a  batch  distillation  column  and implemented  two  types  of  control  strategies  for  the  separation  different  types  of  binary  systems.  The model  was  derived  and  then  simulated  using  "MATLAB"  program.  The  experimental  data  of  dynamic behavior  were  to  tune  the  parameters  of  PID  controller  and  developed  the  training  of  neural  networks controller by using supervised  learning algorithms. The simulation results show a qualitatively acceptable behavior.  This  study  shows  also  that  the  response  of  PID  controller  was  oscillatory  behavior  with  high offset value while neural network controller gave less offset value and less  time to reach the steady state. In general, a good improvement is achieved when the  neural network controller  is used compared with PID control.

  2. A Framework and Comparative Analysis of Control Plane Security of SDN and Conventional Networks

    OpenAIRE

    Abdou, AbdelRahman; van Oorschot, Paul C.; Wan, Tao

    2017-01-01

    Software defined networking implements the network control plane in an external entity, rather than in each individual device as in conventional networks. This architectural difference implies a different design for control functions necessary for essential network properties, e.g., loop prevention and link redundancy. We explore how such differences redefine the security weaknesses in the SDN control plane and provide a framework for comparative analysis which focuses on essential network pr...

  3. Gene networks controlling the initiation of flower development.

    Science.gov (United States)

    Wellmer, Frank; Riechmann, José L

    2010-12-01

    The onset of flower formation is a key regulatory event during the life cycle of angiosperm plants, which marks the beginning of the reproductive phase of development. It has been shown that floral initiation is under tight genetic control, and deciphering the underlying molecular mechanisms has been a main area of interest in plant biology for the past two decades. Here, we provide an overview of the developmental and genetic processes that occur during floral initiation. We further review recent studies that have led to the genome-wide identification of target genes of key floral regulators and discuss how they have contributed to an in-depth understanding of the gene regulatory networks controlling early flower development. We focus especially on a master regulator of floral initiation in Arabidopsis thaliana APETALA1 (AP1), but also outline what is known about the AP1 network in other plant species and the evolutionary implications. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. Diagnostics and control of pressurized reactors using artificial neural networks

    Science.gov (United States)

    Ikonomopoulos, Andreas; Tsoukalas, Lefteri H.; Uhrig, Robert E.

    1992-09-01

    A methodology employing artificial neural networks and fuzzy arithmetic in the diagnosis and control of complex systems such as pressurized water reactors is presented. Fuzzy numbers represent the linguistic values of plant-specific variables, e.g., performance or availability. The notion of a virtual instrument, i.e., a software-based measuring device calibrated to the idiosyncrasies of a specific system is used. Neural networks perform a mapping of physically measurable parameters to fuzzy numbers called Virtual Measurement Values (VMV). The methodology is tested with start-up data from an experimental nuclear reactor. The results demonstrate the very good capacity of such virtual instruments for failure-tolerance and suggest the possibility of developing alternative algorithms for diagnostics and control.

  5. Control capacity and a random sampling method in exploring controllability of complex networks.

    Science.gov (United States)

    Jia, Tao; Barabási, Albert-László

    2013-01-01

    Controlling complex systems is a fundamental challenge of network science. Recent advances indicate that control over the system can be achieved through a minimum driver node set (MDS). The existence of multiple MDS's suggests that nodes do not participate in control equally, prompting us to quantify their participations. Here we introduce control capacity quantifying the likelihood that a node is a driver node. To efficiently measure this quantity, we develop a random sampling algorithm. This algorithm not only provides a statistical estimate of the control capacity, but also bridges the gap between multiple microscopic control configurations and macroscopic properties of the network under control. We demonstrate that the possibility of being a driver node decreases with a node's in-degree and is independent of its out-degree. Given the inherent multiplicity of MDS's, our findings offer tools to explore control in various complex systems.

  6. 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

  7. Simulasi Virtual Local Area Network (VLAN Berbasis Software Defined Network (SDN Menggunakan POX Controller

    Directory of Open Access Journals (Sweden)

    Rohmat Tulloh

    2015-11-01

    Full Text Available VLAN (Virtual LAN merupakan sebuah teknologi yang dapat mengkonfigurasi jaringan logis independen dari struktur jaringan fisik. Hasil dari penelitian sebelumnya sudah diprediksi bahwa dibutuhkan Virtual Network yang akhirnya terciptalah VLAN. Namun paradigma jaringan saat ini tidak flexible, ketergantungan terhadap vendor sangat besar karena fungsi data plane dan control plane berada dalam satu paket device. SDN (Software defined network yang merupakan salahsatu evolusi teknologi jaringan sesuai dengan tuntutan yang berkembang dimana memisahkan fungsi data plane dan control plane pada suatu perangkat. POX Controller digunakan untuk men-simulasikan dan menguji Platform SDN (Software defined network. Pada penelitian ini menggunakan Openflow versi 1.0 untuk memasang header VLAN sehingga penelitian ini difokuskan untuk mengevaluasi performa forwarding VLAN yang memanfaatkan Openflow sebagai control plane dapat berfungsi dengan baik. Hasil penelitian ini mengusulkan penerapan karakteristik teknologi VLAN pada SDN karena telah berjalan dengan benar sesuai hasil pengujian konektifitas, verifikasi dan keamanan. Kemudian hasil pengujian lanjutan untuk melihat pengaruh SDN dengan skenario penambahan jumlah VLAN ID didapatkan bahwa set-up time akan bertambah seiring meningkatnya jumlah host dan dengan menggunakan protokol OpenFlow, latency yang terjadi di jaringan dapat dipantau dengan parameter round trip time (RTT yang stabil direntang 0,2 sampai 6 second walaupun jumlah vlan_id dan background traffic bertambah.

  8. Acute aerobic exercise alters executive control network in preadolescent children

    OpenAIRE

    Chen, Ai-Guo

    2017-01-01

    The present study aimed to investigate the effect of acute aerobic exercise on executive function (EF) and executive control network (ECN) in preadolescent children, and further explored the neural basis of acute aerobic exercise on EF in these children. We used a within-subjects design with a counterbalanced order. Nine healthy, right-handed children were scanned with resting-state functional magnetic resonance imaging and performed an EF task both in baseline session and exercise session. T...

  9. Parental control of children using the internet and social networks

    OpenAIRE

    Zuković Slađana; Slijepčević Senka

    2015-01-01

    The paper starts from the standpoint that the expansion of the Internet imposes a need for instructing the parents to adequately guide children to use safely this virtual space. That is why we present the results of an empirical research, aimed at establishing how parents control the behaviour of their children on the Internet and social networks. The research was conducted on a sample of 105 parents of the sixth grade elementary school pupils, and the applied questionnaire was construed for ...

  10. On a multi-channel stochastic network with controlled input

    Science.gov (United States)

    Livinska, Hanna; Lebedev, Eugene

    2017-06-01

    In this paper stationary properties of queueing network of the type [M|M|∞]r are investigated provided that the input flow is controlled by a Markov chain. We consider two cases. In the one-dimensional case a generating function of the stationary distribution is obtained. The form of the generating function is a matrix version of the well-known Takasc formula. For a multivariate service process the condition of a stationary regime existence and a correlation matrix are found.

  11. Novel methods of utilizing Jitter for Network Congestion Control

    Directory of Open Access Journals (Sweden)

    Ivan

    2013-12-01

    Full Text Available This paper proposes a novel paradigm for network congestion control. Instead of perpetual conflict as in TCP, a proof-of-concept first-ever protocol enabling inter-flow communication without infrastructure support thru a side channel constructed on generic FIFO queue behaviour is presented. This enables independent flows passing thru the same bottleneck queue to communicate and achieve fair capacity sharing and a stable equilibrium state in a rapid fashion.

  12. Control Capacity and A Random Sampling Method in Exploring Controllability of Complex Networks

    OpenAIRE

    Jia, Tao; Barab?si, Albert-L?szl?

    2013-01-01

    Controlling complex systems is a fundamental challenge of network science. Recent advances indicate that control over the system can be achieved through a minimum driver node set (MDS). The existence of multiple MDS's suggests that nodes do not participate in control equally, prompting us to quantify their participations. Here we introduce control capacity quantifying the likelihood that a node is a driver node. To efficiently measure this quantity, we develop a random sampling algorithm. Thi...

  13. Resilient Wireless Sensor Networks Using Topology Control: A Review

    Science.gov (United States)

    Huang, Yuanjiang; Martínez, José-Fernán; Sendra, Juana; López, Lourdes

    2015-01-01

    Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs. PMID:26404272

  14. A survey of trust, control and information in networks

    DEFF Research Database (Denmark)

    Jakobsen, Morten

    This paper focuses on which characteristics managers take into account when they choose and evaluate business partners, and the interrelationship between the constructs trust, control and information. The paper is based on a survey which includes 101 small and middle-sized manufacturing companies...... in Denmark. The results show that managers frequently express that trust is an important aspect of a good relationship. Also product-related attributes and relational attributes have a bearing in a network setting. On the other hand, no significant correlation between neither trust and control nor trust...

  15. Qualitative analysis and control of complex neural networks with delays

    CERN Document Server

    Wang, Zhanshan; Zheng, Chengde

    2016-01-01

    This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.

  16. Improved methods in neural network-based adaptive output feedback control, with applications to flight control

    Science.gov (United States)

    Kim, Nakwan

    Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

  17. Dynamic Cooperative Clustering Based Power Assignment: Network Capacity and Lifetime Efficient Topology Control in Cooperative Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Xiao-Hong Li

    2014-01-01

    Full Text Available Cooperative communication (CC is used in topology control as it can reduce the transmission power and expand the transmission range. However, all previous research on topology control under the CC model focused on maintaining network connectivity and minimizing the total energy consumption, which would lead to low network capacity, transmission interruption, or even network paralysis. Meanwhile, without considering the balance of energy consumption in the network, it would reduce the network lifetime and greatly affect the network performance. This paper tries to solve the above problems existing in the research on topology control under the CC model by proposing a power assignment (DCCPA algorithm based on dynamic cooperative clustering in cooperative ad hoc networks. The new algorithm clusters the network to maximize network capacity and makes the clusters communicate with each other by CC. To reduce the number of redundant links between clusters, we design a static clustering method by using Kruskal algorithm. To maximize the network lifetime, we also propose a cluster head rotating method which can reach a good tradeoff between residual energy and distance for the cluster head reselection. Experimental results show that DCCPA can improve 80% network capacity with Cooperative Bridges algorithm; meanwhile, it can improve 20% network lifetime.

  18. Development of cognitive and affective control networks and decision making.

    Science.gov (United States)

    Kar, Bhoomika R; Vijay, Nivita; Mishra, Shreyasi

    2013-01-01

    Cognitive control and decision making are two important research areas in the realm of higher-order cognition. Control processes such as interference control and monitoring in cognitive and affective contexts have been found to influence the process of decision making. Development of control processes follows a gradual growth pattern associated with the prolonged maturation of underlying neural circuits including the lateral prefrontal cortex, anterior cingulate, and the medial prefrontal cortex. These circuits are also involved in the control of processes that influences decision making, particularly with respect to choice behavior. Developmental studies on affective control have shown distinct patterns of brain activity with adolescents showing greater activation of amygdala whereas adults showing greater activity in ventral prefrontal cortex. Conflict detection, monitoring, and adaptation involve anticipation and subsequent performance adjustments which are also critical to complex decision making. We discuss the gradual developmental patterns observed in two of our studies on conflict monitoring and adaptation in affective and nonaffective contexts. Findings of these studies indicate the need to look at the differences in the effects of the development of cognitive and affective control on decision making in children and particularly adolescents. Neuroimaging studies have shown the involvement of separable neural networks for cognitive (medial prefrontal cortex and anterior cingulate) and affective control (amygdala, ventral medial prefrontal cortex) shows that one system can affect the other also at the neural level. Hence, an understanding of the interaction and balance between the cognitive and affective brain networks may be crucial for self-regulation and decision making during the developmental period, particularly late childhood and adolescence. The chapter highlights the need for empirical investigation on the interaction between the different aspects

  19. Learning anticipation via spiking networks: application to navigation control.

    Science.gov (United States)

    Arena, Paolo; Fortuna, Luigi; Frasca, Mattia; Patané, Luca

    2009-02-01

    In this paper, we introduce a network of spiking neurons devoted to navigation control. Three different examples, dealing with stimuli of increasing complexity, are investigated. In the first one, obstacle avoidance in a simulated robot is achieved through a network of spiking neurons. In the second example, a second layer is designed aiming to provide the robot with a target approaching system, making it able to move towards visual targets. Finally, a network of spiking neurons for navigation based on visual cues is introduced. In all cases, the robot was assumed to rely on some a priori known responses to low-level sensors (i.e., to contact sensors in the case of obstacles, to proximity target sensors in the case of visual targets, or to the visual target for navigation with visual cues). Based on their knowledge, the robot has to learn the response to high-level stimuli (i.e., range finder sensors or visual input). The biologically plausible paradigm of spike-timing-dependent plasticity (STDP) is included in the network to make the system able to learn high-level responses that guide navigation through a simple unstructured environment. The learning procedure is based on classical conditioning.

  20. Statistical process control using optimized neural networks: a case study.

    Science.gov (United States)

    Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

    2014-09-01

    The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  1. The Study of Maglev Train Control and Diagnosis Networks Based on Role Automation Decentralization

    National Research Council Canada - National Science Library

    LIU, Zhigang; WANG, Qi; TAN, Yongdong

    2008-01-01

    The control and diagnosis networks in Maglev Train are the most important parts. In the paper, the control and diagnosis network structures are discussed, and the disadvantages of them are described and analyzed...

  2. Messaging Performance of FIPA Interaction Protocols in Networked Embedded Controllers

    Directory of Open Access Journals (Sweden)

    Omar Jehovani López Orozco

    2007-12-01

    Full Text Available Agent-based technologies in production control systems could facilitate seamless reconfiguration and integration of mechatronic devices/modules into systems. Advances in embedded controllers which are continuously improving computational capabilities allow for software modularization and distribution of decisions. Agent platforms running on embedded controllers could hide the complexity of bootstrap and communication. Therefore, it is important to investigate the messaging performance of the agents whose main motivation is the resource allocation in manufacturing systems (i.e., conveyor system. The tests were implemented using the FIPA-compliant JADE-LEAP agent platform. Agent containers were distributed through networked embedded controllers, and agents were communicating using request and contract-net FIPA interaction protocols. The test scenarios are organized in intercontainer and intracontainer communications. The work shows the messaging performance for the different test scenarios using both interaction protocols.

  3. Polycyclic Aromatic Hydrocarbons in the Martian (SNC) Meteorite ALH 84001: Hydrocarbons from Mars, Terrestrial Contaminants, or Both?

