Transport Protocols for Wireless Mesh Networks

NASA Astrophysics Data System (ADS)

Eddie Law, K. L.

Transmission control protocol (TCP) provides reliable connection-oriented services between any two end systems on the Internet. With TCP congestion control algorithm, multiple TCP connections can share network and link resources simultaneously. These TCP congestion control mechanisms have been operating effectively in wired networks. However, performance of TCP connections degrades rapidly in wireless and lossy networks. To sustain the throughput performance of TCP connections in wireless networks, design modifications may be required accordingly in the TCP flow control algorithm, and potentially, in association with other protocols in other layers for proper adaptations. In this chapter, we explain the limitations of the latest TCP congestion control algorithm, and then review some popular designs for TCP connections to operate effectively in wireless mesh network infrastructure.

An adaptive Hinfinity controller design for bank-to-turn missiles using ridge Gaussian neural networks.

PubMed

Lin, Chuan-Kai; Wang, Sheng-De

2004-11-01

A new autopilot design for bank-to-turn (BTT) missiles is presented. In the design of autopilot, a ridge Gaussian neural network with local learning capability and fewer tuning parameters than Gaussian neural networks is proposed to model the controlled nonlinear systems. We prove that the proposed ridge Gaussian neural network, which can be a universal approximator, equals the expansions of rotated and scaled Gaussian functions. Although ridge Gaussian neural networks can approximate the nonlinear and complex systems accurately, the small approximation errors may affect the tracking performance significantly. Therefore, by employing the Hinfinity control theory, it is easy to attenuate the effects of the approximation errors of the ridge Gaussian neural networks to a prescribed level. Computer simulation results confirm the effectiveness of the proposed ridge Gaussian neural networks-based autopilot with Hinfinity stabilization.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

PubMed

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

Designing Secure Library Networks.

ERIC Educational Resources Information Center

Breeding, Michael

1997-01-01

Focuses on designing a library network to maximize security. Discusses UNIX and file servers; connectivity to campus, corporate networks and the Internet; separation of staff from public servers; controlling traffic; the threat of network sniffers; hubs that eliminate eavesdropping; dividing the network into subnets; Switched Ethernet;…

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. 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 a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. 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 a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

[Network Design of the Spaceport Command and Control System

NASA Technical Reports Server (NTRS)

Teijeiro, Antonio

2017-01-01

I helped the Launch Control System (LCS) hardware team sustain the network design of the Spaceport Command and Control System. I wrote the procedure that will be used to satisfy an official hardware test for the hardware carrying data from the Launch Vehicle. I installed hardware and updated design documents in support of the ongoing development of the Spaceport Command and Control System and applied firewall experience I gained during my spring 2017 semester to inspect and create firewall security policies as requested. Finally, I completed several online courses concerning networking fundamentals and Unix operating systems.

Energy management and multi-layer control of networked microgrids

NASA Astrophysics Data System (ADS)

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.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

Backstepping fuzzy-neural-network control design for hybrid maglev transportation system.

PubMed

Wai, Rong-Jong; Yao, Jing-Xiang; Lee, Jeng-Dao

2015-02-01

This paper focuses on the design of a backstepping fuzzy-neural-network control (BFNNC) for the online levitated balancing and propulsive positioning of a hybrid magnetic levitation (maglev) transportation system. The dynamic model of the hybrid maglev transportation system including levitated hybrid electromagnets to reduce the suspension power loss and the friction force during linear movement and a propulsive linear induction motor based on the concepts of mechanical geometry and motion dynamics is first constructed. The ultimate goal is to design an online fuzzy neural network (FNN) control methodology to cope with the problem of the complicated control transformation and the chattering control effort in backstepping control (BSC) design, and to directly ensure the stability of the controlled system without the requirement of strict constraints, detailed system information, and auxiliary compensated controllers despite the existence of uncertainties. In the proposed BFNNC scheme, an FNN control is utilized to be the major control role by imitating the BSC strategy, and adaptation laws for network parameters are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance. The effectiveness of the proposed control strategy for the hybrid maglev transportation system is verified by experimental results, and the superiority of the BFNNC scheme is indicated in comparison with the BSC strategy and the backstepping particle-swarm-optimization control system in previous research.

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

DOT National Transportation Integrated Search

1996-01-01

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

Control of autonomous robot using neural networks

NASA Astrophysics Data System (ADS)

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.

Scheduling and Topology Design in Networks with Directional Antennas

DTIC Science & Technology

2017-05-19

emergency response networks was recently studied in [14] and [15]. This work examines the topology control problem in group - based wireless networks that...Broadcast Fig. 7: Max-min throughput ⇢ versus number of nodes for non -uniform edge capacities [14] T. Suzuki, et al. “Directional Antenna Control based...Scheduling and Topology Design in Networks with Directional Antennas Thomas Stahlbuhk, Nathaniel M. Jones, Brooke Shrader Lincoln Laboratory

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa.

PubMed

Roy, Sandip; McElwain, Terry F; Wan, Yan

2011-10-01

Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases.

A Network Control Theory Approach to Modeling and Optimal Control of Zoonoses: Case Study of Brucellosis Transmission in Sub-Saharan Africa

PubMed Central

Roy, Sandip; McElwain, Terry F.; Wan, Yan

2011-01-01

Background Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. Methodology/Principal Findings A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. Conclusions/Significance The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases. PMID:22022621

Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments.

PubMed

Gopalakrishnan, V; Subramanian, V; Baskaran, R; Venkatraman, B

2015-07-01

Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in a preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.

Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gopalakrishnan, V.; Subramanian, V.; Baskaran, R.

2015-07-15

Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in amore » preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.« less

Toward Optimal Transport Networks

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Structural Controllability of Temporal Networks with a Single Switching Controller

PubMed Central

Yao, Peng; Hou, Bao-Yu; Pan, Yu-Jian; Li, Xiang

2017-01-01

Temporal network, whose topology evolves with time, is an important class of complex networks. Temporal trees of a temporal network describe the necessary edges sustaining the network as well as their active time points. By a switching controller which properly selects its location with time, temporal trees are used to improve the controllability of the network. Therefore, more nodes are controlled within the limited time. Several switching strategies to efficiently select the location of the controller are designed, which are verified with synthetic and empirical temporal networks to achieve better control performance. PMID:28107538

Free-Energy-Based Design Policy for Robust Network Control against Environmental Fluctuation.

PubMed

Iwai, Takuya; Kominami, Daichi; Murata, Masayuki; Yomo, Tetsuya

2015-01-01

Bioinspired network control is a promising approach for realizing robust network controls. It relies on a probabilistic mechanism composed of positive and negative feedback that allows the system to eventually stabilize on the best solution. When the best solution fails due to environmental fluctuation, the system cannot keep its function until the system finds another solution again. To prevent the temporal loss of the function, the system should prepare some solution candidates and stochastically select available one from them. However, most bioinspired network controls are not designed with this issue in mind. In this paper, we propose a thermodynamics-based design policy that allows systems to retain an appropriate degree of randomness depending on the degree of environmental fluctuation, which prepares the system for the occurrence of environmental fluctuation. Furthermore, we verify the design policy by using an attractor selection model-based multipath routing to run simulation experiments.

Novel approaches to pin cluster synchronization on complex dynamical networks in Lur'e forms

NASA Astrophysics Data System (ADS)

Tang, Ze; Park, Ju H.; Feng, Jianwen

2018-04-01

This paper investigates the cluster synchronization of complex dynamical networks consisted of identical or nonidentical Lur'e systems. Due to the special topology structure of the complex networks and the existence of stochastic perturbations, a kind of randomly occurring pinning controller is designed which not only synchronizes all Lur'e systems in the same cluster but also decreases the negative influence among different clusters. Firstly, based on an extended integral inequality, the convex combination theorem and S-procedure, the conditions for cluster synchronization of identical Lur'e networks are derived in a convex domain. Secondly, randomly occurring adaptive pinning controllers with two independent Bernoulli stochastic variables are designed and then sufficient conditions are obtained for the cluster synchronization on complex networks consisted of nonidentical Lur'e systems. In addition, suitable control gains for successful cluster synchronization of nonidentical Lur'e networks are acquired by designing some adaptive updating laws. Finally, we present two numerical examples to demonstrate the validity of the control scheme and the theoretical analysis.

Programmable multi-node quantum network design and simulation

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

2016-05-01

Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

Smart home design for electronic devices monitoring based wireless gateway network using cisco packet tracer

NASA Astrophysics Data System (ADS)

Sihombing, Oloan; Zendrato, Niskarto; Laia, Yonata; Nababan, Marlince; Sitanggang, Delima; Purba, Windania; Batubara, Diarmansyah; Aisyah, Siti; Indra, Evta; Siregar, Saut

2018-04-01

In the era of technological development today, the technology has become the need for the life of today's society. One is needed to create a smart home in turning on and off electronic devices via smartphone. So far in turning off and turning the home electronic device is done by pressing the switch or remote button, so in control of electronic device control less effective. The home smart design is done by simulation concept by testing system, network configuration, and wireless home gateway computer network equipment required by a smart home network on cisco packet tracer using Internet Thing (IoT) control. In testing the IoT home network wireless network gateway system, multiple electronic devices can be controlled and monitored via smartphone based on predefined configuration conditions. With the Smart Ho me can potentially increase energy efficiency, decrease energy usage costs, control electronics and change the role of residents.

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

NASA Astrophysics Data System (ADS)

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.

Control Centrality and Hierarchical Structure in Complex Networks

PubMed Central

Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László

2012-01-01

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks. PMID:23028542

LMI designmethod for networked-based PID control

NASA Astrophysics Data System (ADS)

Souza, Fernando de Oliveira; Mozelli, Leonardo Amaral; de Oliveira, Maurício Carvalho; Palhares, Reinaldo Martinez

2016-10-01

In this paper, we propose a methodology for the design of networked PID controllers for second-order delayed processes using linear matrix inequalities. The proposed procedure takes into account time-varying delay on the plant, time-varying delays induced by the network and packed dropouts. The design is carried on entirely using a continuous-time model of the closed-loop system where time-varying delays are used to represent sampling and holding occurring in a discrete-time digital PID controller.

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

NASA Astrophysics Data System (ADS)

Li, Fangfei; Lu, Xiwen

2013-12-01

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

Receiver-exciter controller design

NASA Technical Reports Server (NTRS)

Jansma, P. A.

1982-01-01

A description of the general design of both the block 3 and block 4 receiver-exciter controllers for the Deep Space Network (DSN) Mark IV-A System is presented along with the design approach. The controllers are designed to enable the receiver-exciter subsystem (RCV) to be configured, calibrated, initialized and operated from a central location via high level instructions. The RECs are designed to be operated under the control of the DMC subsystem. The instructions are in the form of standard subsystem blocks (SSBs) received via the local area network (LAN). The centralized control provided by RECs and other DSCC controllers in Mark IV-A is intended to reduce DSN operations costs from the Mark III era.

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

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

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints because of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Thomas, George Lindsey; Culley, Dennis E.; Kratz, Jonathan L.

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints be- cause of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Finite-time synchronization control of a class of memristor-based recurrent neural networks.

PubMed

Jiang, Minghui; Wang, Shuangtao; Mei, Jun; Shen, Yanjun

2015-03-01

This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient conditions for finite-time synchronization between the master and corresponding slave memristor-based neural network with the designed controller. In comparison with the existing results, the proposed stability conditions are new, and the obtained results extend some previous works on conventional recurrent neural networks. Two numerical examples are provided to illustrate the effective of the design method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Passivity and Dissipativity as Design and Analysis Tools for Networked Control Systems

ERIC Educational Resources Information Center

Yu, Han

2012-01-01

In this dissertation, several control problems are studied that arise when passive or dissipative systems are interconnected and controlled over a communication network. Since communication networks can impact the systems' stability and performance, there is a need to extend the results on control of passive or dissipative systems to networked…

Design control system of telescope force actuators based on WLAN

NASA Astrophysics Data System (ADS)

Shuai, Xiaoying; Zhang, Zhenchao

2010-05-01

With the development of the technology of autocontrol, telescope, computer, network and communication, the control system of the modern large and extra lager telescope become more and more complicated, especially application of active optics. Large telescope based on active optics maybe contain enormous force actuators. This is a challenge to traditional control system based on wired networks, which result in difficult-to-manage, occupy signification space and lack of system flexibility. Wireless network can resolve these disadvantages of wired network. Presented control system of telescope force actuators based on WLAN (WFCS), designed the control system framework of WFCS. To improve the performance of real-time, we developed software of force actuators control system in Linux. Finally, this paper discussed improvement of WFCS real-time, conceived maybe improvement in the future.

Distributed synchronization control of complex networks with communication constraints.

PubMed

Xu, Zhenhua; Zhang, Dan; Song, Hongbo

2016-11-01

This paper is concerned with the distributed synchronization control of complex networks with communication constraints. In this work, the controllers communicate with each other through the wireless network, acting as a controller network. Due to the constrained transmission power, techniques such as the packet size reduction and transmission rate reduction schemes are proposed which could help reduce communication load of the controller network. The packet dropout problem is also considered in the controller design since it is often encountered in networked control systems. We show that the closed-loop system can be modeled as a switched system with uncertainties and random variables. By resorting to the switched system approach and some stochastic system analysis method, a new sufficient condition is firstly proposed such that the exponential synchronization is guaranteed in the mean-square sense. The controller gains are determined by using the well-known cone complementarity linearization (CCL) algorithm. Finally, a simulation study is performed, which demonstrates the effectiveness of the proposed design algorithm. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

PubMed

Yang, Qinmin; Jagannathan, Sarangapani

2012-04-01

In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

PubMed

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

PubMed Central

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

A programmable synthetic lineage-control network that differentiates human IPSCs into glucose-sensitive insulin-secreting beta-like cells

PubMed Central

Saxena, Pratik; Heng, Boon Chin; Bai, Peng; Folcher, Marc; Zulewski, Henryk; Fussenegger, Martin

2016-01-01

Synthetic biology has advanced the design of standardized transcription control devices that programme cellular behaviour. By coupling synthetic signalling cascade- and transcription factor-based gene switches with reverse and differential sensitivity to the licensed food additive vanillic acid, we designed a synthetic lineage-control network combining vanillic acid-triggered mutually exclusive expression switches for the transcription factors Ngn3 (neurogenin 3; OFF-ON-OFF) and Pdx1 (pancreatic and duodenal homeobox 1; ON-OFF-ON) with the concomitant induction of MafA (V-maf musculoaponeurotic fibrosarcoma oncogene homologue A; OFF-ON). This designer network consisting of different network topologies orchestrating the timely control of transgenic and genomic Ngn3, Pdx1 and MafA variants is able to programme human induced pluripotent stem cells (hIPSCs)-derived pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells, whose glucose-stimulated insulin-release dynamics are comparable to human pancreatic islets. Synthetic lineage-control networks may provide the missing link to genetically programme somatic cells into autologous cell phenotypes for regenerative medicine. PMID:27063289

The development of a fiber optics communication network for controlling a Multidegree-Of-Freedom Serpentine Truss

NASA Astrophysics Data System (ADS)

Andrawis, Alfred S.

1994-10-01

The problem addressed by this report is the large size and heavy weight of the cable bundle, used for controlling a Multidegree-Of-Freedom Serpentine Truss Manipulator arm, which imposes limitations on the manipulator arm maneuverability. This report covers a design of an optical fiber network to replace the existing copper wire network of the Serpentine Truss Manipulator. This report proposes a fiber network design which significantly reduces the bundle size into two phases. The first phase does not require any modifications for the manipulator architecture, while the other requires major modifications. Design philosophy, hardware details and schematic diagrams are presented.

The development of a fiber optics communication network for controlling a Multidegree-Of-Freedom Serpentine Truss

NASA Technical Reports Server (NTRS)

Andrawis, Alfred S.

1994-01-01

The problem addressed by this report is the large size and heavy weight of the cable bundle, used for controlling a Multidegree-Of-Freedom Serpentine Truss Manipulator arm, which imposes limitations on the manipulator arm maneuverability. This report covers a design of an optical fiber network to replace the existing copper wire network of the Serpentine Truss Manipulator. This report proposes a fiber network design which significantly reduces the bundle size into two phases. The first phase does not require any modifications for the manipulator architecture, while the other requires major modifications. Design philosophy, hardware details and schematic diagrams are presented.

A fault-tolerant small world topology control model in ad hoc networks for search and rescue

NASA Astrophysics Data System (ADS)

Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing

2018-02-01

Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.

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

NASA Astrophysics Data System (ADS)

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 on the network. To this end, we propose a distributed version of the classical logic-based supervisory control scheme. Given a network of agents whose dynamics contain unknown parameters, the distributed supervisory control scheme is used to assist the agents to converge to a certain set-point without requiring them to have explicit knowledge of that set-point. Unlike the classical supervisory control scheme where a centralized supervisor makes switching decisions among the candidate controllers, in our scheme, each agent is equipped with a local supervisor that switches among the available controllers. The switching decisions made at a certain agent depend only on the information from its neighboring agents. We provide sufficient conditions for stabilization and apply our framework to the distributed averaging problem in the presence of large modeling uncertainty. For infected networks, we study the stability properties of a susceptible-infected-susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary network topologies. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide conditions for the global asymptotic stability of the equilibrium points in both cases over strongly and weakly connected directed networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. Furthermore, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition, for the global convergence to the all-healthy state, that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control.

Design of Neural Networks for Fast Convergence and Accuracy

NASA Technical Reports Server (NTRS)

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

1998-01-01

A novel procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed to provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component spacecraft design changes and measures of its performance. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The design algorithm attempts to avoid the local minima phenomenon that hampers the traditional network training. A numerical example is performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

NASA Astrophysics Data System (ADS)

Aguado, Alejandro; Hugues-Salas, Emilio; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake E.; Erven, Chris; Rarity, John G.; Thompson, Mark Gerard; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

2017-04-01

We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

PubMed

Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

2016-12-08

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

A network control concept for the 30/20 GHz communication system baseband processor

NASA Technical Reports Server (NTRS)

Sabourin, D. J.; Hay, R. E.

1982-01-01

The architecture and system design for a satellite-switched TDMA communication system employing on-board processing was developed by Motorola for NASA's Lewis Research Center. The system design is based on distributed processing techniques that provide extreme flexibility in the selection of a network control protocol without impacting the satellite or ground terminal hardware. A network control concept that includes system synchronization and allows burst synchronization to occur within the system operational requirement is described. This concept integrates the tracking and control links with the communication links via the baseband processor, resulting in an autonomous system operational approach.

MYSEA: The Monterey Security Architecture

DTIC Science & Technology

2009-01-01

Security and Protection, Organization and Design General Terms: Design; Security Keywords: access controls, authentication, information flow controls...Applicable environments include: mil- itary coalitions, agencies and organizations responding to security emergencies, and mandated sharing in business ...network architecture affords users the abil- ity to securely access information across networks at dif- ferent classifications using standardized

Bio-inspired spiking neural network for nonlinear systems control.