    Science.gov (United States)

    Thomas, K. L.; Clemett, S. J.; Romanek, C. S.; Macheling, C. R.; Gibson, E. K.; McKay, D. S.; Score, R.; Zare, R. N.

    1995-09-01

    Previous work has shown that pre-terrestrial polycyclic aromatic hydrocarbons (PAHs) exist in interplanetary dust particles (IDPs) and certain meteorites [1-3]. We previously reported the first observation of PAHs in the newest member of the SNC group, Allan Hills 84001 [4] and determined that particular types of organic compounds are indigenous to ALH 84001 because they are associated with certain mineralogical features [4]. We also analyzed two diogenites from Antarctica: one showed no evidence for aromatic hydrocarbons while the other contained PAHs with the same major peaks as those in ALH 84001[4]. PAHs in the diogenite meteorite are not associated with mineral features on the analyzed surface and the most abundant PAHs in the diogenite are lower by a factor of 3 than those in ALH 84001. Furthermore, ALH 84001 contains a number of minor PAHs not found in the diogenite or typical terrestrial soils [4]. In this study we are analyzing a more complete group of Antarctic and non-Antarctic meteorites, including SNCs, to determine: (1) PAHs abundance and diversity in Antarctic meteorites and (2) the contribution of PAHs in SNCs from martian and, possibly, terrestrial sources. ALH 84001 is an unusual orthopyroxenite which contains abundant carbonate spheroids which are ~100-200 micrometers in diameter and range in composition from magnesite to ferroan magnesite [5-7]. These spheroids are not the result of terrestrial contamination: oxygen isotopic compositions indicate that the carbonates probably precipitated from a low-temperature fluid within the martian crust [5] and carbon isotopic abundances are consistent with martian atmospheric CO2 as the carbon source [5]. PAHs may coexist with other low-temperature carbon-bearing phases in a subsurface martian environment. Samples: We are analyzing freshly-fractured meteorite samples, or chips, which have been extracted from the internal regions of the following meteorites: ALH 84001 (crush and uncrush zones), EETA79001

  4. A molecular quantum spin network controlled by a single qubit.

    Science.gov (United States)

    Schlipf, Lukas; Oeckinghaus, Thomas; Xu, Kebiao; Dasari, Durga Bhaktavatsala Rao; Zappe, Andrea; de Oliveira, Felipe Fávaro; Kern, Bastian; Azarkh, Mykhailo; Drescher, Malte; Ternes, Markus; Kern, Klaus; Wrachtrup, Jörg; Finkler, Amit

    2017-08-01

    Scalable quantum technologies require an unprecedented combination of precision and complexity for designing stable structures of well-controllable quantum systems on the nanoscale. It is a challenging task to find a suitable elementary building block, of which a quantum network can be comprised in a scalable way. We present the working principle of such a basic unit, engineered using molecular chemistry, whose collective control and readout are executed using a nitrogen vacancy (NV) center in diamond. The basic unit we investigate is a synthetic polyproline with electron spins localized on attached molecular side groups separated by a few nanometers. We demonstrate the collective readout and coherent manipulation of very few (≤ 6) of these S = 1/2 electronic spin systems and access their direct dipolar coupling tensor. Our results show that it is feasible to use spin-labeled peptides as a resource for a molecular qubit-based network, while at the same time providing simple optical readout of single quantum states through NV magnetometry. This work lays the foundation for building arbitrary quantum networks using well-established chemistry methods, which has many applications ranging from mapping distances in single molecules to quantum information processing.

  5. Remote controlled gate controller using a GSM network and Arduino platform

    Directory of Open Access Journals (Sweden)

    Pospisilik Martin

    2016-01-01

    Full Text Available Most remote controllers for entrance gates operate on free frequencies 433 or 868 MHz. However, this technology limits the user comfort, as it is usually not common that bi-directional communication is established. A higher comfort of controlling the entrance gates can be achieved by employing the GSM network for transmission of commands and messages between the gate controller and the user. In this case, only a conventional GSM cellular phone is needed to control the gate. A description of such a controller based on the GSM module and Arduino controller is provided in this paper.

  6. A QoS-Oriented Congestion Control Mechanism for Satellite Networks

    OpenAIRE

    Heyu Liu; Fuchun Sun

    2014-01-01

    The sharply increasing amount of data, which are transferred by the satellite network, requires the satellite network to provide quality-of-service (QoS). However, the upsurge in the data flow leads to the network congestion, impeding its ability to offer QoS. Congestion control mechanisms, deployed in the ground networks, have been thoroughly studied. But those deployed in the satellite networks have not been studied yet. As satellite networks are now important supplements to the ground back...

  7. 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.

  8. Wearable Device Control Platform Technology for Network Application Development

    Directory of Open Access Journals (Sweden)

    Heejung Kim

    2016-01-01

    Full Text Available Application development platform is the most important environment in IT industry. There are a variety of platforms. Although the native development enables application to optimize, various languages and software development kits need to be acquired according to the device. The coexistence of smart devices and platforms has rendered the native development approach time and cost consuming. Cross-platform development emerged as a response to these issues. These platforms generate applications for multiple devices based on web languages. Nevertheless, development requires additional implementation based on a native language because of the coverage and functions of supported application programming interfaces (APIs. Wearable devices have recently attracted considerable attention. These devices only support Bluetooth-based interdevice communication, thereby making communication and device control impossible beyond a certain range. We propose Network Application Agent (NetApp-Agent in order to overcome issues. NetApp-Agent based on the Cordova is a wearable device control platform for the development of network applications, controls input/output functions of smartphones and wearable/IoT through the Cordova and Native API, and enables device control and information exchange by external users by offering a self-defined API. We confirmed the efficiency of the proposed platform through experiments and a qualitative assessment of its implementation.

  9. QTL list: snc7.1 [PGDBj Registered plant list, Marker list, QTL list, Plant DB link and Genome analysis methods[Archive

    Lifescience Database Archive (English)

    Full Text Available QT77164 Solanum lycopersicum Solanaceae snc7.1 Na+ concentrations in stems under s...alinity conditions the Na+ concentrations (mmole per Kg of dry weight) in stems 3,6 ... Chr07 23.01 44.82 ... 10.1007/s00122-008-0720-8 18251001

  10. QTL list: snc7.1 [PGDBj Registered plant list, Marker list, QTL list, Plant DB link and Genome analysis methods[Archive

    Lifescience Database Archive (English)

    Full Text Available QT77165 Solanum lycopersicum Solanaceae snc7.1 Na+ concentrations in stems under s...alinity conditions the Na+ concentrations (mmole per Kg of dry weight) in stems 3,6 ... Chr07 30.01 51.03 ... 10.1007/s00122-008-0720-8 18251001

  11. Model of nonhierarchical control in distributed sensor networks

    Science.gov (United States)

    Meinkoehn, Jens; Knoll, A.

    1992-11-01

    In this paper a model of lateral coordination control in sensor networks is proposed. It is based on the notion of negotiated cooperation between pairs of equal and autonomously acting sensor nodes. The actual communication phase is preceded by a bidding scheme to establish appropriate communication links. This model incorporates the aspect of network self- organization in order to adapt to changing environmental conditions. The cooperation is modelled on human behavior in the case of a task being worked on sequentially by team members with equal rights but different capabilities. To this end, a generalized approach to the organization of distributed systems is given and a cooperation protocol is described to achieve the desired lateral coordination. The qualitative reasoning is supplemented by simulation results to support the superiority of lateral over pure vertical coordination, particularly under severe environmental conditions, such as sensor failure.

  12. Non-Markovian quantum feedback networks II: Controlled flows

    Science.gov (United States)

    Gough, John E.

    2017-06-01

    The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering. In this paper, we build on the ideas presented by Bouten and van Handel [Quantum Stochastics and Information: Statistics, Filtering and Control (World Scientific, 2008)] and develop a general theory of quantum feedback. We elucidate the relationship between the controlling processes, Z, and the measured processes, Y, and to this end we make a distinction between what we call the input picture and the output picture. We should note that the input-output relations for the noise fields have additional terms not present in the standard theory but that the relationship between the control processes and measured processes themselves is internally consistent—we do this for the two main cases of quadrature measurement and photon-counting measurement. The theory is general enough to include a modulating filter which post-processes the measurement readout Y before returning to the system. This opens up the prospect of applying very general engineering feedback control techniques to open quantum systems in a systematic manner, and we consider a number of specific modulating filter problems. Finally, we give a brief argument as to why most of the rules for making instantaneous feedback connections [J. Gough and M. R. James, Commun. Math. Phys. 287, 1109 (2009)] ought to apply for controlled dynamical networks as well.

  13. Congestion control algorithms in wireless sensor networks: Trends and opportunities

    Directory of Open Access Journals (Sweden)

    Syed Afsar Shah

    2017-07-01

    Full Text Available Congestion control is an extremely important area within wireless sensor networks (WSN, where traffic becomes greater than the aggregated or individual capacity of the underlying channels. Therefore, special considerations are required to develop more sophisticated techniques to avoid, detect, and resolve congestion. The constrained resources of the WSN must be considered while devising such techniques to achieve the maximum throughput. Various approaches have been introduced in the past few years that include routing protocols aided with congestion detection and control mechanism, and dedicated congestion control protocols. In the former schemes, the congestion avoidance is performed by the sink node that causes topology reset and bulk traffic drop. As a consequence, the latter mentioned congestion control protocols addressing the congestion avoidance, detection, and resolution were introduced at the node level. In this paper, we explore mechanisms for controlling congestion in the WSNs and present a comparative study. The congestion control schemes are categorized as centralized with partial congestion control and distributed with dedicated congestion control.

  14. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

    Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

  15. 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.

  16. 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.

  17. Neural network output feedback control of robot formations.

    Science.gov (United States)

    Dierks, Travis; Jagannathan, Sarangapani

    2010-04-01

    In this paper, a combined kinematic/torque output feedback control law is developed for leader-follower-based formation control using backstepping to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers. A neural network (NN) is introduced to approximate the dynamics of the follower and its leader using online weight tuning. Furthermore, a novel NN observer is designed to estimate the linear and angular velocities of both the follower robot and its leader. It is shown, by using the Lyapunov theory, that the errors for the entire formation are uniformly ultimately bounded while relaxing the separation principle. In addition, the stability of the formation in the presence of obstacles, is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation are prevented. Numerical results are provided to verify the theoretical conjectures.

  18. Output feedback control of a quadrotor UAV using neural networks.

    Science.gov (United States)

    Dierks, Travis; Jagannathan, Sarangapani

    2010-01-01

    In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

  19. Design and Research on Automotive Controller Area Network Bus Analyzer

    Directory of Open Access Journals (Sweden)

    Hongwei CUI

    2014-03-01

    Full Text Available The detection method of automotive controller area network bus is researched in this paper. Failure identifying of CAN bus under different working conditions has been realized. In order to realizing intelligent failure diagnosis, data fusion means has been put forward in this paper. The composition of analysis and detection system is introduced. By analyzing and processing the data of CAN bus and sensors, work condition of automotive is achieved. Multi-pattern data fusion model and algorithm for failure diagnosis are researched. The analyzer and detection system designed in this paper can be applied to automotive fault analysis, troubleshooting and maintenance.

  20. Robust control of integrated motor-transmission powertrain system over controller area network for automotive applications

    Science.gov (United States)

    Zhu, Xiaoyuan; Zhang, Hui; Cao, Dongpu; Fang, Zongde

    2015-06-01

    Integrated motor-transmission (IMT) powertrain system with directly coupled motor and gearbox is a good choice for electric commercial vehicles (e.g., pure electric buses) due to its potential in motor size reduction and energy efficiency improvement. However, the controller design for powertrain oscillation damping becomes challenging due to the elimination of damping components. On the other hand, as controller area network (CAN) is commonly adopted in modern vehicle system, the network-induced time-varying delays that caused by bandwidth limitation will further lead to powertrain vibration or even destabilize the powertrain control system. Therefore, in this paper, a robust energy-to-peak controller is proposed for the IMT powertrain system to address the oscillation damping problem and also attenuate the external disturbance. The control law adopted here is based on a multivariable PI control, which ensures the applicability and performance of the proposed controller in engineering practice. With the linearized delay uncertainties characterized by polytopic inclusions, a delay-free closed-loop augmented system is established for the IMT powertrain system under discrete-time framework. The proposed controller design problem is then converted to a static output feedback (SOF) controller design problem where the feedback control gains are obtained by solving a set of linear matrix inequalities (LMIs). The effectiveness as well as robustness of the proposed controller is demonstrated by comparing its performance against that of a conventional PI controller.

  1. Control of 12-Cylinder Camless Engine with Neural Networks

    Directory of Open Access Journals (Sweden)

    Ashhab Moh’d Sami

    2017-01-01

    Full Text Available The 12-cyliner camless engine breathing process is modeled with artificial neural networks (ANN’s. The inputs to the net are the intake valve lift (IVL and intake valve closing timing (IVC whereas the output of the net is the cylinder air charge (CAC. The ANN is trained with data collected from an engine simulation model which is based on thermodynamics principles and calibrated against real engine data. A method for adapting single-output feed-forward neural networks is proposed and applied to the camless engine ANN model. As a consequence the overall 12-cyliner camless engine feedback controller is upgraded and the necessary changes are implemented in order to contain the adaptive neural network with the objective of tracking the cylinder air charge (driver’s torque demand while minimizing the pumping losses (increasing engine efficiency. All the needed measurements are extracted only from the two conventional and inexpensive sensors, namely, the mass air flow through the throttle body (MAF and the intake manifold absolute pressure (MAP sensors. The feedback controller’s capability is demonstrated through computer simulation.