PubMed

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

2018-08-01

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

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

PubMed

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.

Design of MPPT Controller Monitoring Software Based on QT Framework

NASA Astrophysics Data System (ADS)

Meng, X. Z.; Lu, P. G.

2017-10-01

The MPPT controller was a hardware device for tracking the maximum power point of solar photovoltaic array. Multiple controllers could be working as networking mode by specific communicating protocol. In this article, based on C++ GUI programming with Qt frame, we designed one sort of desktop application for monitoring and analyzing operational parameter of MPPT controller. The type of communicating protocol for building network was Modbus protocol which using Remote Terminal Unit mode and The desktop application of host computer was connected with all the controllers in the network through RS485 communication or ZigBee wireless communication. Using this application, user could monitor the parameter of controller wherever they were by internet.

An architecture for designing fuzzy logic controllers using neural networks

NASA Technical Reports Server (NTRS)

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.

The Use of Meta-Level Control for Coordination in a Distributed Problem Solving Network,

DTIC Science & Technology

1983-01-01

crucial aspect of the design organizational structuring in coordinating the local activity of achs decentralized network control policies. It is...TEMTED EXflD.MENTS WITn and ratings of the subgoals." Threshold values indicating ORGANIZATIONAL STRUCIURING IkeA usaw lani of a subal are specif’ied in...the monitoring are. This environmental vehicle, approximate position, time frame, and belief. The scenario was designed to test the networks ability

The analysis of transient noise of PCB P/G network based on PI/SI co-simulation

NASA Astrophysics Data System (ADS)

Haohang, Su

2018-02-01

With the frequency of the space camera become higher than before, the power noise of the imaging electronic system become the important factor. Much more power noise would disturb the transmissions signal, and even influence the image sharpness and system noise. "Target impedance method" is one of the traditional design method of P/G network (power and ground network), which is shorted of transient power noise analysis and often made "over design". In this paper, a new design method of P/G network is provided which simulated by PI/SI co-simulation. The transient power noise can be simulated and then applied in the design of noise reduction, thus effectively controlling the change of the noise in the P/G network. The method can efficiently control the number of adding decoupling capacitor, and is very efficient and feasible to keep the power integrity.

Fuzzy and neural control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Transformational Communications Architecture for the Unit Operations Center (UOC); Common Aviation Command and Control System (CAC2S); and Command and Control On-the-Move Network, Digital Over-the-Horizon Relay (CONDOR)

DTIC Science & Technology

2004-06-01

CAPABILITY SETS..............................................................................11 Figure 6. T3 DESIGN ...Radio System (JTRS) in 2008 and beyond. JTRS is being designed to provide a flexible new approach to meet diverse warfighter communications needs...Command and Control On-the-Move Network, Digital Over the Horizon Relay (CoNDOR) The CoNDOR Capability Set is an Architectural Approach designed to

Enhancing synchronization stability in a multi-area power grid

PubMed Central

Wang, Bing; Suzuki, Hideyuki; Aihara, Kazuyuki

2016-01-01

Maintaining a synchronous state of generators is of central importance to the normal operation of power grids, in which many networks are generally interconnected. In order to understand the condition under which the stability can be optimized, it is important to relate network stability with feedback control strategies as well as network structure. Here, we present a stability analysis on a multi-area power grid by relating it with several control strategies and topological design of network structure. We clarify the minimal feedback gain in the self-feedback control, and build the optimal communication network for the local and global control strategies. Finally, we consider relationship between the interconnection pattern and the synchronization stability; by optimizing the network interlinks, the obtained network shows better synchronization stability than the original network does, in particular, at a high power demand. Our analysis shows that interlinks between spatially distant nodes will improve the synchronization stability. The results seem unfeasible to be implemented in real systems but provide a potential guide for the design of stable power systems. PMID:27225708

The Command and Control of the Grand Armee: Napoleon as Organizational Designer

DTIC Science & Technology

2009-06-01

AUTHOR(S) Norman L. Durham 5. FUNDING NUMBERS 7 . PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000...served as the framework for a highly effective command and control system. This command and control network allowed Napoleon to dominate a war with...within his organizational design was a vast information network that served as the framework for a highly effective command and control system. This

Controllability of flow-conservation networks

NASA Astrophysics Data System (ADS)

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.

NIF ICCS network design and loading analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tietbohl, G; Bryant, R

The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow providemore » operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738).« less

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

PubMed

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

2017-04-06

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

A Unified Framework for Analyzing and Designing for Stationary Arterial Networks

DOT National Transportation Integrated Search

2017-05-17

This research aims to develop a unified theoretical and simulation framework for analyzing and designing signals for stationary arterial networks. Existing traffic flow models used in design and analysis of signal control strategies are either too si...

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: a simulation study.

PubMed

Padhi, Radhakant; Bhardhwaj, Jayender R

2009-06-01

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

The application of immune genetic algorithm in main steam temperature of PID control of BP network

NASA Astrophysics Data System (ADS)

Li, Han; Zhen-yu, Zhang

In order to overcome the uncertainties, large delay, large inertia and nonlinear property of the main steam temperature controlled object in the power plant, a neural network intelligent PID control system based on immune genetic algorithm and BP neural network is designed. Using the immune genetic algorithm global search optimization ability and good convergence, optimize the weights of the neural network, meanwhile adjusting PID parameters using BP network. The simulation result shows that the system is superior to conventional PID control system in the control of quality and robustness.

Distributed Coordinated Control of Large-Scale Nonlinear Networks

DOE PAGES

Kundu, Soumya; Anghel, Marian

2015-11-08

We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Compliance and Functional Testing of IEEE 1451.1 for NCAP-to-NCAP Communications in a Sensor Network

NASA Technical Reports Server (NTRS)

Figueroa, Jorge; Gurkan, Deniz; Yuan, X.; Benhaddou, D.; Liu, H.; Singla, A.; Franzl, R.; Ma, H.; Bhatt, S.; Morris, J.;

Application of Artificial Neural Networks to the Design of Turbomachinery Airfoils

NASA Technical Reports Server (NTRS)

Rai, Man Mohan; Madavan, Nateri

1997-01-01

Artificial neural networks are widely used in engineering applications, such as control, pattern recognition, plant modeling and condition monitoring to name just a few. In this seminar we will explore the possibility of applying neural networks to aerodynamic design, in particular, the design of turbomachinery airfoils. The principle idea behind this effort is to represent the design space using a neural network (within some parameter limits), and then to employ an optimization procedure to search this space for a solution that exhibits optimal performance characteristics. Results obtained for design problems in two spatial dimensions will be presented.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Algebraic and adaptive learning in neural control systems

NASA Astrophysics Data System (ADS)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

A Software Implementation of a Satellite Interface Message Processor.

ERIC Educational Resources Information Center

Eastwood, Margaret A.; Eastwood, Lester F., Jr.

A design for network control software for a computer network is described in which some nodes are linked by a communications satellite channel. It is assumed that the network has an ARPANET-like configuration; that is, that specialized processors at each node are responsible for message switching and network control. The purpose of the control…

Reliable and Fault-Tolerant Software-Defined Network Operations Scheme for Remote 3D Printing

NASA Astrophysics Data System (ADS)

Kim, Dongkyun; Gil, Joon-Min

2015-03-01

The recent wide expansion of applicable three-dimensional (3D) printing and software-defined networking (SDN) technologies has led to a great deal of attention being focused on efficient remote control of manufacturing processes. SDN is a renowned paradigm for network softwarization, which has helped facilitate remote manufacturing in association with high network performance, since SDN is designed to control network paths and traffic flows, guaranteeing improved quality of services by obtaining network requests from end-applications on demand through the separated SDN controller or control plane. However, current SDN approaches are generally focused on the controls and automation of the networks, which indicates that there is a lack of management plane development designed for a reliable and fault-tolerant SDN environment. Therefore, in addition to the inherent advantage of SDN, this paper proposes a new software-defined network operations center (SD-NOC) architecture to strengthen the reliability and fault-tolerance of SDN in terms of network operations and management in particular. The cooperation and orchestration between SDN and SD-NOC are also introduced for the SDN failover processes based on four principal SDN breakdown scenarios derived from the failures of the controller, SDN nodes, and connected links. The abovementioned SDN troubles significantly reduce the network reachability to remote devices (e.g., 3D printers, super high-definition cameras, etc.) and the reliability of relevant control processes. Our performance consideration and analysis results show that the proposed scheme can shrink operations and management overheads of SDN, which leads to the enhancement of responsiveness and reliability of SDN for remote 3D printing and control processes.

A conceptual ground-water-quality monitoring network for San Fernando Valley, California

USGS Publications Warehouse

Setmire, J.G.

1985-01-01

A conceptual groundwater-quality monitoring network was developed for San Fernando Valley to provide the California State Water Resources Control Board with an integrated, basinwide control system to monitor the quality of groundwater. The geology, occurrence and movement of groundwater, land use, background water quality, and potential sources of pollution were described and then considered in designing the conceptual monitoring network. The network was designed to monitor major known and potential point and nonpoint sources of groundwater contamination over time. The network is composed of 291 sites where wells are needed to define the groundwater quality. The ideal network includes four specific-purpose networks to monitor (1) ambient water quality, (2) nonpoint sources of pollution, (3) point sources of pollution, and (4) line sources of pollution. (USGS)

Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.

PubMed

Jeng, J T; Lee, T T

2000-01-01

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

An LMI approach to design H(infinity) controllers for discrete-time nonlinear systems based on unified models.

PubMed

Liu, Meiqin; Zhang, Senlin

2008-10-01

A unified neural network model termed standard neural network model (SNNM) is advanced. Based on the robust L(2) gain (i.e. robust H(infinity) performance) analysis of the SNNM with external disturbances, a state-feedback control law is designed for the SNNM to stabilize the closed-loop system and eliminate the effect of external disturbances. The control design constraints are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms (e.g. interior-point algorithms) to determine the control law. Most discrete-time recurrent neural network (RNNs) and discrete-time nonlinear systems modelled by neural networks or Takagi and Sugeno (T-S) fuzzy models can be transformed into the SNNMs to be robust H(infinity) performance analyzed or robust H(infinity) controller synthesized in a unified SNNM's framework. Finally, some examples are presented to illustrate the wide application of the SNNMs to the nonlinear systems, and the proposed approach is compared with related methods reported in the literature.

Design and performance evaluation of an OpenFlow-based control plane for software-defined elastic optical networks with direct-detection optical OFDM (DDO-OFDM) transmission.

PubMed

Liu, Lei; Peng, Wei-Ren; Casellas, Ramon; Tsuritani, Takehiro; Morita, Itsuro; Martínez, Ricardo; Muñoz, Raül; Yoo, S J B

2014-01-13

Optical Orthogonal Frequency Division Multiplexing (O-OFDM), which transmits high speed optical signals using multiple spectrally overlapped lower-speed subcarriers, is a promising candidate for supporting future elastic optical networks. In contrast to previous works which focus on Coherent Optical OFDM (CO-OFDM), in this paper, we consider the direct-detection optical OFDM (DDO-OFDM) as the transport technique, which leads to simpler hardware and software realizations, potentially offering a low-cost solution for elastic optical networks, especially in metro networks, and short or medium distance core networks. Based on this network scenario, we design and deploy a software-defined networking (SDN) control plane enabled by extending OpenFlow, detailing the network architecture, the routing and spectrum assignment algorithm, OpenFlow protocol extensions and the experimental validation. To the best of our knowledge, it is the first time that an OpenFlow-based control plane is reported and its performance is quantitatively measured in an elastic optical network with DDO-OFDM transmission.

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

Distributed dynamic simulations of networked control and building performance applications.

PubMed

Yahiaoui, Azzedine

2018-02-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper.

Distributed dynamic simulations of networked control and building performance applications

PubMed Central

Yahiaoui, Azzedine

2017-01-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper. PMID:29568135

Design and implementation of a software package to control a network of robotic observatories

NASA Astrophysics Data System (ADS)

Tuparev, G.; Nicolova, I.; Zlatanov, B.; Mihova, D.; Popova, I.; Hessman, F. V.

2006-09-01

We present a description of a reusable software package able to control a large, heterogeneous network of fully and semi-robotic observatories initially developed to run the MONET network of two 1.2 m telescopes. Special attention is given to the design of a robust, long-term observation scheduler which also allows the trading of observation time and facilities within various networks. The handling of the ``Phase I&II" project-development process, the time-accounting between complex organizational structures, and usability issues for making the package accessible not only to professional astronomers, but also to amateurs and high-school students is discussed. A simple RTML-based solution to link multiple networks is demonstrated.

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Optimal exponential synchronization of general chaotic delayed neural networks: an LMI approach.

PubMed

Liu, Meiqin

2009-09-01

This paper investigates the optimal exponential synchronization problem of general chaotic neural networks with or without time delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. This general model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs) with or without delays. Using the drive-response concept, time-delay feedback controllers are designed to synchronize two identical chaotic neural networks as quickly as possible. The control design equations are shown to be a generalized eigenvalue problem (GEVP) which can be easily solved by various convex optimization algorithms to determine the optimal control law and the optimal exponential synchronization rate. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

Application of neural networks with orthogonal activation functions in control of dynamical systems

NASA Astrophysics Data System (ADS)

Nikolić, Saša S.; Antić, Dragan S.; Milojković, Marko T.; Milovanović, Miroslav B.; Perić, Staniša Lj.; Mitić, Darko B.

2016-04-01

In this article, we present a new method for the synthesis of almost and quasi-orthogonal polynomials of arbitrary order. Filters designed on the bases of these functions are generators of generalised quasi-orthogonal signals for which we derived and presented necessary mathematical background. Based on theoretical results, we designed and practically implemented generalised first-order (k = 1) quasi-orthogonal filter and proved its quasi-orthogonality via performed experiments. Designed filters can be applied in many scientific areas. In this article, generated functions were successfully implemented in Nonlinear Auto Regressive eXogenous (NARX) neural network as activation functions. One practical application of the designed orthogonal neural network is demonstrated through the example of control of the complex technical non-linear system - laboratory magnetic levitation system. Obtained results were compared with neural networks with standard activation functions and orthogonal functions of trigonometric shape. The proposed network demonstrated superiority over existing solutions in the sense of system performances.

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

PubMed Central

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

2015-01-01

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. PMID:26674854

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

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

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

Analysis and Design of Complex Network Environments

DTIC Science & Technology

2012-03-01

and J. Lowe, “The myths and facts behind cyber security risks for industrial control systems ,” in the Proceedings of the VDE Kongress, VDE Congress...questions about 1) how to model them, 2) the design of experiments necessary to discover their structure (and thus adapt system inputs to optimize the...theoretical work that clarifies fundamental limitations of complex networks with network engineering and systems biology to implement specific designs and

Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

NASA Astrophysics Data System (ADS)

Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin

2017-05-01

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.

Research on NGN network control technology

NASA Astrophysics Data System (ADS)

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

2004-04-01

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

Neural network-based model reference adaptive control system.

PubMed

Patino, H D; Liu, D

2000-01-01

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

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

PubMed

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

2010-05-18

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

Observer design for compensation of network-induced delays in integrated communication and control systems

NASA Technical Reports Server (NTRS)

Luck, R.; Ray, A.

1988-01-01

A method for compensating the effects of network-induced delays in integrated communication and control systems (ICCS) is proposed, and a finite-dimensional time-invariant ICCS model is developed. The problem of analyzing systems with time-varying and stochastic delays is circumvented by the application of a deterministic observer. For the case of controller-to-actuator delays, the observed design must rely on an extended model which represents the delays as additional states.

Synchronization transmission of laser pattern signal within uncertain switched network

NASA Astrophysics Data System (ADS)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Nonlinear adaptive inverse control via the unified model neural network

NASA Astrophysics Data System (ADS)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

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

Some new results on stability and synchronization for delayed inertial neural networks based on non-reduced order method.

PubMed

Li, Xuanying; Li, Xiaotong; Hu, Cheng

2017-12-01

In this paper, without transforming the second order inertial neural networks into the first order differential systems by some variable substitutions, asymptotic stability and synchronization for a class of delayed inertial neural networks are investigated. Firstly, a new Lyapunov functional is constructed to directly propose the asymptotic stability of the inertial neural networks, and some new stability criteria are derived by means of Barbalat Lemma. Additionally, by designing a new feedback control strategy, the asymptotic synchronization of the addressed inertial networks is studied and some effective conditions are obtained. To reduce the control cost, an adaptive control scheme is designed to realize the asymptotic synchronization. It is noted that the dynamical behaviors of inertial neural networks are directly analyzed in this paper by constructing some new Lyapunov functionals, this is totally different from the traditional reduced-order variable substitution method. Finally, some numerical simulations are given to demonstrate the effectiveness of the derived theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

NASA Technical Reports Server (NTRS)

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.

Robust output feedback H∞ control for networked control systems based on the occurrence probabilities of time delays

NASA Astrophysics Data System (ADS)

Guo, Chenyu; Zhang, Weidong; Bao, Jie

2012-02-01

This article is concerned with the problem of robust H ∞ output feedback control for a kind of networked control systems with time-varying network-induced delays. Instead of using boundaries of time delays to represent all time delays, the occurrence probability of each time delay is considered in H∞ stability analysis and stabilisation. The problem addressed is the design of an output feedback controller such that, for all admissible uncertainties, the resulting closed-loop system is stochastically stable for the zero disturbance input and also simultaneously achieves a prescribed H∞ performance level. It is shown that less conservativeness is obtained. A set of linear matrix inequalities is given to solve the corresponding controller design problem. An example is provided to show the effectiveness and applicability of the proposed method.

Pinning impulsive control algorithms for complex network

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Development of a decentralized multi-axis synchronous control approach for real-time networks.

PubMed

Xu, Xiong; Gu, Guo-Ying; Xiong, Zhenhua; Sheng, Xinjun; Zhu, Xiangyang

2017-05-01

The message scheduling and the network-induced delays of real-time networks, together with the different inertias and disturbances in different axes, make the synchronous control of the real-time network-based systems quite challenging. To address this challenge, a decentralized multi-axis synchronous control approach is developed in this paper. Due to the limitations of message scheduling and network bandwidth, error of the position synchronization is firstly defined in the proposed control approach as a subset of preceding-axis pairs. Then, a motion message estimator is designed to reduce the effect of network delays. It is proven that position and synchronization errors asymptotically converge to zero in the proposed controller with the delay compensation. Finally, simulation and experimental results show that the developed control approach can achieve the good position synchronization performance for the multi-axis motion over the real-time network. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. 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. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

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

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. 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. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

Electrooptical adaptive switching network for the hypercube computer

NASA Technical Reports Server (NTRS)

Chow, E.; Peterson, J.