  2. An Efficient Wireless Sensor Network for Industrial Monitoring and Control

    Directory of Open Access Journals (Sweden)

    Juan Aponte-Luis

    2018-01-01

    Full Text Available This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

  3. An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

    Science.gov (United States)

    Aponte-Luis, Juan; Gómez-Galán, Juan Antonio; Gómez-Bravo, Fernando; Sánchez-Raya, Manuel; Alcina-Espigado, Javier; Teixido-Rovira, Pedro Miguel

    2018-01-10

    This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

  4. Idiotypic immune networks in mobile-robot control.

    Science.gov (United States)

    Whitbrook, Amanda M; Aickelin, Uwe; Garibaldi, Jonathan M

    2007-12-01

    Jerne's idiotypic-network theory postulates that the immune response involves interantibody stimulation and suppression, as well as matching to antigens. The theory has proved the most popular artificial immune system (AIS) model for incorporation into behavior-based robotics, but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with nonidiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a reinforcement-learning (RL)-based control system is described, and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels, and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

  5. Evolution of Wireless Sensor Networks for Industrial Control

    Directory of Open Access Journals (Sweden)

    Arthur Low

    2013-05-01

    Full Text Available Technologies evolve in a process of gradual scientific change, but the commercial application of technologies is discontinuous. Managers interested in technology evolution can integrate these contrasting ideas using a powerful theoretical framework, based on the concept of punctuated equilibrium from evolutionary biology. The framework, which enables the differentiation of the technical evolution of a technology from its market application, is used in this article to compare the two standards for wireless sensor networks (WSN for industrial instrumentation and control: WirelessHART and ISA100.11a. The two WSN standards are the product of two different market contexts, which have selected different minimum viable technologies for evolution in their respective niches. Network security issues present some important selection criteria. Both WSN standards implement security countermeasures against localized wireless network attacks based on the application of the AES encryption standard, but some specific security threats – some local, others remotely launched – are only well-defended by the adoption of public-key cryptographic (PKC protocols, which only ISA100.11a supports. This article concludes that the mainstream market potential of the Internet has influenced the evolution of ISA100.11a and will continue to demand that each WSN standard evolve in ways that are difficult to predict.

  6. Mars Digital Image Model 2.1 Control Network

    Science.gov (United States)

    Archinal, B. A.; Kirk, R. L.; Duxbury, T. C.; Lee, E. M.; Sucharski, R.; Cook, D.

    2003-01-01

    USGS is currently preparing a new version of its global Mars digital image mosaic, which will be known as MDIM 2.1. As part of this process we are completing a new photogrammetric solution of the global Mars control network. This is an improved version of the network established earlier by RAND and USGS personnel, as partially described previously. MDIM 2.1 will have many improvements over earlier Viking Orbiter (VO) global mosaics. Geometrically, it will be an orthoimage product, draped on Mars Orbiter Laser Altimeter (MOLA) derived topography, thus accounting properly for the commonly oblique VO imagery. Through the network being described here it will be tied to the newly defined IAU/IAG 2000 Mars coordinate system via ties to MOLA data. Thus, MDIM 2.1 will provide complete global orthorectified imagery coverage of Mars at the resolution of 1/256 deg of MDIM 2.0, and be compatible with MOLA and other products produced in the current coordinate system.

  7. Rbfox2 controls autoregulation in RNA-binding protein networks.

    Science.gov (United States)

    Jangi, Mohini; Boutz, Paul L; Paul, Prakriti; Sharp, Phillip A

    2014-03-15

    The tight regulation of splicing networks is critical for organismal development. To maintain robust splicing patterns, many splicing factors autoregulate their expression through alternative splicing-coupled nonsense-mediated decay (AS-NMD). However, as negative autoregulation results in a self-limiting window of splicing factor expression, it is unknown how variations in steady-state protein levels can arise in different physiological contexts. Here, we demonstrate that Rbfox2 cross-regulates AS-NMD events within RNA-binding proteins to alter their expression. Using individual nucleotide-resolution cross-linking immunoprecipitation coupled to high-throughput sequencing (iCLIP) and mRNA sequencing, we identified >200 AS-NMD splicing events that are bound by Rbfox2 in mouse embryonic stem cells. These "silent" events are characterized by minimal apparent splicing changes but appreciable changes in gene expression upon Rbfox2 knockdown due to degradation of the NMD-inducing isoform. Nearly 70 of these AS-NMD events fall within genes encoding RNA-binding proteins, many of which are autoregulated. As with the coding splicing events that we found to be regulated by Rbfox2, silent splicing events are evolutionarily conserved and frequently contain the Rbfox2 consensus UGCAUG. Our findings uncover an unexpectedly broad and multilayer regulatory network controlled by Rbfox2 and offer an explanation for how autoregulatory splicing networks are tuned.

  8. Overflow control mechanism (OCM) for Ethernet passive optical networks (EPONs)

    Science.gov (United States)

    Hajduczenia, Marek; da Silva, Henrique J. A.; Monteiro, Paulo P.

    2007-05-01

    The nonfragmentable nature of Ethernet data frames, as well as operation of the priority oriented packet schedulers in the optical network units, in conjunction with heavy network load conditions and the lack of detailed knowledge about the queue's composition at the optical line terminal (OLT) level, result in the creation of upstream channel slot remainders. The existing methods, in the form of nonpreemptive packet schedulers and multithreshold reporting process defined vaguely by the IEEE 802.3-2005 standard, result in either increased packet delay or Ethernet passive optical network (EPON) system incompatibility, respectively, since threshold processing was never officially defined in the scope of the respective EPON standard. We propose an alternative approach, based on basic modifications of the standard and extended GATE multipoint control protocol data unit format and meaning, allowing for the OLT packet scheduling agent to grant always exactly the requested slot size, thus preventing creation of any upstream channel slot remainders. It is estimated that, on average, ˜3% of upstream channel bandwidth can be salvaged when slot remainders are absent in the upstream channel transmission.

  9. Microglia Control Neuronal Network Excitability via BDNF Signalling

    Directory of Open Access Journals (Sweden)

    Francesco Ferrini

    2013-01-01

    Full Text Available Microglia-neuron interactions play a crucial role in several neurological disorders characterized by altered neural network excitability, such as epilepsy and neuropathic pain. While a series of potential messengers have been postulated as substrates of the communication between microglia and neurons, including cytokines, purines, prostaglandins, and nitric oxide, the specific links between messengers, microglia, neuronal networks, and diseases have remained elusive. Brain-derived neurotrophic factor (BDNF released by microglia emerges as an exception in this riddle. Here, we review the current knowledge on the role played by microglial BDNF in controlling neuronal excitability by causing disinhibition. The efforts made by different laboratories during the last decade have collectively provided a robust mechanistic paradigm which elucidates the mechanisms involved in the synthesis and release of BDNF from microglia, the downstream TrkB-mediated signals in neurons, and the biophysical mechanism by which disinhibition occurs, via the downregulation of the K+-Cl− cotransporter KCC2, dysrupting Cl−homeostasis, and hence the strength of GABAA- and glycine receptor-mediated inhibition. The resulting altered network activity appears to explain several features of the associated pathologies. Targeting the molecular players involved in this canonical signaling pathway may lead to novel therapeutic approach for ameliorating a wide array of neural dysfunctions.

  10. Interactive control over a programmable computer network using a multi-touch surface

    NARCIS (Netherlands)

    Strijkers, R.J.; Muller, L.; Cristea, M.L.; Belleman, R.; de Laat, C.; Sloot, P.; Meijer, R.

    2009-01-01

    This article introduces the Interactive Network concept and describes the design and implementation of the first prototype. In an Interactive Network humans become an integral part of the control system to manage programmable networks and grid networks. The implementation consists of a multi-touch

  11. Probes for narcotic receptor mediated phenomena 22. Pt.1: Synthesis and characterization of optically pure [{sup 3}H](+)-4-[({alpha}R)-{alpha}-((2S,5R)-4-propyl-2,5-dimethyl-1-pi perazinyl)-3-methoxybenzyl]-N,N-diethylbenzamide, [{sup 3}H]SNC 121, a novel high affinity and selective ligand for delta opioid receptors

    Energy Technology Data Exchange (ETDEWEB)

    Calderon, S.N.; Bertha, C.M.; Rice, K.C. [National Inst. of Diabetes and Digestive and Kidney Diseases, Medicinal Chemistry Lab., Bethesda, MD (United States); Gutkind, J.S. [National Inst. of Dental Research, Bethesda, MD (United States); Heng Xu; Partilla, J.S.; Rothman, R.B. [National Inst. on Drug Abuse, Clinical Psychopharmacology Section, Baltimore, MD (United States)

    1996-09-01

    The synthesis of unlabelled and labelled SNC 121, a selective nonpeptide ligand for the delta opioid receptor is reported. [{sup 3}H]SNC 121 of specific activity of 26.8 Ci/mmol, was synthesized by catalytic tritiation of the optically pure precursor SNC 80. (author).

  12. Web based educational tool for neural network robot control

    Directory of Open Access Journals (Sweden)

    Jure Čas

    2007-05-01

    Full Text Available Abstract— This paper describes the application for teleoperations of the SCARA robot via the internet. The SCARA robot is used by students of mehatronics at the University of Maribor as a remote educational tool. The developed software consists of two parts i.e. the continuous neural network sliding mode controller (CNNSMC and the graphical user interface (GUI. Application is based on two well-known commercially available software packages i.e. MATLAB/Simulink and LabVIEW. Matlab/Simulink and the DSP2 Library for Simulink are used for control algorithm development, simulation and executable code generation. While this code is executing on the DSP-2 Roby controller and through the analog and digital I/O lines drives the real process, LabVIEW virtual instrument (VI, running on the PC, is used as a user front end. LabVIEW VI provides the ability for on-line parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation. The main advantage of a CNNSMC is the exploitation of its self-learning capability. When friction or an unexpected impediment occurs for example, the user of a remote application has no information about any changed robot dynamic and thus is unable to dispatch it manually. This is not a control problem anymore because, when a CNNSMC is used, any approximation of changed robot dynamic is estimated independently of the remote’s user. Index Terms—LabVIEW; Matlab/Simulink; Neural network control; remote educational tool; robotics

  13. 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.

  14. Neural network based optimal control of HVAC&R systems

    Science.gov (United States)

    Ning, Min

    Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the

  15. End-System Network Interface Controller for 100 Gb/s Wide Area Networks: Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Wen, Jesse [Acadia Optronics LLC, Rockville, MD (United States)

    2013-08-30

    In recent years, network bandwidth requirements have scaled multiple folds, pushing the need for the development of data exchange mechanisms at 100 Gb/s and beyond. High performance computing, climate modeling, large-scale storage, and collaborative scientific research are examples of applications that can greatly benefit by leveraging high bandwidth capabilities of the order of 100 Gb/s. Such requirements and advances in IEEE Ethernet standards, Optical Transport Unit4 (OTU4), and host-system interconnects demand a network infrastructure supporting throughput rates of the order of 100 Gb/s with a single wavelength. To address such a demand Acadia Optronics in collaboration with the University of New Mexico, proposed and developed a end-system Network Interface Controller (NIC) for the 100Gbps WANs. Acadia’s 100G NIC employs an FPGA based system with a high-performance processor interconnect (PCIe 3.0) and a high capacity optical transmission link (CXP) to provide data transmission at the rate of 100 Gbps.

  16. Energy-efficient power control for OFDMA cellular networks

    KAUST Repository

    Sboui, Lokman

    2016-12-24

    In this paper, we study the energy efficiency (EE) of orthogonal frequency-division multiple access (OFDMA) cellular networks. Our objective is to present a power allocation scheme that maximizes the EE of downlink communications. We propose a novel explicit expression of the optimal power allocation to each subcarrier. We also present the power control when the transmit power is limited by power budget constraint or/and minimal rate constraint and we highlight the occurrence of some transmission outage events depending on the constraints\\' parameters. In the numerical results, we show that our proposed power control improves the EE especially at high power budget regime and low minimal rate regime. In addition, we show that having a higher number of subcarriers enhances the OFDMA EE.

  17. Enhancing coherent transport in a photonic network using controllable decoherence

    Science.gov (United States)

    Biggerstaff, Devon N.; Heilmann, René; Zecevik, Aidan A.; Gräfe, Markus; Broome, Matthew A.; Fedrizzi, Alessandro; Nolte, Stefan; Szameit, Alexander; White, Andrew G.; Kassal, Ivan

    2016-04-01

    Transport phenomena on a quantum scale appear in a variety of systems, ranging from photosynthetic complexes to engineered quantum devices. It has been predicted that the efficiency of coherent transport can be enhanced through dynamic interaction between the system and a noisy environment. We report an experimental simulation of environment-assisted coherent transport, using an engineered network of laser-written waveguides, with relative energies and inter-waveguide couplings tailored to yield the desired Hamiltonian. Controllable-strength decoherence is simulated by broadening the bandwidth of the input illumination, yielding a significant increase in transport efficiency relative to the narrowband case. We show integrated optics to be suitable for simulating specific target Hamiltonians as well as open quantum systems with controllable loss and decoherence.

  18. Service-Aware Retransmission Control in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Nadhir Ben Halima

    2010-01-01

    Full Text Available This paper proposes a service-aware cross-layer approach between application/transport layers on the mobile terminal and link layer on the wireless base station to enable dynamic control on the level of per-packet error protection for multimedia data streams. Specifically, in the context of cellular networks, the proposed scheme enables the mobile terminal to specify to the base station the desired level of Hybrid ARQ (HARQ protection by using an in-band control feedback channel. Such protection is dynamically adapted on a per-packet basis and depends on the perceptual importance of different packets as well as on the reception history of the flow. Experimental results demonstrate the potential benefits deriving from the proposed strategy either for audio and video real-time streams as well as for TCP-based data transfers.

  19. Wireless Network Control with Privacy Using Hybrid ARQ

    CERN Document Server

    Sarikaya, Yunus; Koksal, Emre C

    2012-01-01

    We consider the problem of resource allocation in a wireless cellular network, in which nodes have both open and private information to be transmitted to the base station over block fading uplink channels. We develop a cross-layer solution, based on hybrid ARQ transmission with incremental redundancy. We provide a scheme that combines power control, flow control, and scheduling in order to maximize a global utility function, subject to the stability of the data queues, an average power constraint, and a constraint on the privacy outage probability. Our scheme is based on the assumption that each node has an estimate of its uplink channel gain at each block, while only the distribution of the cross channel gains is available. We prove that our scheme achieves a utility, arbitrarily close to the maximum achievable utility given the available channel state information.

  20. Synchronization control for large-scale network systems

    CERN Document Server

    Wu, Yuanqing; Su, Hongye; Shi, Peng; Wu, Zheng-Guang

    2017-01-01

    This book provides recent advances in analysis and synthesis of Large-scale network systems (LSNSs) with sampled-data communication and non-identical nodes. In its first chapter of the book presents an introduction to Synchronization of LSNSs and Algebraic Graph Theory as well as an overview of recent developments of LSNSs with sampled data control or output regulation control. The main text of the book is organized into two main parts - Part I: LSNSs with sampled-data communication and Part II: LSNSs with non-identical nodes. This monograph provides up-to-date advances and some recent developments in the analysis and synthesis issues for LSNSs with sampled-data communication and non-identical nodes. It describes the constructions of the adaptive reference generators in the first stage and the robust regulators in the second stage. Examples are presented to show the effectiveness of the proposed design techniques.