1988-01-01

An all-optical network design for the hyperswitch network using regular free-space interconnects between electronic processor nodes is presented. The adaptive routing model used is described, and an adaptive routing control example is presented. The design demonstrates that existing electrooptical techniques are sufficient for implementing efficient parallel architectures without the need for more complex means of implementing arbitrary interconnection schemes. The electrooptical hyperswitch network significantly improves the communication performance of the hypercube computer.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Computer Code for Transportation Network Design and Analysis

DOT National Transportation Integrated Search

1977-01-01

This document describes the results of research into the application of the mathematical programming technique of decomposition to practical transportation network problems. A computer code called Catnap (for Control Analysis Transportation Network A...

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.

Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

Ductile thermoset polymers via controlling network flexibility.

PubMed

Hameed, N; Salim, N V; Walsh, T R; Wiggins, J S; Ajayan, P M; Fox, B L

2015-06-18

We report the design and synthesis of a polymer structure from a cross-linkable epoxy-ionic liquid system which behaves like a hard and brittle epoxy thermoset, perfectly ductile thermoplastic and an elastomer, all depending on controllable network compositions.

New User Support in the University Network with DACS Scheme

ERIC Educational Resources Information Center

Odagiri, Kazuya; Yaegashi, Rihito; Tadauchi, Masaharu; Ishii, Naohiro

2007-01-01

Purpose: The purpose of this paper is to propose and examine the new user support in university network. Design/methodology/approach: The new user support is realized by use of DACS (Destination Addressing Control System) Scheme which manages a whole network system through communication control on a client computer. This DACS Scheme has been…

Optics derotator servo control system for SONG Telescope

NASA Astrophysics Data System (ADS)

Xu, Jin; Ren, Changzhi; Ye, Yu

2012-09-01

The Stellar Oscillations Network Group (SONG) is an initiative which aims at designing and building a groundbased network of 1m telescopes dedicated to the study of phenomena occurring in the time domain. Chinese standard node of SONG is an Alt-Az Telescope of F/37 with 1m diameter. Optics derotator control system of SONG telescope adopts the development model of "Industrial Computer + UMAC Motion Controller + Servo Motor".1 Industrial computer is the core processing part of the motion control, motion control card(UMAC) is in charge of the details on the motion control, Servo amplifier accepts the control commands from UMAC, and drives the servo motor. The position feedback information comes from the encoder, to form a closed loop control system. This paper describes in detail hardware design and software design for the optics derotator servo control system. In terms of hardware design, the principle, structure, and control algorithm of servo system based on optics derotator are analyzed and explored. In terms of software design, the paper proposes the architecture of the system software based on Object-Oriented Programming.

Toward Real Time Neural Net Flight Controllers

NASA Technical Reports Server (NTRS)

Jorgensen, C. C.; Mah, R. W.; Ross, J.; Lu, Henry, Jr. (Technical Monitor)

1994-01-01

NASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

PubMed

Peng, Zhouhua; Wang, Dan; Wang, Wei; Liu, Lu

2015-11-01

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Cyber-physical approach to the network-centric robotics control task

NASA Astrophysics Data System (ADS)

Muliukha, Vladimir; Ilyashenko, Alexander; Zaborovsky, Vladimir; Lukashin, Alexey

2016-10-01

Complex engineering tasks concerning control for groups of mobile robots are developed poorly. In our work for their formalization we use cyber-physical approach, which extends the range of engineering and physical methods for a design of complex technical objects by researching the informational aspects of communication and interaction between objects and with an external environment [1]. The paper analyzes network-centric methods for control of cyber-physical objects. Robots or cyber-physical objects interact with each other by transmitting information via computer networks using preemptive queueing system and randomized push-out mechanism [2],[3]. The main field of application for the results of our work is space robotics. The selection of cyber-physical systems as a special class of designed objects is due to the necessity of integrating various components responsible for computing, communications and control processes. Network-centric solutions allow using universal means for the organization of information exchange to integrate different technologies for the control system.

Design and Implementation of an Underlay Control Channel for Cognitive Radios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daryl Wasden; Hussein Moradi; Behrouz Farhang-Boroujeny

Implementation of any cognitive radio network requires an effective control channel that can operate under various modes of activity from the primary users. This paper reports the design and implementation of a filter bank multicarrier spread spectrum (FBMC-SS) system for use as the control channel in cognitive radio networks. The proposed design is based on a filtered multitone (FMT) implementation. Carrier and timing acquisition and tracking methods as well as a blind channel estimation method are developed for the proposed control channel. We also report an implementation of the proposed FBMC-SS system on a hardware platform; a FlexRIO FPGA modulemore » from National Instruments.« less

A tangent-ring optical TWDM-MAN enabling three-level transregional reconfigurations and shared protections by multipoint distributed control

NASA Astrophysics Data System (ADS)

Gou, Kaiyu; Gan, Chaoqin; Zhang, Xiaoyu; Zhang, Yuchao

2018-03-01

An optical time-and-wavelength-division-multiplexing metro-access network (TWDM-MAN) is proposed and demonstrated in this paper. By the reuse of tangent-ring optical distribution network and the design of distributed control mechanism, ONUs needing to communicate with each other can be flexibly accessed to successfully make up three kinds of reconfigurable networks. By the nature advantage of ring topology in protection, three-level comprehensive protections covering both feeder and distribution fibers are also achieved. Besides, a distributed wavelength allocation (DWA) is designed to support efficient parallel upstream transmission. The analyses including capacity, congestion and transmission simulation show that this network has a great performance.

Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output.

PubMed

Nochomovitz, Yigal D; Li, Hao

2006-03-14

Deciphering the design principles for regulatory networks is fundamental to an understanding of biological systems. We have explored the mapping from the space of network topologies to the space of dynamical phenotypes for small networks. Using exhaustive enumeration of a simple model of three- and four-node networks, we demonstrate that certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences. The network topologies that encode a highly designable dynamical phenotype possess two classes of connections: a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and a partially conserved set of variable connections that controls the transient dynamical flow. By comparing the topologies and dynamics of the three- and four-node network ensembles, we observe a large number of instances of the phenomenon of "mutational buffering," whereby addition of a fourth node suppresses phenotypic variation amongst a set of three-node networks.

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a neural network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. The neural network technique works well not only as an interpolating device but also as an extrapolating device to achieve blade designs from a given database. Two validating test cases are discussed.

Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer.

PubMed

He, Wei; Yan, Zichen; Sun, Changyin; Chen, Yunan

2017-10-01

The research of this paper works out the attitude and position control of the flapping wing micro aerial vehicle (FWMAV). Neural network control with full state and output feedback are designed to deal with uncertainties in this complex nonlinear FWMAV dynamic system and enhance the system robustness. Meanwhile, we design disturbance observers which are exerted into the FWMAV system via feedforward loops to counteract the bad influence of disturbances. Then, a Lyapunov function is proposed to prove the closed-loop system stability and the semi-global uniform ultimate boundedness of all state variables. Finally, a series of simulation results indicate that proposed controllers can track desired trajectories well via selecting appropriate control gains. And the designed controllers possess potential applications in FWMAVs.

Digital Signal Processing and Control for the Study of Gene Networks

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun

2016-04-01

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.

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

PubMed

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.

Digital Signal Processing and Control for the Study of Gene Networks

PubMed Central

Shin, Yong-Jun

2016-01-01

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. PMID:27102828

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Efficient evaluation of wireless real-time control networks.

PubMed

Horvath, Peter; Yampolskiy, Mark; Koutsoukos, Xenofon

2015-02-11

In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

Communication Needs Assessment for Distributed Turbine Engine Control

NASA Technical Reports Server (NTRS)

Culley, Dennis E.; Behbahani, Alireza R.

2008-01-01

Control system architecture is a major contributor to future propulsion engine performance enhancement and life cycle cost reduction. The control system architecture can be a means to effect net weight reduction in future engine systems, provide a streamlined approach to system design and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a centralized, point-to-point analog control topology to a modular, networked, distributed system is paramount to extracting these system improvements. However, distributed engine control systems are only possible through the successful design and implementation of a suitable communication system. In a networked system, understanding the data flow between control elements is a fundamental requirement for specifying the communication architecture which, itself, is dependent on the functional capability of electronics in the engine environment. This paper presents an assessment of the communication needs for distributed control using strawman designs and relates how system design decisions relate to overall goals as we progress from the baseline centralized architecture, through partially distributed and fully distributed control systems.

RACOON: a multiuser QoS design for mobile wireless body area networks.

PubMed

Cheng, Shihheng; Huang, Chingyao; Tu, Chun Chen

2011-10-01

In this study, Random Contention-based Resource Allocation (RACOON) medium access control (MAC) protocol is proposed to support the quality of service (QoS) for multi-user mobile wireless body area networks (WBANs). Different from existing QoS designs that focus on a single WBAN, a multiuser WBAN QoS should further consider both inter-WBAN interference and inter-WBAN priorities. Similar problems have been studied in both overlapped wireless local area networks (WLANs) and Bluetooth piconets that need QoS supports. However, these solutions are designed for non-medical transmissions that do not consider any priority scheme for medical applications. Most importantly, these studies focus on only static or low mobility networks. Network mobility of WBANs will introduce unnecessary inter-network collisions and energy waste, which are not considered by these solutions. The proposed multiuser-QoS protocol, RACOON, simultaneously satisfies the inter WBAN QoS requirements and overcomes the performance degradation caused by WBAN mobility. Simulation results verify that RACOON provides better latency and energy control, as compared with WBAN QoS protocols without considering the inter-WBAN requirements.

The NASA Fireball Network All-Sky Cameras

NASA Technical Reports Server (NTRS)

Suggs, Rob M.

2011-01-01

The construction of small, inexpensive all-sky cameras designed specifically for the NASA Fireball Network is described. The use of off-the-shelf electronics, optics, and plumbing materials results in a robust and easy to duplicate design. Engineering challenges such as weather-proofing and thermal control and their mitigation are described. Field-of-view and gain adjustments to assure uniformity across the network will also be detailed.

Identification and control of plasma vertical position using neural network in Damavand tokamak.

PubMed

Rasouli, H; Rasouli, C; Koohi, A

2013-02-01

In this work, a nonlinear model is introduced to determine the vertical position of the plasma column in Damavand tokamak. Using this model as a simulator, a nonlinear neural network controller has been designed. In the first stage, the electronic drive and sensory circuits of Damavand tokamak are modified. These circuits can control the vertical position of the plasma column inside the vacuum vessel. Since the vertical position of plasma is an unstable parameter, a direct closed loop system identification algorithm is performed. In the second stage, a nonlinear model is identified for plasma vertical position, based on the multilayer perceptron (MLP) neural network (NN) structure. Estimation of simulator parameters has been performed by back-propagation error algorithm using Levenberg-Marquardt gradient descent optimization technique. The model is verified through simulation of the whole closed loop system using both simulator and actual plant in similar conditions. As the final stage, a MLP neural network controller is designed for simulator model. In the last step, online training is performed to tune the controller parameters. Simulation results justify using of the NN controller for the actual plant.

Software-Enabled Distributed Network Governance: The PopMedNet Experience.

PubMed

Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

2016-01-01

The expanded availability of electronic health information has led to increased interest in distributed health data research networks. The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Four case studies describe how PopMedNet is used to enforce network governance models. Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.

Design of a ground-water-quality monitoring network for the Salinas River basin, California

USGS Publications Warehouse

Showalter, P.K.; Akers, J.P.; Swain, L.A.

1984-01-01

A regional ground-water quality monitoring network for the entire Salinas River drainage basin was designed to meet the needs of the California State Water Resources Control Board. The project included phase 1--identifying monitoring networks that exist in the region; phase 2--collecting information about the wells in each network; and phase 3--studying the factors--such as geology, land use, hydrology, and geohydrology--that influence the ground-water quality, and designing a regional network. This report is the major product of phase 3. Based on the authors ' understanding of the ground-water-quality monitoring system and input from local offices, an ideal network was designed. The proposed network includes 317 wells and 8 stream-gaging stations. Because limited funds are available to implement the monitoring network, the proposed network is designed to correspond to the ideal network insofar as practicable, and is composed mainly of 214 wells that are already being monitored by a local agency. In areas where network wells are not available, arrangements will be made to add wells to local networks. The data collected by this network will be used to assess the ground-water quality of the entire Salinas River drainage basin. After 2 years of data are collected, the network will be evaluated to test whether it is meeting the network objectives. Subsequent network evaluations will be done very 5 years. (USGS)

Two-layer wireless distributed sensor/control network based on RF

NASA Astrophysics Data System (ADS)

Feng, Li; Lin, Yuchi; Zhou, Jingjing; Dong, Guimei; Xia, Guisuo

2006-11-01

A project of embedded Wireless Distributed Sensor/Control Network (WDSCN) based on RF is presented after analyzing the disadvantages of traditional measure and control system. Because of high-cost and complexity, such wireless techniques as Bluetooth and WiFi can't meet the needs of WDSCN. The two-layer WDSCN is designed based on RF technique, which operates in the ISM free frequency channel with low power and high transmission speed. Also the network is low cost, portable and moveable, integrated with the technologies of computer network, sensor, microprocessor and wireless communications. The two-layer network topology is selected in the system; a simple but efficient self-organization net protocol is designed to fit the periodic data collection, event-driven and store-and-forward. Furthermore, adaptive frequency hopping technique is adopted for anti-jamming apparently. The problems about power reduction and synchronization of data in wireless system are solved efficiently. Based on the discussion above, a measure and control network is set up to control such typical instruments and sensors as temperature sensor and signal converter, collect data, and monitor environmental parameters around. This system works well in different rooms. Experiment results show that the system provides an efficient solution to WDSCN through wireless links, with high efficiency, low power, high stability, flexibility and wide working range.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.

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

PubMed

Liu, Xuemei; Ge, Baofeng

2012-04-01

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

REAL TIME CONTROL OF URBAN DRAINAGE NETWORKS

EPA Science Inventory

Real-time control (RTC) is a custom-designed, computer-assisted management technology for a specific sewerage network to meet the operational objectives of its collection/conveyance system. RTC can operate in several modes, including a mode that is activated during a wet weather ...

Evolutionary Computation with Spatial Receding Horizon Control to Minimize Network Coding Resources

PubMed Central

Leeson, Mark S.

2014-01-01

The minimization of network coding resources, such as coding nodes and links, is a challenging task, not only because it is a NP-hard problem, but also because the problem scale is huge; for example, networks in real world may have thousands or even millions of nodes and links. Genetic algorithms (GAs) have a good potential of resolving NP-hard problems like the network coding problem (NCP), but as a population-based algorithm, serious scalability and applicability problems are often confronted when GAs are applied to large- or huge-scale systems. Inspired by the temporal receding horizon control in control engineering, this paper proposes a novel spatial receding horizon control (SRHC) strategy as a network partitioning technology, and then designs an efficient GA to tackle the NCP. Traditional network partitioning methods can be viewed as a special case of the proposed SRHC, that is, one-step-wide SRHC, whilst the method in this paper is a generalized N-step-wide SRHC, which can make a better use of global information of network topologies. Besides the SRHC strategy, some useful designs are also reported in this paper. The advantages of the proposed SRHC and GA for the NCP are illustrated by extensive experiments, and they have a good potential of being extended to other large-scale complex problems. PMID:24883371

Model-based Compositional Design of Networked Control Systems

DTIC Science & Technology

2013-12-01

communication network. As described in Section 1.2, although there are several advantages in using NCS, there exist some drawbacks due to the presence of the... pendulum was used to demonstrate the approach, the results showed desirable performance in the presence of time delays. The passivity of the...certain level of performance under a wide range of failures, the designed controller is typically conservative. The drawback of this approach is that one

Soft sensor based composition estimation and controller design for an ideal reactive distillation column.

PubMed

Vijaya Raghavan, S R; Radhakrishnan, T K; Srinivasan, K

2011-01-01

In this research work, the authors have presented the design and implementation of a recurrent neural network (RNN) based inferential state estimation scheme for an ideal reactive distillation column. Decentralized PI controllers are designed and implemented. The reactive distillation process is controlled by controlling the composition which has been estimated from the available temperature measurements using a type of RNN called Time Delayed Neural Network (TDNN). The performance of the RNN based state estimation scheme under both open loop and closed loop have been compared with a standard Extended Kalman filter (EKF) and a Feed forward Neural Network (FNN). The online training/correction has been done for both RNN and FNN schemes for every ten minutes whenever new un-trained measurements are available from a conventional composition analyzer. The performance of RNN shows better state estimation capability as compared to other state estimation schemes in terms of qualitative and quantitative performance indices. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

Neural network-based optimal adaptive output feedback control of a helicopter UAV.

PubMed

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

On-board processing satellite network architectures for broadband ISDN

NASA Technical Reports Server (NTRS)

Inukai, Thomas; Faris, Faris; Shyy, Dong-Jye

1992-01-01

Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

RAID-2: Design and implementation of a large scale disk array controller

NASA Technical Reports Server (NTRS)

Katz, R. H.; Chen, P. M.; Drapeau, A. L.; Lee, E. K.; Lutz, K.; Miller, E. L.; Seshan, S.; Patterson, D. A.

1992-01-01

We describe the implementation of a large scale disk array controller and subsystem incorporating over 100 high performance 3.5 inch disk drives. It is designed to provide 40 MB/s sustained performance and 40 GB capacity in three 19 inch racks. The array controller forms an integral part of a file server that attaches to a Gb/s local area network. The controller implements a high bandwidth interconnect between an interleaved memory, an XOR calculation engine, the network interface (HIPPI), and the disk interfaces (SCSI). The system is now functionally operational, and we are tuning its performance. We review the design decisions, history, and lessons learned from this three year university implementation effort to construct a truly large scale system assembly.

Controller design for global fixed-time synchronization of delayed neural networks with discontinuous activations.

PubMed

Wang, Leimin; Zeng, Zhigang; Hu, Junhao; Wang, Xiaoping

2017-03-01

This paper addresses the controller design problem for global fixed-time synchronization of delayed neural networks (DNNs) with discontinuous activations. To solve this problem, adaptive control and state feedback control laws are designed. Then based on the two controllers and two lemmas, the error system is proved to be globally asymptotically stable and even fixed-time stable. Moreover, some sufficient and easy checked conditions are derived to guarantee the global synchronization of drive and response systems in fixed time. It is noted that the settling time functional for fixed-time synchronization is independent on initial conditions. Our fixed-time synchronization results contain the finite-time results as the special cases by choosing different values of the two controllers. Finally, theoretical results are supported by numerical simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural-tree call admission controller for ATM networks

NASA Astrophysics Data System (ADS)

Rughooputh, Harry C. S.

1999-03-01

Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.

Interaction Control to Synchronize Non-synchronizable Networks.