  1. Wireless Plug and Play Control Systems: Hardware, Networks, and Protocols

    DEFF Research Database (Denmark)

    Meybodi, Soroush Afkhami

    2012-01-01

    D project are presented in two distinct areas which are: 1) Signal propagation in underground and confined areas, and 2) Access and Networking protocols that accommodate the required flexibility, scalability, and quality of services for plug and play control systems. The first category finds application...... the damp soil medium. To overcome the challenge, all potentially useful signal propagation methods are surveyed either by reviewing the open literature, or by doing simulations, or even running experiments. At the end, Magnetic Induction (MI) is chosen as the winning candidate. New findings are achieved...... in antenna design of magneto-inductive communication systems. They are verified by simulations and experiments. It is shown, via simulations, that MI is a reliable signal propagation technique for the full-scale case study: Distributed Control of the New Generation of District Heating Systems...

  2. Network-Cognizant Design of Decentralized Volt/VAR Controllers

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Kyri A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bernstein, Andrey [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-10-03

    This paper considers the problem of designing decentralized Volt/VAR controllers for distributed energy resources (DERs). The voltage-reactive power characteristics of individual DERs are obtained by solving a convex optimization problem, where given performance objectives (e.g., minimization of the voltage deviations from a given profile) are specified and stability constraints are enforced. The resultant Volt/VAR characteristics are network-cognizant, in the sense that they embed information on the location of the DERs and, consequently, on the effect of reactive-power adjustments on the voltages throughout the feeder. Bounds on the maximum voltage deviation incurred by the controllers are analytically established. Numerical results are reported to corroborate the technical findings.

  3. Optimal control of metabolic networks with saturable enzyme kinetics.

    Science.gov (United States)

    Oyarzuun, D A

    2011-03-01

    This note addresses the optimal control of non-linear metabolic networks by means of time-dependent enzyme synthesis rates. The authors consider networks with general topologies described by a control-affine dynamical system coupled with a linear model for enzyme synthesis and degradation. The problem formulation accounts for transitions between two metabolic equilibria, which typically arise in metabolic adaptations to environmental changes, and the minimisation of a quadratic functional that weights the cost/benefit relation between the transcriptional effort required for enzyme synthesis and the transition to the new phenotype. Using a linear time-variant approximation of the non-linear dynamics, the problem is recast as a sequence of linear-quadratic problems, the solution of which involves a sequence of differential Lyapunov equations. The authors provide conditions for convergence to an approximate solution of the original problem, which are naturally satisfied by a wide class of models for saturable enzyme kinetics. As a case study the authors use the method to examine the robustness of an optimal just-in-time gene expression pattern with respect to heterogeneity in the biosynthetic costs of individual proteins.

  4. 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

  5. Dynamic Resource Allocation and QoS Control Capabilities of the Japanese Academic Backbone Network

    Directory of Open Access Journals (Sweden)

    Michihiro Aoki

    2010-08-01

    Full Text Available Dynamic resource control capabilities have become increasingly important for academic networks that must support big scientific research projects at the same time as less data intensive research and educational activities. This paper describes the dynamic resource allocation and QoS control capabilities of the Japanese academic backbone network, called SINET3, which supports a variety of academic applications with a wide range of network services. The article describes the network architecture, networking technologies, resource allocation, QoS control, and layer-1 bandwidth on-demand services. It also details typical services developed for scientific research, including the user interface, resource control, and management functions, and includes performance evaluations.

  6. Neural network based adaptive output feedback control: Applications and improvements

    Science.gov (United States)

    Kutay, Ali Turker

    Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in

  7. Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial.

    Science.gov (United States)

    Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Creswell, J David

    Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown. Here, we test whether mindfulness training interventions foster executive control by strengthening functional connections between dorsolateral prefrontal cortex (dlPFC)-a hub of the executive control network-and frontoparietal regions that coordinate executive function. Thirty-five adults with elevated levels of psychological distress participated in a 3-day randomized controlled trial of intensive mindfulness meditation or relaxation training. Participants completed a resting state functional magnetic resonance imaging scan before and after the intervention. We tested whether mindfulness meditation training increased resting state functional connectivity (rsFC) between dlPFC and frontoparietal control network regions. Left dlPFC showed increased connectivity to the right inferior frontal gyrus (T = 3.74), right middle frontal gyrus (MFG) (T = 3.98), right supplementary eye field (T = 4.29), right parietal cortex (T = 4.44), and left middle temporal gyrus (T = 3.97, all p < .05) after mindfulness training relative to the relaxation control. Right dlPFC showed increased connectivity to right MFG (T = 4.97, p < .05). We report that mindfulness training increases rsFC between dlPFC and dorsal network (superior parietal lobule, supplementary eye field, MFG) and ventral network (right IFG, middle temporal/angular gyrus) regions. These findings extend previous work showing increased functional connectivity among brain regions associated with executive function during active meditation by identifying specific neural circuits in which rsFC is enhanced by a mindfulness intervention in individuals with high levels of psychological distress. Clinicaltrials.gov,NCT01628809.

  8. A biologically inspired neural network controller for ballistic arm movements

    Directory of Open Access Journals (Sweden)

    Schmid Maurizio

    2007-09-01

    Full Text Available Abstract Background In humans, the implementation of multijoint tasks of the arm implies a highly complex integration of sensory information, sensorimotor transformations and motor planning. Computational models can be profitably used to better understand the mechanisms sub-serving motor control, thus providing useful perspectives and investigating different control hypotheses. To this purpose, the use of Artificial Neural Networks has been proposed to represent and interpret the movement of upper limb. In this paper, a neural network approach to the modelling of the motor control of a human arm during planar ballistic movements is presented. Methods The developed system is composed of three main computational blocks: 1 a parallel distributed learning scheme that aims at simulating the internal inverse model in the trajectory formation process; 2 a pulse generator, which is responsible for the creation of muscular synergies; and 3 a limb model based on two joints (two degrees of freedom and six muscle-like actuators, that can accommodate for the biomechanical parameters of the arm. The learning paradigm of the neural controller is based on a pure exploration of the working space with no feedback signal. Kinematics provided by the system have been compared with those obtained in literature from experimental data of humans. Results The model reproduces kinematics of arm movements, with bell-shaped wrist velocity profiles and approximately straight trajectories, and gives rise to the generation of synergies for the execution of movements. The model allows achieving amplitude and direction errors of respectively 0.52 cm and 0.2 radians. Curvature values are similar to those encountered in experimental measures with humans. The neural controller also manages environmental modifications such as the insertion of different force fields acting on the end-effector. Conclusion The proposed system has been shown to properly simulate the development of

  9. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

    National Research Council Canada - National Science Library

    Antonio Artuñedo; Raúl M del Toro; Rodolfo E Haber

    2017-01-01

    .... The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks...

  10. Optimal dynamics for quality control in spatially distributed mitochondrial networks.

    Directory of Open Access Journals (Sweden)

    Pinkesh K Patel

    Full Text Available Recent imaging studies of mitochondrial dynamics have implicated a cycle of fusion, fission, and autophagy in the quality control of mitochondrial function by selectively increasing the membrane potential of some mitochondria at the expense of the turnover of others. This complex, dynamical system creates spatially distributed networks that are dependent on active transport along cytoskeletal networks and on protein import leading to biogenesis. To study the relative impacts of local interactions between neighboring mitochondria and their reorganization via transport, we have developed a spatiotemporal mathematical model encompassing all of these processes in which we focus on the dynamics of a health parameter meant to mimic the functional state of mitochondria. In agreement with previous models, we show that both autophagy and the generation of membrane potential asymmetry following a fusion/fission cycle are required for maintaining a healthy mitochondrial population. This health maintenance is affected by mitochondrial density and motility primarily through changes in the frequency of fusion events. Health is optimized when the selectivity thresholds for fusion and fission are matched, providing a mechanistic basis for the observed coupling of the two processes through the protein OPA1. We also demonstrate that the discreteness of the components exchanged during fusion is critical for quality control, and that the effects of limiting total amounts of autophagy and biogenesis have distinct consequences on health and population size, respectively. Taken together, our results show that several general principles emerge from the complexity of the quality control cycle that can be used to focus and interpret future experimental studies, and our modeling framework provides a road-map for deconstructing the functional importance of local interactions in communities of cells as well as organelles.

  11. Optimization of a neural network based direct inverse control for controlling a quadrotor unmanned aerial vehicle

    Directory of Open Access Journals (Sweden)

    Heryanto M Ary

    2015-01-01

    Full Text Available UAVs are mostly used for surveillance, inspection and data acquisition. We have developed a Quadrotor UAV that is constructed based on a four motors with a lift-generating propeller at each motors. In this paper, we discuss the development of a quadrotor and its neural networks direct inverse control model using the actual flight data. To obtain a better performance of the control system of the UAV, we proposed an Optimized Direct Inverse controller based on re-training the neural networks with the new data generated from optimal maneuvers of the quadrotor. Through simulation of the quadrotor using the developed DIC and Optimized DIC model, results show that both models have the ability to stabilize the quadrotor with a good tracking performance. The optimized DIC model, however, has shown a better performance, especially in the settling time parameter.

  12. Composite learning from adaptive backstepping neural network control.

    Science.gov (United States)

    Pan, Yongping; Sun, Tairen; Liu, Yiqi; Yu, Haoyong

    2017-11-01

    In existing neural network (NN) learning control methods, the trajectory of NN inputs must be recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN parameter convergence is obtainable. This paper focuses on command-filtered backstepping adaptive control for a class of strict-feedback nonlinear systems with functional uncertainties, where an NN composite learning technique is proposed to guarantee convergence of NN weights to their ideal values without the PE condition. In the NN composite learning, spatially localized NN approximation is employed to handle functional uncertainties, online historical data together with instantaneous data are exploited to generate prediction errors, and both tracking errors and prediction errors are employed to update NN weights. The influence of NN approximation errors on the control performance is also clearly shown. The distinctive feature of the proposed NN composite learning is that NN parameter convergence is guaranteed without the requirement of the trajectory of NN inputs being recurrent. Illustrative results have verified effectiveness and superiority of the proposed method compared with existing NN learning control methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Comparative Study between Robust Control of Robotic Manipulators by Static and Dynamic Neural Networks

    OpenAIRE

    Ghrab, Nadya; Kallel, Hichem

    2013-01-01

    A comparative study between static and dynamic neural networks for robotic systems control is considered. So, two approaches of neural robot control were selected, exposed, and compared. One uses a static neural network; the other uses a dynamic neural network. Both compensate the nonlinear modeling and uncertainties of robotic systems. The first approach is direct; it approximates the nonlinearities and uncertainties by a static neural network. The second approach is indirect; it uses a dyna...

  14. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  15. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Directory of Open Access Journals (Sweden)

    Axel Hutt

    Full Text Available Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  16. Parental control of children using the internet and social networks

    Directory of Open Access Journals (Sweden)

    Zuković Slađana

    2015-01-01

    Full Text Available The paper starts from the standpoint that the expansion of the Internet imposes a need for instructing the parents to adequately guide children to use safely this virtual space. That is why we present the results of an empirical research, aimed at establishing how parents control the behaviour of their children on the Internet and social networks. The research was conducted on a sample of 105 parents of the sixth grade elementary school pupils, and the applied questionnaire was construed for this occasion. The obtained results show that the majority of parents think that they know about their children's activities on the Internet, and that a significant number of parents recognize potentional dangers of using the Internet and social networks. When it comes to mediation, i.e. the ways of guiding/regulating the child's behaviour on the Internet, it turned out that the parents most commonly use mediation based on facts or restrictive mediation, while value-based, i.e. active mediation is used by a considerably smaller number of parents. Especially important finding is that the majority of parents show interest for organized instruction on protection of children on the Internet. This interest of parents should be a starting point for creating a systemic support of the society, and especially the support of educational institutions for strengthening parental competencies for providing a safe Internet space for their children.

  17. Dynamic Output Feedback Control for Nonlinear Networked Control Systems with Random Packet Dropout and Random Delay

    Directory of Open Access Journals (Sweden)

    Shuiqing Yu

    2013-01-01

    Full Text Available This paper investigates the dynamic output feedback control for nonlinear networked control systems with both random packet dropout and random delay. Random packet dropout and random delay are modeled as two independent random variables. An observer-based dynamic output feedback controller is designed based upon the Lyapunov theory. The quantitative relationship of the dropout rate, transition probability matrix, and nonlinear level is derived by solving a set of linear matrix inequalities. Finally, an example is presented to illustrate the effectiveness of the proposed method.

  18. Guaranteeing Isochronous Control of Networked Motion Control Systems Using Phase Offset Adjustment

    Directory of Open Access Journals (Sweden)

    Ikhwan Kim

    2015-06-01

    Full Text Available Guaranteeing isochronous transfer of control commands is an essential function for networked motion control systems. The adoption of real-time Ethernet (RTE technologies may be profitable in guaranteeing deterministic transfer of control messages. However, unpredictable behavior of software in the motion controller often results in unexpectedly large deviation in control message transmission intervals, and thus leads to imprecise motion. This paper presents a simple and efficient heuristic to guarantee the end-to-end isochronous control with very small jitter. The key idea of our approach is to adjust the phase offset of control message transmission time in the motion controller by investigating the behavior of motion control task. In realizing the idea, we performed a pre-runtime analysis to determine a safe and reliable phase offset and applied the phase offset to the runtime code of motion controller by customizing an open-source based integrated development environment (IDE. We also constructed an EtherCAT-based motion control system testbed and performed extensive experiments on the testbed to verify the effectiveness of our approach. The experimental results show that our heuristic is highly effective even for low-end embedded controller implemented in open-source software components under various configurations of control period and the number of motor drives.

  19. Adaptive pinning control of deteriorated nonlinear coupling networks with circuit realization.

    Science.gov (United States)

    Jin, Xiao-Zheng; Yang, Guang-Hong; Che, Wei-Wei

    2012-09-01

    This paper deals with a class of complex networks with nonideal coupling networks, and addresses the problem of asymptotic synchronization of the complex network through designing adaptive pinning control and coupling adjustment strategies. A more general coupled nonlinearity is considered as perturbations of the network, while a serious faulty network named deteriorated network is also proposed to be further study. For the sake of eliminating these adverse impacts for synchronization, indirect adaptive schemes are designed to construct controllers and adjusters on pinned nodes and nonuniform couplings of un-pinned nodes, respectively. According to Lyapunov stability theory, the proposed adaptive strategies are successful in ensuring the achievement of asymptotic synchronization of the complex network even in the presence of perturbed and deteriorated networks. The proposed schemes are physically implemented by circuitries and tested by simulation on a Chua's circuit network.

  20. DATA ACQUISITION FROM LOOMS USING CONTROLLER AREA NETWORK

    Directory of Open Access Journals (Sweden)

    Bedri BAHTİYAR

    2007-03-01

    Full Text Available To make efficiency analysis and to increase efficiency of a weaving hall, it is necessary to obtain and then analyze technical and weaving data received from looms. In small and mid-size weaving halls, generally technical data of the looms are kept by responsible technical personnel. Data processing without a defined automation makes efficiency analysis of weaving hall more complex, or may decrease liability of the analysis. In this paper, a data acquisition system that uses controller area network (CAN for the efficiency analysis of looms where developed and implemented in a mid-size weaving hall is presented. In system, technical and weaving data taken from the ports of the looms are sent to central computer via CAN, and then are processed in central computer.

  1. Phoebe: A preliminary control network and rotational elements

    Science.gov (United States)

    Colvin, Tim R.; Davies, Merton E.; Rogers, Patricia G.; Heller, Jeanne (Editor)

    1989-01-01

    A preliminary control network for the Saturnian satellite Phoebe was determined based upon 6 distinct albedo features mapped on 16 Voyager 2 images. Using an existing map and an analytical triangulation program which minimized the measurement error, the north pole of Phoebe was calculated to be alpha sub 0 = 355.0 deg + or - 9.6 deg, delta sub 0 = 68.7 deg + or - 7.9 deg, where alpha sub 0, delta sub 0 are standard equatorial coordinates with equinox J2000 at epoch J2000. The prime meridian of Phoebe was computed to be W = 304.7 deg + 930.833872d, where d is the interval in days from JD 2451545.0 TDB.

  2. Delay compensation using Smith predictor for wireless network control system

    Directory of Open Access Journals (Sweden)

    Mahmoud Gamal

    2016-06-01

    In this paper, a delay compensation scheme using classical and adaptive Smith predictor is applied to wireless NCS. The Markov model is proposed to compute the estimated network delay used in the classical predictor. In the adaptive predictor, the channel delay statistics using shift register is proposed to update the estimated delay. To evaluate the proposed schemes, a DC-motor controller system based on IEEE 802.15.4 is built using True Time Matlab software. The system performance with and without the proposed delay compensation scheme is studied. It is also compared to other delay compensation schemes. The results show that the proposed scheme improves the NCS performance significantly and reduces the effect of the delay on the system.

  3. Distributed Ship Navigation Control System Based on Dual Network

    Science.gov (United States)

    Yao, Ying; Lv, Wu

    2017-10-01

    Navigation system is very important for ship’s normal running. There are a lot of devices and sensors in the navigation system to guarantee ship’s regular work. In the past, these devices and sensors were usually connected via CAN bus for high performance and reliability. However, as the development of related devices and sensors, the navigation system also needs the ability of high information throughput and remote data sharing. To meet these new requirements, we propose the communication method based on dual network which contains CAN bus and industrial Ethernet. Also, we import multiple distributed control terminals with cooperative strategy based on the idea of synchronizing the status by multicasting UDP message contained operation timestamp to make the system more efficient and reliable.

  4. Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.

    Energy Technology Data Exchange (ETDEWEB)

    Ameme, Dan Selorm Kwami [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guttromson, Ross [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-10-01

    This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.

  5. Upregulation of cognitive control networks in older adults’ speech comprehension

    Directory of Open Access Journals (Sweden)

    Julia eErb

    2013-12-01

    Full Text Available Speech comprehension abilities decline with age and with age-related hearing loss, but it is unclear how this decline expresses in terms of central neural mechanisms. The current study examined neural speech processing in a group of older adults (aged 56–77, n=16, with varying degrees of sensorineural hearing loss, and compared them to a cohort of young adults (aged 22–31, n=30, self-reported normal hearing. In an fMRI experiment, listeners heard and repeated back degraded sentences (4-band vocoding, which preserves the temporal envelope of the acoustic signal, while substantially degrading spectral information. Behaviourally, older adults adapted to degraded speech at the same rate as young listeners, although their overall comprehension of degraded speech was lower. Neurally, both older and young adults relied on the left anterior insula for degraded more than clear speech perception. However, anterior insula engagement in older adults was dependent on hearing acuity. Young adults additionally employed the anterior cingulate cortex (ACC. Interestingly, this age group × degradation interaction was driven by a reduced dynamic range in older adults, who displayed elevated levels of ACC activity in both conditions, consistent with a persistent upregulation in cognitive control irrespective of task difficulty. For correct speech comprehension, older adults recruited the middle frontal gyrus in addition to a core speech comprehension network on which young adults relied, suggestive of a compensatory mechanism. Taken together, the results indicate that older adults increasingly recruit cognitive control networks, even under optimal listening conditions, at the expense of these systems’ dynamic range.

  6. Position Control of a Pneumatic Muscle Actuator Using RBF Neural Network Tuned PID Controller

    Directory of Open Access Journals (Sweden)

    Jie Zhao

    2015-01-01

    Full Text Available Pneumatic Muscle Actuator (PMA has a broad application prospect in soft robotics. However, PMA has highly nonlinear and hysteretic properties among force, displacement, and pressure, which lead to difficulty in accurate position control. A phenomenological model is developed to portray the hysteretic behavior of PMA. This phenomenological model consists of linear component and hysteretic component force. The latter component is described by Duhem model. An experimental apparatus is built up and sets of experimental data are acquired. Based on the experimental data, parameters of the model are identified. Validation of the model is performed. Then a novel cascade position PID controller is devised for a 1-DOF manipulator actuated by PMA. The outer loop of the controller is to cope with position control whilst the inner loop deals with pressure dynamics within PMA. To enhance the adaptability of the PID algorithm to the high nonlinearities of the manipulator, PID parameters are tuned online using RBF Neural Network. Experiments are performed and comparison between position response of RBF Neural Network based PID controller and that of classic PID controller demonstrates the effectiveness of the novel adaptive controller on the manipulator.

  7. Static-dynamic hybrid communication scheduling and control co-design for networked control systems.

    Science.gov (United States)

    Wen, Shixi; Guo, Ge

    2017-11-01

    In this paper, the static-dynamic hybrid communication scheduling and control co-design is proposed for the networked control systems (NCSs) to solve the capacity limitation of the wireless communication network. The analytical most regular binary sequences (MRBSs) are used as the communication scheduling function for NCSs. When the communication conflicts yielded in the binary sequence MRBSs, a dynamic scheduling strategy is proposed to on-line reallocate the medium access status for each plant. Under such static-dynamic hybrid scheduling policy, plants in NCSs are described as the non-uniform sampled-control systems, whose controller have a group of controller gains and switch according to the sampling interval yielded by the binary sequence. A useful communication scheduling and control co-design framework is proposed for the NCSs to simultaneously decide the controller gains and the parameters used to generate the communication sequences MRBS. Numerical example and realistic example are respectively given to demonstrate the effectiveness of the proposed co-design method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Molecular networks involved in the immune control of BK polyomavirus.

    Science.gov (United States)

    Girmanova, Eva; Brabcova, Irena; Klema, Jiri; Hribova, Petra; Wohlfartova, Mariana; Skibova, Jelena; Viklicky, Ondrej

    2012-01-01

    BK polyomavirus infection is the important cause of virus-related nephropathy following kidney transplantation. BK virus reactivates in 30%-80% of kidney transplant recipients resulting in BK virus-related nephropathy in 1%-10% of cases. Currently, the molecular processes associated with asymptomatic infections in transplant patients infected with BK virus remain unclear. In this study we evaluate intrarenal molecular processes during different stages of BKV infection. The gene expression profiles of 90 target genes known to be associated with immune response were evaluated in kidney graft biopsy material using TaqMan low density array. Three patient groups were examined: control patients with no evidence of BK virus reactivation (n = 11), infected asymptomatic patients (n = 9), and patients with BK virus nephropathy (n = 10). Analysis of biopsies from asymptomatic viruria patients resulted in the identification of 5 differentially expressed genes (CD3E, CD68, CCR2, ICAM-1, and SKI) (P < 0.05), and functional analysis showed a significantly heightened presence of costimulatory signals (e.g., CD40/CD40L; P < 0.05). Gene ontology analysis revealed several biological networks associated with BKV immune control in comparison to the control group. This study demonstrated that asymptomatic BK viruria is associated with a different intrarenal regulation of several genes implicating in antiviral immune response.

  9. Molecular Networks Involved in the Immune Control of BK Polyomavirus

    Directory of Open Access Journals (Sweden)

    Eva Girmanova

    2012-01-01

    Full Text Available BK polyomavirus infection is the important cause of virus-related nephropathy following kidney transplantation. BK virus reactivates in 30%–80% of kidney transplant recipients resulting in BK virus-related nephropathy in 1%–10% of cases. Currently, the molecular processes associated with asymptomatic infections in transplant patients infected with BK virus remain unclear. In this study we evaluate intrarenal molecular processes during different stages of BKV infection. The gene expression profiles of 90 target genes known to be associated with immune response were evaluated in kidney graft biopsy material using TaqMan low density array. Three patient groups were examined: control patients with no evidence of BK virus reactivation (n=11, infected asymptomatic patients (n=9, and patients with BK virus nephropathy (n=10. Analysis of biopsies from asymptomatic viruria patients resulted in the identification of 5 differentially expressed genes (CD3E, CD68, CCR2, ICAM-1, and SKI (P<0.05, and functional analysis showed a significantly heightened presence of costimulatory signals (e.g., CD40/CD40L; P<0.05. Gene ontology analysis revealed several biological networks associated with BKV immune control in comparison to the control group. This study demonstrated that asymptomatic BK viruria is associated with a different intrarenal regulation of several genes implicating in antiviral immune response.

  10. Neural network control of mobile robot formations using RISE feedback.

    Science.gov (United States)

    Dierks, Travis; Jagannathan, S

    2009-04-01

    In this paper, an asymptotically stable (AS) combined kinematic/torque control law is developed for leader-follower-based formation control using backstepping in order to accommodate the complete dynamics of the robots and the formation, and a neural network (NN) is introduced along with robust integral of the sign of the error feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are AS and that the NN weights are bounded as opposed to uniformly ultimately bounded stability which is typical with most NN controllers. Additionally, the stability of the formation in the presence of obstacles is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation do not occur. The asymptotic stability of the follower robots as well as the entire formation during an obstacle avoidance maneuver is demonstrated using Lyapunov methods, and numerical results are provided to verify the theoretical conjectures.

  11. ZIKV - CDB: A Collaborative Database to Guide Research Linking SncRNAs and ZIKA Virus Disease Symptoms.

    Science.gov (United States)

    Pylro, Victor Satler; Oliveira, Francislon Silva; Morais, Daniel Kumazawa; Cuadros-Orellana, Sara; Pais, Fabiano Sviatopolk-Mirsky; Medeiros, Julliane Dutra; Geraldo, Juliana Assis; Gilbert, Jack; Volpini, Angela Cristina; Fernandes, Gabriel Rocha

    2016-06-01

    In early 2015, a ZIKA Virus (ZIKV) infection outbreak was recognized in northeast Brazil, where concerns over its possible links with infant microcephaly have been discussed. Providing a causal link between ZIKV infection and birth defects is still a challenge. MicroRNAs (miRNAs) are small noncoding RNAs (sncRNAs) that regulate post-transcriptional gene expression by translational repression, and play important roles in viral pathogenesis and brain development. The potential for flavivirus-mediated miRNA signalling dysfunction in brain-tissue development provides a compelling hypothesis to test the perceived link between ZIKV and microcephaly. Here, we applied in silico analyses to provide novel insights to understand how Congenital ZIKA Syndrome symptoms may be related to an imbalance in miRNAs function. Moreover, following World Health Organization (WHO) recommendations, we have assembled a database to help target investigations of the possible relationship between ZIKV symptoms and miRNA-mediated human gene expression. We have computationally predicted both miRNAs encoded by ZIKV able to target genes in the human genome and cellular (human) miRNAs capable of interacting with ZIKV genomes. Our results represent a step forward in the ZIKV studies, providing new insights to support research in this field and identify potential targets for therapy.

  12. ZIKV - CDB: A Collaborative Database to Guide Research Linking SncRNAs and ZIKA Virus Disease Symptoms.

    Directory of Open Access Journals (Sweden)

    Victor Satler Pylro

    2016-06-01

    Full Text Available In early 2015, a ZIKA Virus (ZIKV infection outbreak was recognized in northeast Brazil, where concerns over its possible links with infant microcephaly have been discussed. Providing a causal link between ZIKV infection and birth defects is still a challenge. MicroRNAs (miRNAs are small noncoding RNAs (sncRNAs that regulate post-transcriptional gene expression by translational repression, and play important roles in viral pathogenesis and brain development. The potential for flavivirus-mediated miRNA signalling dysfunction in brain-tissue development provides a compelling hypothesis to test the perceived link between ZIKV and microcephaly.Here, we applied in silico analyses to provide novel insights to understand how Congenital ZIKA Syndrome symptoms may be related to an imbalance in miRNAs function. Moreover, following World Health Organization (WHO recommendations, we have assembled a database to help target investigations of the possible relationship between ZIKV symptoms and miRNA-mediated human gene expression.We have computationally predicted both miRNAs encoded by ZIKV able to target genes in the human genome and cellular (human miRNAs capable of interacting with ZIKV genomes. Our results represent a step forward in the ZIKV studies, providing new insights to support research in this field and identify potential targets for therapy.

  13. A model composition for Mars derived from the oxygen isotopic ratios of martian/SNC meteorites. [Abstract only

    Science.gov (United States)

    Delaney, J. S.

    1994-01-01

    Oxygen is the most abundant element in most meteorites, yet the ratios of its isotopes are seldom used to constrain the compositional history of achondrites. The two major achondrite groups have O isotope signatures that differ from any plausible chondritic precursors and lie between the ordinary and carbonaceous chondrite domains. If the assumption is made that the present global sampling of chondritic meteorites reflects the variability of O reservoirs at the time of planetessimal/planet aggregation in the early nebula, then the O in these groups must reflect mixing between known chondritic reservoirs. This approach, in combination with constraints based on Fe-Mn-Mg systematics, has been used previously to model the composition of the basaltic achondrite parent body (BAP) and provides a model precursor composition that is generally consistent with previous eucrite parent body (EPB) estimates. The same approach is applied to Mars exploiting the assumption that the SNC and related meteorites sample the martian lithosphere. Model planet and planetesimal compositions can be derived by mixing of known chondritic components using O isotope ratios as the fundamental compositional constraint. The major- and minor-element composition for Mars derived here and that derived previously for the basaltic achondrite parent body are, in many respects, compatible with model compositions generated using completely independent constraints. The role of volatile elements and alkalis in particular remains a major difficulty in applying such models.