PubMed

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-11-17

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks' exact interaction topology and consequently have implications for biological and self-organizing technical systems.

The design of the automated control system for warehouse equipment under radio-electronic manufacturing

NASA Astrophysics Data System (ADS)

Kapulin, D. V.; Chemidov, I. V.; Kazantsev, M. A.

2017-01-01

In the paper, the aspects of design, development and implementation of the automated control system for warehousing under the manufacturing process of the radio-electronic enterprise JSC «Radiosvyaz» are discussed. The architecture of the automated control system for warehousing proposed in the paper consists of a server which is connected to the physically separated information networks: the network with a database server, which stores information about the orders for picking, and the network with the automated storage and retrieval system. This principle allows implementing the requirements for differentiation of access, ensuring the information safety and security requirements. Also, the efficiency of the developed automated solutions in terms of optimizing the warehouse’s logistic characteristics is researched.

Food Web Designer: a flexible tool to visualize interaction networks.

PubMed

Sint, Daniela; Traugott, Michael

Species are embedded in complex networks of ecological interactions and assessing these networks provides a powerful approach to understand what the consequences of these interactions are for ecosystem functioning and services. This is mandatory to develop and evaluate strategies for the management and control of pests. Graphical representations of networks can help recognize patterns that might be overlooked otherwise. However, there is a lack of software which allows visualizing these complex interaction networks. Food Web Designer is a stand-alone, highly flexible and user friendly software tool to quantitatively visualize trophic and other types of bipartite and tripartite interaction networks. It is offered free of charge for use on Microsoft Windows platforms. Food Web Designer is easy to use without the need to learn a specific syntax due to its graphical user interface. Up to three (trophic) levels can be connected using links cascading from or pointing towards the taxa within each level to illustrate top-down and bottom-up connections. Link width/strength and abundance of taxa can be quantified, allowing generating fully quantitative networks. Network datasets can be imported, saved for later adjustment and the interaction webs can be exported as pictures for graphical display in different file formats. We show how Food Web Designer can be used to draw predator-prey and host-parasitoid food webs, demonstrating that this software is a simple and straightforward tool to graphically display interaction networks for assessing pest control or any other type of interaction in both managed and natural ecosystems from an ecological network perspective.

On Improved Least Squares Regression and Artificial Neural Network Meta-Models for Simulation via Control Variates

DTIC Science & Technology

2016-09-15

18] under the context of robust parameter design for simulation. Bellucci’s technique is used in this research, primarily because the interior -point...Fundamentals of Radial Basis Neural Network (RBNN) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 1.2.2.2 Design of Experiments...with Neural Nets . . . . . . . . . . . . . 31 1.2.2.3 Factorial Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 1.2.2.4

Design and implementation of an Internet based effective controlling and monitoring system with wireless fieldbus communications technologies for process automation--an experimental study.

PubMed

Cetinceviz, Yucel; Bayindir, Ramazan

2012-05-01

The network requirements of control systems in industrial applications increase day by day. The Internet based control system and various fieldbus systems have been designed in order to meet these requirements. This paper describes an Internet based control system with wireless fieldbus communication designed for distributed processes. The system was implemented as an experimental setup in a laboratory. In industrial facilities, the process control layer and the distance connection of the distributed control devices in the lowest levels of the industrial production environment are provided with fieldbus networks. In this paper, the Internet based control system that will be able to meet the system requirements with a new-generation communication structure, which is called wired/wireless hybrid system, has been designed on field level and carried out to cover all sectors of distributed automation, from process control, to distributed input/output (I/O). The system has been accomplished by hardware structure with a programmable logic controller (PLC), a communication processor (CP) module, two industrial wireless modules and a distributed I/O module, Motor Protection Package (MPP) and software structure with WinCC flexible program used for the screen of Scada (Supervisory Control And Data Acquisition), SIMATIC MANAGER package program ("STEP7") used for the hardware and network configuration and also for downloading control program to PLC. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Controlling gene networks and cell fate with precision-targeted DNA-binding proteins and small-molecule-based genome readers

PubMed Central

Eguchi, Asuka; Lee, Garrett O.; Wan, Fang; Erwin, Graham S.; Ansari, Aseem Z.

2014-01-01

Transcription factors control the fate of a cell by regulating the expression of genes and regulatory networks. Recent successes in inducing pluripotency in terminally differentiated cells as well as directing differentiation with natural transcription factors has lent credence to the efforts that aim to direct cell fate with rationally designed transcription factors. Because DNA-binding factors are modular in design, they can be engineered to target specific genomic sequences and perform pre-programmed regulatory functions upon binding. Such precision-tailored factors can serve as molecular tools to reprogramme or differentiate cells in a targeted manner. Using different types of engineered DNA binders, both regulatory transcriptional controls of gene networks, as well as permanent alteration of genomic content, can be implemented to study cell fate decisions. In the present review, we describe the current state of the art in artificial transcription factor design and the exciting prospect of employing artificial DNA-binding factors to manipulate the transcriptional networks as well as epigenetic landscapes that govern cell fate. PMID:25145439

Study of mobile satellite network based on GEO/LEO satellite constellation

NASA Astrophysics Data System (ADS)

Hu, Xiulin; Zeng, Yujiang; Wang, Ying; Wang, Xianhui

2005-11-01

Mobile satellite network with Inter Satellite Links (ISLs), which consists of non-geostationary satellites, has the characteristic of network topology's variability. This is a great challenge to the design and management of mobile satellite network. This paper analyzes the characteristics of mobile satellite network, takes multimedia Quality of Service (QoS) as the chief object and presents a reference model based on Geostationary Earth Orbit (GEO)/ Low Earth Orbit (LEO) satellite constellation which adapts to the design and management of mobile satellite network. In the reference model, LEO satellites constitute service subnet with responsibility for the access, transmission and switch of the multimedia services for mobile users, while GEO satellites constitute management subnet taking on the centralized management to service subnet. Additionally ground control centre realizes the whole monitoring and control via management subnet. Comparing with terrestrial network, the above reference model physically separates management subnet from service subnet, which not only enhances the advantage of centralized management but also overcomes the shortcoming of low reliability in terrestrial network. Routing of mobile satellite network based on GEO/LEO satellite constellation is also discussed in this paper.

Definition and evaluation of the data-link layer of PACnet

NASA Astrophysics Data System (ADS)

Alsafadi, Yasser H.; Martinez, Ralph; Sanders, William H.

1991-07-01

PACnet is a 200-500 Mbps dual-ring fiber optic network designed to implement a picture archiving and communication system (PACS) in a hospital environment. The network consists of three channels: an image transfer channel, a command and control channel, and a real-time data channel. An initial network interface unit (NIU) design for PACnet consisted of a functional description of the protocols and NIU major components. In order to develop a demonstration prototype, additional definition of protocol algorithms of each channel is necessary. Using the International Standards Organization/Open Systems Interconnection (ISO/OSI) reference model as a guide, the definition of the data link layer is extended. This definition covers interface service specifications for the two constituent sublayers: logical link control (LLC) and medium access control (MAC). Furthermore, it describes procedures for data transfer, mechanisms of error detection and fault recovery. A performance evaluation study was then made to determine how the network performs under various application scenarios. The performance evaluation study was performed using stochastic activity networks, which can formally describe the network behavior. The results of the study demonstrate the feasibility of PACnet as an integrated image, data, and voice network for PACS.

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

NASA Astrophysics Data System (ADS)

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.

Research and realization of info-net security controlling system

NASA Astrophysics Data System (ADS)

Xu, Tao; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-03-01

The thesis introduces some relative concepts about Network Cybernetics, and we design and realize a new info-net security controlling system based on Network Cybernetics. The system can control the endpoints, safely save files, encrypt communication, supervise actions of users and show security conditions, in order to realize full-scale security management. At last, we simulate the functions of the system. The results show, the system can ensure the controllability of users and devices, and supervise them real-time. The system can maximize the security of the network and users.

Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters.

PubMed

Wang, Dandan; Zong, Qun; Tian, Bailing; Shao, Shikai; Zhang, Xiuyun; Zhao, Xinyi

2018-02-01

The distributed finite-time formation tracking control problem for multiple unmanned helicopters is investigated in this paper. The control object is to maintain the positions of follower helicopters in formation with external interferences. The helicopter model is divided into a second order outer-loop subsystem and a second order inner-loop subsystem based on multiple-time scale features. Using radial basis function neural network (RBFNN) technique, we first propose a novel finite-time multivariable neural network disturbance observer (FMNNDO) to estimate the external disturbance and model uncertainty, where the neural network (NN) approximation errors can be dynamically compensated by adaptive law. Next, based on FMNNDO, a distributed finite-time formation tracking controller and a finite-time attitude tracking controller are designed using the nonsingular fast terminal sliding mode (NFTSM) method. In order to estimate the second derivative of the virtual desired attitude signal, a novel finite-time sliding mode integral filter is designed. Finally, Lyapunov analysis and multiple-time scale principle ensure the realization of control goal in finite-time. The effectiveness of the proposed FMNNDO and controllers are then verified by numerical simulations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

2016-09-01

A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

A Framework for Engineering Stress Resilient Plants Using Genetic Feedback Control and Regulatory Network Rewiring.