  14. Hierarchical nanostructured core-shell Sn@C nanoparticles embedded in graphene nanosheets: spectroscopic view and their application in lithium ion batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Dongniu; Li, Xifei; Yang, Jinli; Wang, Jiajun; Geng, Dongsheng; Li, Ruying; Cai, Mei; Sham, Tsun-Kong; Sun, Xueliang (General Motors); (UWO)

    2016-02-04

    Hierarchical carbon encapsulated tin (Sn@C) embedded graphene nanosheet (GN) composites (Sn@C–GNs) have been successfully fabricated via a simple and scalable one-step chemical vapor deposition (CVD) procedure. The GN supported Sn@C core–shell structures consist of a crystalline tin core, which is thoroughly covered by a carbon shell and more interestingly, extra voids are present between the carbon shell and the tin core. Synchrotron spectroscopy confirms that the metallic tin core is free of oxidation and the existence of charge redistribution transfer from tin to the carbonaceous materials of the shell, facilitating their intimate contact by chemical bonding and resultant lattice variation. The hybrid electrodes of this material exhibit a highly stable and reversible capacity together with an excellent rate capability, which benefits from the improved electrochemical properties of tin provided by the protective carbon matrix, voids and the flexible GN matrices.

  15. Utilizing Network QoS for Dependability of Adaptive Smart Grid Control

    DEFF Research Database (Denmark)

    Madsen, Jacob Theilgaard; Kristensen, Thomas le Fevre; Olsen, Rasmus Løvenstein

    2014-01-01

    A smart grid is a complex system consisting of a wide range of electric grid components, entities controlling power distribution, generation and consumption, and a communication network supporting data exchange. This paper focuses on the influence of imperfect network conditions on smart grid con......- trollers, and how this can be counteracted by utilizing Quality of Service (QoS) information from the communication network. Such an interface between grid controller and network QoS is particularly relevant for smart grid scenarios that use third party communication network infrastructure, where...... modification of networking and lower layer protocols are impossible. This paper defines a middleware solution for adaptation of smart grid control, which uses network QoS information and interacts with the smart grid controller to increase dependability. In order to verify the methodology, an example scenario...

  16. 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

  17. Deep Space Network (DSN), Network Operations Control Center (NOCC) computer-human interfaces

    Science.gov (United States)

    Ellman, Alvin; Carlton, Magdi

    1993-01-01

    The Network Operations Control Center (NOCC) of the DSN is responsible for scheduling the resources of DSN, and monitoring all multi-mission spacecraft tracking activities in real-time. Operations performs this job with computer systems at JPL connected to over 100 computers at Goldstone, Australia and Spain. The old computer system became obsolete, and the first version of the new system was installed in 1991. Significant improvements for the computer-human interfaces became the dominant theme for the replacement project. Major issues required innovating problem solving. Among these issues were: How to present several thousand data elements on displays without overloading the operator? What is the best graphical representation of DSN end-to-end data flow? How to operate the system without memorizing mnemonics of hundreds of operator directives? Which computing environment will meet the competing performance requirements? This paper presents the technical challenges, engineering solutions, and results of the NOCC computer-human interface design.

  18. Genetic control of functional brain network efficiency in children

    NARCIS (Netherlands)

    Heuvel, M.P.; van Soelen, I.L.C.; Stam, C.J.; Kahn, R.S.; Boomsma, D.I.; Hulshoff Pol, H.E.

    2013-01-01

    The human brain is a complex network of interconnected brain regions. In adulthood, the brain's network was recently found to be under genetic influence. However, the extent to which genes influence the functional brain network early in development is not yet known. We report on the heritability of

  19. RBF Neural Network of Sliding Mode Control for Time-Varying 2-DOF Parallel Manipulator System

    Directory of Open Access Journals (Sweden)

    Haizhong Chen

    2013-01-01

    Full Text Available This paper presents a radial basis function (RBF neural network control scheme for manipulators with actuator nonlinearities. The control scheme consists of a time-varying sliding mode control (TVSMC and an RBF neural network compensator. Since the actuator nonlinearities are usually included in the manipulator driving motor, a compensator using RBF network is proposed to estimate the actuator nonlinearities and their upper boundaries. Subsequently, an RBF neural network controller that requires neither the evaluation of off-line dynamical model nor the time-consuming training process is given. In addition, Barbalat Lemma is introduced to help prove the stability of the closed control system. Considering the SMC controller and the RBF network compensator as the whole control scheme, the closed-loop system is proved to be uniformly ultimately bounded. The whole scheme provides a general procedure to control the manipulators with actuator nonlinearities. Simulation results verify the effectiveness of the designed scheme and the theoretical discussion.

  20. 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 identified...... 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...

  1. 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

  2. Aplicabilidade e regulamentação sanitária da nanomedicina em grandes distúrbios do Sistema Nervoso Central (SNC

    Directory of Open Access Journals (Sweden)

    Antonio Claudio Tedesco

    2013-11-01

    Full Text Available Na nanomedicina, os nanocarreadores são geralmente biocompatíveis, biodegradáveis de rápida biodistribuição pelo organismo e podem ser utilizados para transportar drogas ou genes terapêuticos. Assim, novos sistemas de liberação de fármacos têm sido altamente explorados no tratamento de doenças do Sistema Nervoso Central (SNC, como Parkinson, Alzheimer e gliomas, visto que o SNC representa um grande desafio para as abordagens terapêuticas devido às barreiras hemato-encefálica (BHE e sangue- -líquido cefalorraquidiano (BSLCR. Desse modo, a comunidade científica juntamente com instituições governamentais e indústrias privadas vêm somando esforços para gerar novas formulações em escalas nanométricas com o intuito de alcançar uma abordagem terapêutica adequada, satisfatória e que esteja dentro dos princípios da vigilância sanitária para os acometimentos cerebrais. Este artigo visa sumarizar os conhecimentos sobre principais barreiras para entrega de fármacos ao SNC, nanomedicina, glioma, Parkinson, Alzheimer e vigilância sanitária.

  3. 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

  4. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Science.gov (United States)

    Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

    2014-01-01

    The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

  5. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Directory of Open Access Journals (Sweden)

    Claudia Casellato

    Full Text Available The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning, a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

  6. Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

    Directory of Open Access Journals (Sweden)

    Juan F. Monsalve-Posada

    2015-01-01

    Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

  7. 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.

  8. Sufficient Condition for the Existence of the Compact Set in the RBF Neural Network Control.

    Science.gov (United States)

    Zhu, Jiaming; Cao, Zhiqiang; Zhang, Tianping; Yang, Yuequan; Yi, Yang

    2017-06-20

    In this brief, sufficient conditions are proposed for the existence of the compact sets in the neural network controls. First, we point out that the existence of the compact set in a classical neural network control scheme is unsolved and its result is incomplete. Next, as a simple case, we derive the sufficient condition of the existence of the compact set for the neural network control of first-order systems. Finally, we propose the sufficient condition of the existence of the compact set for the neural-network-based backstepping control of high-order nonlinear systems. The theoretic result is illustrated through a simulation example.

  9. State feedback controller design for the synchronization of Boolean networks with time delays

    Science.gov (United States)

    Li, Fangfei; Li, Jianning; Shen, Lijuan

    2018-01-01

    State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.

  10. Network Support II: Randomized controlled trial of Network Support treatment and cognitive behavioral therapy for alcohol use disorder.

    Science.gov (United States)

    Litt, Mark D; Kadden, Ronald M; Tennen, Howard; Kabela-Cormier, Elise

    2016-08-01

    The social network of those treated for alcohol use disorder can play a significant role in subsequent drinking behavior, both for better and worse. Network Support treatment was devised to teach ways to reconstruct social networks so that they are more supportive of abstinence and less supportive of drinking. For many patients this may involve engagement with AA, but other strategies are also used. The current trial of Network Support treatment, building on our previous work, was intended to further enhance the ability of patients to construct abstinence-supportive social networks, and to test this approach against a strong control treatment. Patients were 193 men and women with alcohol use disorder recruited from the community and assigned to either 12 weeks of Network Support (NS) or Packaged Cognitive-Behavioral Treatment (PCBT), and followed for 27 months. Results of multilevel analyses indicated that NS yielded better posttreatment results in terms of both proportion of days abstinent and drinking consequences, and equivalent improvements in 90-day abstinence, heavy drinking days and drinks per drinking day. Mediation analyses revealed that NS treatment effects were mediated by pre-post changes in abstinence self-efficacy and in social network variables, especially proportion of non-drinkers in the social network and attendance at Alcoholics Anonymous. It was concluded that helping patients enhance their abstinent social network can be effective, and may provide a useful alternative or adjunctive approach to treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Autonomous Distributed Congestion Control Scheme in WCDMA Network

    Science.gov (United States)

    Ahmad, Hafiz Farooq; Suguri, Hiroki; Choudhary, Muhammad Qaisar; Hassan, Ammar; Liaqat, Ali; Khan, Muhammad Umer

    Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.

  12. Modeling and Output Feedback Control of Networked Control Systems with Both Time Delays; and Packet Dropouts

    Directory of Open Access Journals (Sweden)

    Li Qiu

    2013-01-01

    Full Text Available This paper is concerned with the problem of modeling and output feedback controller design for a class of discrete-time networked control systems (NCSs with time delays and packet dropouts. A Markovian jumping method is proposed to deal with random time delays and packet dropouts. Different from the previous studies on the issue, the characteristics of networked communication delays and packet dropouts can be truly reflected by the unified model; namely, both sensor-to-controller (S-C and controller-to-actuator (C-A time delays, and packet dropouts are modeled and their history behavior is described by multiple Markov chains. The resulting closed-loop system is described by a new Markovian jump linear system (MJLS with Markov delays model. Based on Lyapunov stability theory and linear matrix inequality (LMI method, sufficient conditions of the stochastic stability and output feedback controller design method for NCSs with random time delays and packet dropouts are presented. A numerical example is given to illustrate the effectiveness of the proposed method.

  13. Self-Tuning Vibration Control of a Rotational Flexible Timoshenko Arm Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Minoru Sasaki

    2012-01-01

    Full Text Available A self-tuning vibration control of a rotational flexible arm using neural networks is presented. To the self-tuning control system, the control scheme consists of gain tuning neural networks and a variable-gain feedback controller. The neural networks are trained so as to make the root moment zero. In the process, the neural networks learn the optimal gain of the feedback controller. The feedback controller is designed based on Lyapunov's direct method. The feedback control of the vibration of the flexible system is derived by considering the time rate of change of the total energy of the system. This approach has the advantage over the conventional methods in the respect that it allows one to deal directly with the system's partial differential equations without resorting to approximations. Numerical and experimental results for the vibration control of a rotational flexible arm are discussed. It verifies that the proposed control system is effective at controlling flexible dynamical systems.

  14. Neural-networks-based feedback linearization versus model predictive control of continuous alcoholic fermentation process

    Energy Technology Data Exchange (ETDEWEB)

    Mjalli, F.S.; Al-Asheh, S. [Chemical Engineering Department, Qatar University, Doha (Qatar)

    2005-10-01

    In this work advanced nonlinear neural networks based control system design algorithms are adopted to control a mechanistic model for an ethanol fermentation process. The process model equations for such systems are highly nonlinear. A neural network strategy has been implemented in this work for capturing the dynamics of the mechanistic model for the fermentation process. The neural network achieved has been validated against the mechanistic model. Two neural network based nonlinear control strategies have also been adopted using the model identified. The performance of the feedback linearization technique was compared to neural network model predictive control in terms of stability and set point tracking capabilities. Under servo conditions, the feedback linearization algorithm gave comparable tracking and stability. The feedback linearization controller achieved the control target faster than the model predictive one but with vigorous and sudden controller moves. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

  15. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  16. Modeling and adaptive pinning synchronization control for a chaotic-motion motor in complex network

    Science.gov (United States)

    Zhu, Darui; Liu, Chongxin; Yan, Bingnan

    2014-01-01

    We introduce a chaos model for a permanent-magnet synchronous motor and construct a coupled chaotic motor in a complex dynamic network using the Newman-Watts small-world network algorithm. We apply adaptive pinning control theory for complex networks to obtain suitable adaptive feedback gain and the number of nodes to be pinned. Nodes of low degree are pinned to realize global asymptotic synchronization in the complex network. The proposed adaptive pinning controller is added to the complex motor network for simulation and verification.

  17. Effect of edge pruning on structural controllability and observability of complex networks

    Science.gov (United States)

    Mengiste, Simachew Abebe; Aertsen, Ad; Kumar, Arvind

    2015-12-01

    Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is important to understand how perturbations in the connectivity affect the controllability of the system. To this end, we studied the control structure of different types of artificial, social and biological neuronal networks (BNN) as their connections were progressively pruned using four different pruning strategies. We show that the BNNs are more similar to scale-free networks than to small-world networks, when comparing the robustness of their control structure to structural perturbations. We introduce a new graph descriptor, ‘the cardinality curve’, to quantify the robustness of the control structure of a network to progressive edge pruning. Knowing the susceptibility of control structures to different pruning methods could help design strategies to destroy the control structures of dangerous networks such as epidemic networks. On the other hand, it could help make useful networks more resistant to edge attacks.

  18. 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...

  19. Reliable monitoring and controling of energy transport networks; Energietransportnetze zuverlaessig ueberwachen und steuern

    Energy Technology Data Exchange (ETDEWEB)

    Schwarz, Hans-Joachim [Keymile GmbH, Hannover (Germany). Consulting and Projects

    2013-06-01

    Energy suppliers distribute their products often over long distances. For a long time, monitoring data and control data are exchanged in supply networks and transport networks. The necessary data lines and data networks are typically arranged in parallel to the power supply routes. Increasing demands on the transmission rate and hence the bandwidth of such remote systems are not easy to fulfill. But the today's broadcast technology provides cost-effective solutions also for cable networks which exist for decades.

  20. Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

    DEFF Research Database (Denmark)

    Huang, Qian; Huang, Yue-Cai; Ko, King-Tim

    2011-01-01

    A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...... dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers...

  1. Proposta de rede de interconexão WDM com controle TDM Proposal of WDM interconnection network with TDM control

    Directory of Open Access Journals (Sweden)

    João Angelo Martini

    1999-05-01

    Full Text Available Este artigo apresenta uma proposta de rede de interconexão WDM com controle TDM e discute os princípios da tecnologia WDM. O artigo também classifica as redes de interconexão WDM e discute as arquiteturas de redes de interconexão e os protocolos de controle.This article presents a proposal for a WDM interconnection network with TDM control and discusses principles of WDM technology. It also classifies WDM interconnection networks and discusses interconnection network architectures as well as the protocols for control.

  2. 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

  3. H∞ Networked Cascade Control System Design for Turboshaft Engines with Random Packet Dropouts

    Directory of Open Access Journals (Sweden)

    Xiaofeng Liu

    2017-01-01

    Full Text Available The distributed control architecture becomes more and more important in future gas turbine engine control systems, in which the sensors and actuators will be connected to the controllers via a network. Therefore, the control problem of network-enabled high-performance distributed engine control (DEC has come to play an important role in modern gas turbine control systems, while, due to the properties of the network, the packet dropouts must be considered. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS. Typical turboshaft engine distributed controllers are designed based on the NCCS framework with H∞ state feedback under random packet dropouts. The sufficient robust stable conditions are derived via the Lyapunov stability theory and linear matrix inequality approach. Simulations illustrate the effectiveness of the presented method.

  4. Design of proportional-derivative-type state feedback controllers for congestion control of transmission control protocol networks

    Science.gov (United States)

    Azadegan, Masoumeh; Beheshti, Mohammad T. H.; Tavassoli, Babak

    2015-07-01

    A new proportional-derivative-type state feedback controller is proposed for congestion control of transmission control protocol (TCP) networks. An analytical TCP model is adopted. In the proposed control scheme, it is possible to efficiently control the TCP traffic using only the queue length at the router without the need to know the TCP window size which is not available locally. The results are presented in terms of delay-dependent linear matrix inequality. The proposed method is verified by simulation examples using NS software, and the effectiveness and superiority of our method over other control schemes, such as the proportional-integral, random early detection and generalised minimum variancemethods, are also shown.

  5. AQM controller design for networks supporting TCP vegas: a control theoretical approach.

    Science.gov (United States)

    Bigdeli, Nooshin; Haeri, Mohammad

    2008-01-01

    In this paper, a mathematical model and control theoretical framework for designing AQM controllers in networks supporting TCP Vegas is introduced. We have emphasized on a modified TCP Vegas algorithm that can respond to congestion signals through explicit congestion notification (ECN). The overall nonlinear delayed differential equations of the dynamics model of closed loop system have been derived based on TCP Vegas model. The model is then linearized to derive a transfer function representation between the packet marking probability and the bottleneck router queue length as the input and output of the modified TCP Vegas/AQM system. The model properties have been then examined especially for the case of single bottleneck homogeneous network which is closely investigated. Finally an AQM controller based on Coefficient Diagram Method (CDM) has been designed for the system and its performance has been compared with some other AQM controllers. CDM is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. In order for synthesizing the simulation scenarios, our campus router traffic has been studied experimentally for a sample period of one hour and the corresponding parameters has been extracted. The simulation results are representative of good performance of developed TCP Vegas/AQM structure for different simulated scenarios.

  6. Power control algorithms for mobile ad hoc networks

    Directory of Open Access Journals (Sweden)

    Nuraj L. Pradhan

    2011-07-01

    We will also focus on an adaptive distributed power management (DISPOW algorithm as an example of the multi-parameter optimization approach which manages the transmit power of nodes in a wireless ad hoc network to preserve network connectivity and cooperatively reduce interference. We will show that the algorithm in a distributed manner builds a unique stable network topology tailored to its surrounding node density and propagation environment over random topologies in a dynamic mobile wireless channel.

  7. Distributed Downlink Power Control for Dense Networks with Carrier Aggregation

    OpenAIRE

    Fazliu, Zana Limani; Chiasserini, Carla-Fabiana; Dell'Aera, Gian Michele; Hamiti, Enver

    2017-01-01

    Given the proven benefits cell densification brings in terms of capacity and coverage, it is certain that 5G networks will be even more heterogeneous and dense. However, as smaller cells are introduced in the network, interference will inevitably become a serious problem as they are expected to share the same radio resources. Another central feature envisioned for future cellular networks is carrier aggregation (CA), which allows users to simultaneously use several component carriers of vario...

  8. Design and control approaches for energy harvesting wireless sensor networks

    OpenAIRE

    Frezzetti, Antonio

    2016-01-01

    Wireless Networks are monitoring infrastructures composed of sensing (measuring), computing, and communication devices used to observe, supervise and monitor environmental phenomena. Energy Harvesting Wireless Sensor Networks (EH-WSN) have the additional feature to save energy from the environment in order to ensure long life autonomy of the entire network, without ideally the human intervention over long periods of time. The present work is aimed to address some of the most significant limit...

  9. The Contribution of Network Organization and Integration to the Development of Cognitive Control.

    Science.gov (United States)

    Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

    2015-12-01

    Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

  10. Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control.

    Science.gov (United States)

    Wen, Shiping; Zeng, Zhigang; Chen, Michael Z Q; Huang, Tingwen

    2017-10-01

    This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

  11. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview...

  12. Main control computer security model of closed network systems protection against cyber attacks

    Science.gov (United States)

    Seymen, Bilal

    2014-06-01

    The model that brings the data input/output under control in closed network systems, that maintains the system securely, and that controls the flow of information through the Main Control Computer which also brings the network traffic under control against cyber-attacks. The network, which can be controlled single-handedly thanks to the system designed to enable the network users to make data entry into the system or to extract data from the system securely, intends to minimize the security gaps. Moreover, data input/output record can be kept by means of the user account assigned for each user, and it is also possible to carry out retroactive tracking, if requested. Because the measures that need to be taken for each computer on the network regarding cyber security, do require high cost; it has been intended to provide a cost-effective working environment with this model, only if the Main Control Computer has the updated hardware.

  13. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...

  14. Reversible Control of Anisotropic Electrical Conductivity using Colloidal Microfluidic Networks

    National Research Council Canada - National Science Library

    Beskok, Ali; Bevan, Michael; Lagoudas, Dimitris; Ounaies, Zoubeida; Bahukudumbi, Pradipkumar; Everett, William

    2007-01-01

    This research addresses the tunable assembly of reversible colloidal structures within microfluidic networks to engineer multifunctional materials that exhibit a wide range of electrical properties...

  15. 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.

  16. Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks

    Directory of Open Access Journals (Sweden)

    De Momi Elena

    2006-10-01

    Full Text Available Abstract Background The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. Methods The error mapping controller (EMC here proposed uses artificial neural networks (ANNs both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID included in an anti wind-up scheme (called PIDAW and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID. In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. Results The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Conclusion Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice.

  17. Global Accelerator Network, Control Systems And Beam Diagnostics

    CERN Document Server

    Raich, U

    2003-01-01

    Falling funds force all accelerator centers to look for new sources of financing and for the most efficient way of implementing new projects. This very often leads to collaborations between institutes scattered around the globe, a problem well known to big high energy physics experiments. The collaborations working on big detectors e.g. for LHC started thinking about detector acquisition and control systems which can be remotely used from their respective home institutes with minimal support on the spot. This idea was taken up by A. Wagner from DESY for the TESLA machine, who proposed the “Global Accelerator Network” (GAN) enabling users from around the world to run an accelerator remotely. Questions around this subject that immediately come to mind Is the GAN only relevant to big labs ? Or is it reasonable e.g. for operators or engineers in charge to do certain manipulations from home? Are our instruments ready for the GAN? Does the fact of being “GAN ready” increa...

  18. Control of the mitotic exit network during meiosis

    Science.gov (United States)

    Attner, Michelle A.; Amon, Angelika

    2012-01-01

    The mitotic exit network (MEN) is an essential GTPase signaling pathway that triggers exit from mitosis in budding yeast. We show here that during meiosis, the MEN is dispensable for exit from meiosis I but contributes to the timely exit from meiosis II. Consistent with a role for the MEN during meiosis II, we find that the signaling pathway is active only during meiosis II. Our analysis further shows that MEN signaling is modulated during meiosis in several key ways. Whereas binding of MEN components to spindle pole bodies (SPBs) is necessary for MEN signaling during mitosis, during meiosis MEN signaling occurs off SPBs and does not require the SPB recruitment factor Nud1. Furthermore, unlike during mitosis, MEN signaling is controlled through the regulated interaction between the MEN kinase Dbf20 and its activating subunit Mob1. Our data lead to the conclusion that a pathway essential for vegetative growth is largely dispensable for the specialized meiotic divisions and provide insights into how cell cycle regulatory pathways are modulated to accommodate different modes of cell division. PMID:22718910

  19. 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

  20. Secure Reprogramming of a Network Connected Device : Securing programmable logic controllers

    OpenAIRE

    Tesfaye, Mussie

    2012-01-01

    This is a master’s thesis project entitled “Secure reprogramming of network connected devices”. The thesis begins by providing some background information to enable the reader to understand the current vulnerabilities of network-connected devices, specifically with regard to cyber security and data integrity. Today supervisory control and data acquisition systems utilizing network connected programmable logic controllers are widely used in many industries and critical infrastructures. These n...

  1. A source-based congestion control strategy for real-time video transport on IP network

    Science.gov (United States)

    Chen, Xia; Cai, Canhui

    2005-07-01

    The goal of this paper is to design a TCP friendly real-time video transport protocol that will not only utilize network resource efficiently, but also prevent network congestion from the real-time video transmitting effectively. To this end, we proposed a source based congestion control scheme to adapt video coding rate to the channel capacity of the IP network, including three stages: rate control, rate-adaptive video encoding, and rate shaping.

  2. Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

    OpenAIRE

    Chao-Yang Lee; Chu-Sing Yang

    2012-01-01

    Because machine-to-machine (M2M) technology enables machines to communicate with each other without human intervention, it could play a big role in sensor network systems. Through wireless sensor network (WSN) gateways, various information can be collected by sensors for M2M systems. For home M2M networks, this study proposes a distributed energy-efficient topology control algorithm for both topology construction and topology maintenance. Topology control is an effective method of enhancing e...

  3. Digital Signal Processing and Control for the Study of Gene Networks.

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-22

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  4. Modafinil modulates resting-state functional network connectivity and cognitive control in alcohol-dependent patients

    NARCIS (Netherlands)

    Schmaal, Lianne; Goudriaan, Anna E.; Joos, Leen; Krüse, Anne Maren; Dom, Geert; van den Brink, Wim; Veltman, Dick J.

    2013-01-01

    Chronic alcohol abuse is associated with deficits in cognitive control functions. Cognitive control is likely to be mediated through the interaction between intrinsic large-scale brain networks involved in externally oriented executive functioning and internally focused thought processing. Improving

  5. Modafinil Modulates Resting-State Functional Network Connectivity and Cognitive Control in Alcohol-Dependent Patients

    NARCIS (Netherlands)

    Schmaal, L.; Goudriaan, A.E.; Joos, L.; Kruse, A.M.; Dom, G.; van den Brink, W.; Veltman, D.J.

    2013-01-01

    Background: Chronic alcohol abuse is associated with deficits in cognitive control functions. Cognitive control is likely to be mediated through the interaction between intrinsic large-scale brain networks involved in externally oriented executive functioning and internally focused thought

  6. Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Ruijun Liu

    2014-01-01

    Full Text Available Through researching the instantaneous control strategy and Elman neural network, the paper established equivalent fuel consumption functions under the charging and discharging conditions of power batteries, deduced the optimal control objective function of instantaneous equivalent consumption, established the instantaneous optimal control model, and designs the Elman neural network controller. Based on the ADVISOR 2002 platform, the instantaneous optimal control strategy and the Elman neural network control strategy were simulated on a parallel HEV. The simulation results were analyzed in the end. The contribution of the paper is that the trained Elman neural network control strategy can reduce the simulation time by 96% and improve the real-time performance of energy control, which also ensures the good performance of power and fuel economy.

  7. Low-level Control of Network Elements from an Agent Platform

    DEFF Research Database (Denmark)

    Hansen, Mads Stenhuus; Jensen, P.; Soldatos, J.

    1999-01-01

    An important issue for the implementation of an agent system, which controls a telecommunications network, is to enable low-level access of the network devices by the agent platform, bypassing the control logic inherent in them. This issue has been coped with successfully in the IMPACT project...

  8. On the Use of Information Quality in Stochastic Networked Control Systems

    DEFF Research Database (Denmark)

    Olsen, Rasmus Løvenstein; Madsen, Jacob Theilgaard; Rasmussen, Jakob Gulddahl

    2017-01-01

    Networked control is challenged by stochastic delays that are caused by the communication networks as well as by the approach taken to exchange information about system state and set-points. Combined with stochastic changing information, there is a probability that information at the controller...

  9. Evaluation of DECT for low latency real-time industrial control networks

    NARCIS (Netherlands)

    Das, Kallol; Havinga, Paul J.M.

    2013-01-01

    Wireless sensor networks (WSNs) have revolutionized the industrial networks by enabling wireless sensing and control to the machine parts where wiring is impossible. However, new challenges in terms of communication reliability and latency, appear with the advances in the industrial wireless control

  10. Neural network based adaptive control of nonlinear plants using random search optimization algorithms

    Science.gov (United States)

    Boussalis, Dhemetrios; Wang, Shyh J.

    1992-01-01

    This paper presents a method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems.

  11. A Logically Centralized Approach for Control and Management of Large Computer Networks

    Science.gov (United States)

    Iqbal, Hammad A.

    2012-01-01

    Management of large enterprise and Internet service provider networks is a complex, error-prone, and costly challenge. It is widely accepted that the key contributors to this complexity are the bundling of control and data forwarding in traditional routers and the use of fully distributed protocols for network control. To address these…

  12. Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

    Science.gov (United States)

    Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

    2017-01-01

    Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

  13. Neural network model to control an experimental chaotic pendulum

    NARCIS (Netherlands)

    Bakker, R; Schouten, JC; Takens, F; vandenBleek, CM

    1996-01-01

    A feedforward neural network was trained to predict the motion of an experimental, driven, and damped pendulum operating in a chaotic regime. The network learned the behavior of the pendulum from a time series of the pendulum's angle, the single measured variable. The validity of the neural

  14. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  15. Analytical Modeling of Medium Access Control Protocols in Wireless Networks

    Science.gov (United States)

    2006-03-01

    Imperatives and chal- lenges. Ad Hoc Networks, 1(1):13–64, July 2003. [28] I. Chlamtac and A. Faragó. Making transmission schedules immune to topology changes...P. Karn. MACA - a new channel access method for packet radio. In ARRL/CRRL Amateur Radio 9th Computer Networking Conference, pages 134–140, 1990

  16. Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry

    Directory of Open Access Journals (Sweden)

    Nickbakhsh Sema

    2011-10-01

    Full Text Available Abstract Background Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI control planning in Great Britain (GB provides one example where network data for the poultry industry (the Poultry Network Database or PND, targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks. Results The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR; this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network. Conclusions With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between

  17. Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry.

    Science.gov (United States)

    Nickbakhsh, Sema; Matthews, Louise; Bessell, Paul R; Reid, Stuart W J; Kao, Rowland R

    2011-10-25

    Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI) control planning in Great Britain (GB) provides one example where network data for the poultry industry (the Poultry Network Database or PND), targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks. The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR); this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network. With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between-farm transmission will be the focus of future work.

  18. Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

    Directory of Open Access Journals (Sweden)

    Andrzej Pawlowski

    2009-01-01

    Full Text Available Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

  19. Adaptive Wavelet Neural Network Backstepping Sliding Mode Tracking Control for PMSM Drive System

    OpenAIRE

    Liu, Da; Li, Muguo

    2015-01-01

    This paper presents a wavelet neural network backstepping sliding mode controller (WNNBSSM) for permanent-magnet synchronous motor (PMSM) position servo control system. Backstepping sliding mode (BSSM) is utilized to guarantee favorable tracking performance and stability of the whole system, meanwhile, wavelet neural network (WNN) is used for approximating nonlinear uncertainties. The designed controller combined the merits of the backstepping sliding mode control with robust characteristics ...

  20. 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.

  1. Stability and Time Delay Tolerance Analysis Approach for Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Ashraf F. Khalil

    2015-01-01

    Full Text Available Networked control system is a research area where the theory is behind practice. Closing the feedback loop through shared network induces time delay and some of the data could be lost. So the network induced time delay and data loss are inevitable in networked control Systems. The time delay may degrade the performance of control systems or even worse lead to system instability. Once the structure of a networked control system is confirmed, it is essential to identify the maximum time delay allowed for maintaining the system stability which, in turn, is also associated with the process of controller design. Some studies reported methods for estimating the maximum time delay allowed for maintaining system stability; however, most of the reported methods are normally overcomplicated for practical applications. A method based on the finite difference approximation is proposed in this paper for estimating the maximum time delay tolerance, which has a simple structure and is easy to apply.

  2. Study on the evolutionary optimization of the topology of network control systems

    DEFF Research Database (Denmark)

    Zhou, Z.; Chen, B.; Wang, H.

    2010-01-01

    Computer networks have been very popular in enterprise applications. However, optimisation of network designs that allows networks to be used more efficiently in industrial environment and enterprise applications remains an interesting research topic. This article mainly discusses the topology...... optimisation theory and methods of the network control system based on switched Ethernet in an industrial context. Factors that affect the real-time performance of the industrial control network are presented in detail, and optimisation criteria with their internal relations are analysed. After the definition...... control network are considered in the optimisation process. In respect to the evolutionary algorithm design, an improved arena algorithm is proposed for the construction of the non-dominated set of the population. In addition, for the evaluation of individuals, the integrated use of the dominative...

  3. Out of control: Fluctuation of cascading dynamics in networks

    Science.gov (United States)

    Wang, Jianwei; Cai, Lin; Xu, Bo; Li, Peng; Sun, Enhui; Zhu, Zhiguo

    2016-11-01

    Applying two preferential selection mechanisms of flow destination, we develop two new methods to quantify the initial load of a node, where the flow is transported along the shortest path between two nodes. We propose a simple cascading model and study cascading dynamics induced by attacking the node with the highest load in some synthetic and actual networks. Surprisingly, we observe the abnormal fluctuation of cascading dynamics, i.e., more damage can be triggered if we spend significantly higher cost to protect a network. In particular, this phenomenon is independent of the initial flow distribution and the preferential selection mechanisms of flow destination. However, it remains unclear which specific structural patterns may affect the fluctuation of cascading dynamics. In this paper, we examine the local evolution of the cascading propagation by constructing some special networks. We show that revivals of some nodes in the double ring structure facilitate the transportation of the flow between two unconnected sub-networks, cause more damage and subsequently lead to the abnormal fluctuation of cascading dynamics. Compared with the traditional definition of the betweenness, we adopt two new proposed methods to further evaluate the resilience of several actual networks. We find that some real world networks reach the strongest resilience level against cascading failures in our preferential selection mechanisms of flow destination. Moreover, we explore how to use the minimum cost to maximize the resilience of the studied networks.

  4. Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy

    Science.gov (United States)

    Sun, Yong-Zheng; Leng, Si-Yang; Lai, Ying-Cheng; Grebogi, Celso; Lin, Wei

    2017-11-01

    Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure. The closed-loop controller is tested on a large number of real systems including stem cell differentiation, food webs, random ecosystems, and spiking neuronal networks. Our results represent a step forward in developing a rigorous and general framework to control nonlinear dynamical networks with a complex topology.

  5. Media access control and resource allocation for next generation passive optical networks

    CERN Document Server

    Ansari, Nirwan

    2013-01-01

    This book focuses on various Passive optical networks (PONs)  types, including currently deployed Ethernet PON (EPON) and Gigabit PON (GPON) as well as next generation WDM PON and OFDM PON. Also this book examines the integrated optical and wireless access networks. Concentrating on two issues in these networks: media access control (MAC) and resource allocation. These two problems can greatly affect performances of PONs such as network resource utilization and QoS of end users. Finally this book will discuss various solutions to address the MAC and resource allocation issues in various PON networks.

  6. Runtime Performance and Virtual Network Control Alternatives in VM-Based High-Fidelity Network Simulations

    Science.gov (United States)

    2012-12-01

    network emulation systems have been proposed, such as V-eM (Apostolopoulos and Hasapis 2006), DieCast (Gupta et al. 2008), VENICE (Liu, Raju, and...Proceedings of the 2006 3rd Symposium on Networked Systems Design and Implementation (NSDI’06), San Jose, CA, USA. Gupta, D., et al. 2008. “ DieCast

  7. Role of graph architecture in controlling dynamical networks with applications to neural systems

    Science.gov (United States)

    Kim, Jason Z.; Soffer, Jonathan M.; Kahn, Ari E.; Vettel, Jean M.; Pasqualetti, Fabio; Bassett, Danielle S.

    2018-01-01

    Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

  8. Enhanced reliable transmission control protocol for spatial information networks

    Science.gov (United States)

    Qin, Zhihong; Zhang, Juan; Wang, Junfeng

    2009-12-01

    Satellites channels are generally featured by high bit error rate (BER), long propagation delay, large bandwidth-delay product (BDP) and so on. This tends to make the traditional TCP suffer from serious performance degradation in satellite networks. Therefore, a TCP-compatible reliable transmission protocol (i.e., TCP-AX) for spatial information networks is proposed in this paper. And a bandwidth probing mechanism is designed to distinguish network congestion and link error. Simulation results show that TCP-AX has better performance than some popular enhanced TCP protocols.

  9. Performance evaluation of a Software-Defined Network (SDN) controller

    OpenAIRE

    Casas Moreno, Xavier

    2016-01-01

    The 5th generation of mobile networks (5G) will enable access to information anywhere and anytime to anyone and anything, i.e., the so-called Networked Society. The details of 5G are still the subject of ongoing research and debate, mostly focused on understanding the radio technologies that can enable the 5G vision. On the other hand, less work has been dedicated so far to address the challenges that 5G will pose to the transport network infrastructure. These challenges include: (i) the capa...

  10. Large area controlled assembly of transparent conductive networks

    Science.gov (United States)

    Ivanov, Ilia N.; Simpson, John T.

    2015-09-29

    A method of preparing a network comprises disposing a solution comprising particulate materials in a solvent onto a superhydrophobic surface comprising a plurality of superhydrophobic features and interfacial areas between the superhydrophobic features. The plurality of superhydrophobic features has a water contact angle of at least about 150.degree.. The method of preparing the network also comprises removing the solvent from the solution of the particulate materials, and forming a network of the particulate materials in the interfacial areas, the particulate materials receding to the interfacial areas as the solvent is removed.

  11. Take control of your 802.11n airport network

    CERN Document Server

    Fleishman, Glenn

    2009-01-01

    Make your 802.11n-based AirPort network fast, reliable, and secure! Find real-world advice from Wi-Fi wizard Glenn Fleishman on setting up the 802.11n models of Apple's AirPort Express, AirPort Extreme, and Time Capsule, with full information about the simultaneous dual-band models introduced in early 2009. You'll get help with all the special networking details, such as how to set the best band and channel for your network, use pre-802.11n base stations and clients without hurting performance, set up complex Int

  12. A Grhl2-dependent gene network controls trophoblast branching morphogenesis.

    Science.gov (United States)

    Walentin, Katharina; Hinze, Christian; Werth, Max; Haase, Nadine; Varma, Saaket; Morell, Robert; Aue, Annekatrin; Pötschke, Elisabeth; Warburton, David; Qiu, Andong; Barasch, Jonathan; Purfürst, Bettina; Dieterich, Christoph; Popova, Elena; Bader, Michael; Dechend, Ralf; Staff, Anne Cathrine; Yurtdas, Zeliha Yesim; Kilic, Ergin; Schmidt-Ott, Kai M

    2015-03-15

    Healthy placental development is essential for reproductive success; failure of the feto-maternal interface results in pre-eclampsia and intrauterine growth retardation. We found that grainyhead-like 2 (GRHL2), a CP2-type transcription factor, is highly expressed in chorionic trophoblast cells, including basal chorionic trophoblast (BCT) cells located at the chorioallantoic interface in murine placentas. Placentas from Grhl2-deficient mouse embryos displayed defects in BCT cell polarity and basement membrane integrity at the chorioallantoic interface, as well as a severe disruption of labyrinth branching morphogenesis. Selective Grhl2 inactivation only in epiblast-derived cells rescued all placental defects but phenocopied intraembryonic defects observed in global Grhl2 deficiency, implying the importance of Grhl2 activity in trophectoderm-derived cells. ChIP-seq identified 5282 GRHL2 binding sites in placental tissue. By integrating these data with placental gene expression profiles, we identified direct and indirect Grhl2 targets and found a marked enrichment of GRHL2 binding adjacent to genes downregulated in Grhl2(-/-) placentas, which encoded known regulators of placental development and epithelial morphogenesis. These genes included that encoding the serine protease inhibitor Kunitz type 1 (Spint1), which regulates BCT cell integrity and labyrinth formation. In human placenta, we found that human orthologs of murine GRHL2 and its targets displayed co-regulation and were expressed in trophoblast cells in a similar domain as in mouse placenta. Our data indicate that a conserved Grhl2-coordinated gene network controls trophoblast branching morphogenesis, thereby facilitating development of the site of feto-maternal exchange. This might have implications for syndromes related to placental dysfunction. © 2015. Published by The Company of Biologists Ltd.

  13. 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

  14. Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Tat-Bao-Thien Nguyen

    2014-01-01

    Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

  15. Prioritizing connection requests in GMPLS-controlled optical networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Koster, A.; Andriolli, N.

    2009-01-01

    We prioritize bidirectional connection requests by combining dynamic connection provisioning with off-line optimization. Results show that the proposed approach decreases wavelength-converter usage, thereby allowing operators to reduce blocking-probably under bulk connection assignment or network...

  16. Resource Allocation and Cross Layer Control in Wireless Networks

    National Research Council Canada - National Science Library

    Georgiadis, L; Neely, M; Tassiulas, L

    2006-01-01

    .... In this paper we will present abstract models that capture the cross layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor...

  17. Event-driven model predictive control of sewage pumping stations for sulfide mitigation in sewer networks.

    Science.gov (United States)

    Liu, Yiqi; Ganigué, Ramon; Sharma, Keshab; Yuan, Zhiguo

    2016-07-01

    Chemicals such as Mg(OH)2 and iron salts are widely dosed to sewage for mitigating sulfide-induced corrosion and odour problems in sewer networks. The chemical dosing rate is usually not automatically controlled but profiled based on experience of operators, often resulting in over- or under-dosing. Even though on-line control algorithms for chemical dosing in single pipes have been developed recently, network-wide control algorithms are currently not available. The key challenge is that a sewer network is typically wide-spread comprising many interconnected sewer pipes and pumping stations, making network-wide sulfide mitigation with a relatively limited number of dosing points challenging. In this paper, we propose and demonstrate an Event-driven Model Predictive Control (EMPC) methodology, which controls the flows of sewage streams containing the dosed chemical to ensure desirable distribution of the dosed chemical throughout the pipe sections of interests. First of all, a network-state model is proposed to predict the chemical concentration in a network. An EMPC algorithm is then designed to coordinate sewage pumping station operations to ensure desirable chemical distribution in the network. The performance of the proposed control methodology is demonstrated by applying the designed algorithm to a real sewer network simulated with the well-established SeweX model using real sewage flow and characteristics data. The EMPC strategy significantly improved the sulfide mitigation performance with the same chemical consumption, compared to the current practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. CytoCtrlAnalyser: a Cytoscape app for biomolecular network controllability analysis.

    Science.gov (United States)

    Wu, Lin; Min, Li; Wang, Jianxin; Wu, Fang-Xiang

    2017-11-23

    Studying the controllability of biomolecular networks can result in profound knowledge about molecular biological systems. However, there is no comprehensive and easy-to-use platform for analyzing controllability of biomolecular networks although various algorithms for analyzing complex network controllability have been proposed recently. In this application note, we develop the CytoCtrlAnalyser which is a Cytoscape app to provide a comprehensive platform for analyzing controllability of biomolecular networks. Nine algorithms have been integrated in CytoCtrlAnalyser. With network topologies and customized control settings imported into CytoCtrlAnalyser, users can identify the steering nodes which should be actuated by input control signals for achieving different control objectives as well as investigate the importance of nodes from different perspectives in the controllability of networks. CytoCtrlAnalyser offers a tool for many promising applications, such as identification of potential drug targets or biologically important nodes in biomolecular networks. Freely available for downloading at http://apps.cytoscape.org/apps/cytoctrlanalyser. faw341@mail.usask.ca. Supplementary data are available at Bioinformatics online.

  19. Spacecraft Neural Network Control System Design using FPGA

    OpenAIRE

    Hanaa T. El-Madany; Faten H. Fahmy; Ninet M. A. El-Rahman; Hassen T. Dorrah

    2011-01-01

    Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffer...

  20. Decentralized Control of Unmanned Aerial Robots for Wireless Airborne Communication Networks

    Directory of Open Access Journals (Sweden)

    Deok-Jin Lee

    2010-09-01

    Full Text Available This paper presents a cooperative control strategy for a team of aerial robotic vehicles to establish wireless airborne communication networks between distributed heterogeneous vehicles. Each aerial robot serves as a flying mobile sensor performing a reconfigurable communication relay node which enabls communication networks with static or slow-moving nodes on gorund or ocean. For distributed optimal deployment of the aerial vehicles for communication networks, an adaptive hill-climbing type decentralized control algorithm is developed to seek out local extremum for optimal localization of the vehicles. The sensor networks estabilished by the decentralized cooperative control approach can adopt its configuraiton in response to signal strength as the function of the relative distance between the autonomous aerial robots and distributed sensor nodes in the sensed environment. Simulation studies are conducted to evaluate the effectiveness of the proposed decentralized cooperative control technique for robust communication networks.