PubMed

Foo, Mathias; Gherman, Iulia; Zhang, Peijun; Bates, Declan G; Denby, Katherine J

2018-05-23

Crop disease leads to significant waste worldwide, both pre- and postharvest, with subsequent economic and sustainability consequences. Disease outcome is determined both by the plants' response to the pathogen and by the ability of the pathogen to suppress defense responses and manipulate the plant to enhance colonization. The defense response of a plant is characterized by significant transcriptional reprogramming mediated by underlying gene regulatory networks, and components of these networks are often targeted by attacking pathogens. Here, using gene expression data from Botrytis cinerea-infected Arabidopsis plants, we develop a systematic approach for mitigating the effects of pathogen-induced network perturbations, using the tools of synthetic biology. We employ network inference and system identification techniques to build an accurate model of an Arabidopsis defense subnetwork that contains key genes determining susceptibility of the plant to the pathogen attack. Once validated against time-series data, we use this model to design and test perturbation mitigation strategies based on the use of genetic feedback control. We show how a synthetic feedback controller can be designed to attenuate the effect of external perturbations on the transcription factor CHE in our subnetwork. We investigate and compare two approaches for implementing such a controller biologically-direct implementation of the genetic feedback controller, and rewiring the regulatory regions of multiple genes-to achieve the network motif required to implement the controller. Our results highlight the potential of combining feedback control theory with synthetic biology for engineering plants with enhanced resilience to environmental stress.

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

NASA Astrophysics Data System (ADS)

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.

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

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 behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. 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 behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

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

NASA Astrophysics Data System (ADS)

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.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

NASA Astrophysics Data System (ADS)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

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

NASA Astrophysics Data System (ADS)

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.

Prediction and control of chaotic processes using nonlinear adaptive networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, R.D.; Barnes, C.W.; Flake, G.W.

1990-01-01

We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

Constrained target controllability of complex networks

NASA Astrophysics Data System (ADS)

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.

Coactivation of cognitive control networks during task switching.

PubMed

Yin, Shouhang; Deák, Gedeon; Chen, Antao

2018-01-01

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) 2018 APA, all rights reserved).

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.

A Network Thermodynamic Framework for the Analysis and Control Design of Large-Scale Dynamical Systems

DTIC Science & Technology

2006-03-31

Nonnegative Dynamical Sys- tems................................................. 18 2.10. Adaptive Control for General Anesthesia and Intensive Care...Unit Sedation 20 2.11. Neural Network Adaptive Control for Intensive Care Unit Sedation and In- traoperative Anesthesia ...control for operating room hypnosis and intefisive care unit sedation. 1.3. Goals of this Report The main goal of this report is to summarize the

Feedback Controller Design for the Synchronization of Boolean Control Networks.

PubMed

Liu, Yang; Sun, Liangjie; Lu, Jianquan; Liang, Jinling

2016-09-01

This brief investigates the partial and complete synchronization of two Boolean control networks (BCNs). Necessary and sufficient conditions for partial and complete synchronization are established by the algebraic representations of logical dynamics. An algorithm is obtained to construct the feedback controller that guarantees the synchronization of master and slave BCNs. Two biological examples are provided to illustrate the effectiveness of the obtained results.

System data communication structures for active-control transport aircraft, volume 1

NASA Technical Reports Server (NTRS)

Hopkins, A. L.; Martin, J. H.; Brock, L. D.; Jansson, D. G.; Serben, S.; Smith, T. B.; Hanley, L. D.

1981-01-01

Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems.

Dynamics and control of diseases in networks with community structure.

PubMed

Salathé, Marcel; Jones, James H

2010-04-08

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.

An investigation of networking techniques for the ASRM facility

NASA Technical Reports Server (NTRS)

Moorhead, Robert J., II; Smith, Wayne D.; Thompson, Dale R.

1992-01-01

This report is based on the early design concepts for a communications network for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, MS. The investigators have participated in the early design concepts and in the evaluation of the initial concepts. The continuing system design effort and any modification of the plan will require a careful evaluation of the required bandwidth of the network, the capabilities of the protocol, and the requirements of the controllers and computers on the network. The overall network, which is heterogeneous in protocol and bandwidth, is being modeled, analyzed, simulated, and tested to obtain some degree of confidence in its performance capabilities and in its performance under nominal and heavy loads. The results of the proposed work should have an impact on the design and operation of the ASRM facility.

Reconfigurable origami-inspired acoustic waveguides

PubMed Central

Babaee, Sahab; Overvelde, Johannes T. B.; Chen, Elizabeth R.; Tournat, Vincent; Bertoldi, Katia

2016-01-01

We combine numerical simulations and experiments to design a new class of reconfigurable waveguides based on three-dimensional origami-inspired metamaterials. Our strategy builds on the fact that the rigid plates and hinges forming these structures define networks of tubes that can be easily reconfigured. As such, they provide an ideal platform to actively control and redirect the propagation of sound. We design reconfigurable systems that, depending on the externally applied deformation, can act as networks of waveguides oriented along one, two, or three preferential directions. Moreover, we demonstrate that the capability of the structure to guide and radiate acoustic energy along predefined directions can be easily switched on and off, as the networks of tubes are reversibly formed and disrupted. The proposed designs expand the ability of existing acoustic metamaterials and exploit complex waveguiding to enhance control over propagation and radiation of acoustic energy, opening avenues for the design of a new class of tunable acoustic functional systems. PMID:28138527

GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

PubMed

Lin, C T; Jou, C P

2000-01-01

This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

Control of collective network chaos.

PubMed

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

2014-06-01

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

Implementation of Sensor and Control Designs for Bioregenerative Systems

NASA Technical Reports Server (NTRS)

Rodriguez, Pedro R. (Editor)

1990-01-01

The goal of the Spring 1990 EGM 4001 Design class was to design, fabricate, and test sensors and control systems for a closed loop life support system (CLLSS). The designs investigated were to contribute to the development of NASA's Controlled Ecological Life Support System (CELSS) at Kennedy Space Center (KSC). Designs included a seed moisture content sensor, a porous medium wetness sensor, a plant health sensor, and a neural network control system. The seed group focused on the design and implementation of a sensor that could detect the moisture content of a seed batch. The porous medium wetness group concentrated on the development of a sensor to monitor the amount of nutrient solution within a porous plate incorporating either infrared reflectance or thermal conductance properties. The plant health group examined the possibility of remotely monitoring the health of the plants within the Biomass Production Chamber (BPC) using infrared reflectance properties. Finally, the neural network group concentrated on the ability to use parallel processing in order to control a robot arm and analyze the data from the health sensor to detect regions of a plant.

Neural Networks for Flight Control

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1996-01-01

Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.

Advanced Networks in Motion Mobile Sensorweb

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Stewart, David H.

2011-01-01

Advanced mobile networking technology applicable to mobile sensor platforms was developed, deployed and demonstrated. A two-tier sensorweb design was developed. The first tier utilized mobile network technology to provide mobility. The second tier, which sits above the first tier, utilizes 6LowPAN (Internet Protocol version 6 Low Power Wireless Personal Area Networks) sensors. The entire network was IPv6 enabled. Successful mobile sensorweb system field tests took place in late August and early September of 2009. The entire network utilized IPv6 and was monitored and controlled using a remote Web browser via IPv6 technology. This paper describes the mobile networking and 6LowPAN sensorweb design, implementation, deployment and testing as well as wireless systems and network monitoring software developed to support testing and validation.

Quality-control design for surface-water sampling in the National Water-Quality Network

USGS Publications Warehouse

Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

2018-04-10

The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

PubMed

Dai, Shi-Lu; Wang, Cong; Wang, Min

2014-01-01

This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

Interaction Control to Synchronize Non-synchronizable Networks

PubMed Central

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-01-01

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks’ exact interaction topology and consequently have implications for biological and self-organizing technical systems. PMID:27853266

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

Why we need more than just randomized controlled trials to establish the effectiveness of online social networks for health behavior change.

PubMed

Vandelanotte, Corneel; Maher, Carol A

2015-01-01

Despite their popularity and potential to promote health in large populations, the effectiveness of online social networks (e.g., Facebook) to improve health behaviors has been somewhat disappointing. Most of the research examining the effectiveness of such interventions has used randomized controlled trials (RCTs). It is asserted that the modest outcomes may be due to characteristics specific to both online social networks and RCTs. The highly controlled nature of RCTs stifles the dynamic nature of online social networks. Alternative and ecologically valid research designs that evaluate online social networks in real-life conditions are needed to advance the science in this area.

An Investigation of Synchrony in Transport Networks

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Alexandrov, Natalia M.; Holroyd, Michael J.

2007-01-01

The cumulative degree distributions of transport networks, such as air transportation networks and respiratory neuronal networks, follow power laws. The significance of power laws with respect to other network performance measures, such as throughput and synchronization, remains an open question. Evolving methods for the analysis and design of air transportation networks must address network performance in the face of increasing demands and the need to contain and control local network disturbances, such as congestion. Toward this end, we investigate functional relationships that govern the performance of transport networks; for example, the links between the first nontrivial eigenvalue of a network's Laplacian matrix - a quantitative measure of network synchronizability - and other global network parameters. In particular, among networks with a fixed degree distribution and fixed network assortativity (a measure of a network's preference to attach nodes based on a similarity or difference), those with the small eigenvalue are shown to be poor synchronizers, to have much longer shortest paths and to have greater clustering in comparison to those with large. A simulation of a respiratory network adds data to our investigation. This study is a beginning step in developing metrics and design variables for the analysis and active design of air transport networks.

Integrating Artificial Immune, Neural and Endrocine Systems in Autonomous Sailing Robots

DTIC Science & Technology

2010-09-24

system - Development of an adaptive hormone system capable of changing operation and control of the neural network depending on changing enviromental ...and control of the neural network depending on changing enviromental conditions • First basic design of the MOOP and a simple neural-endocrine based

Caffeine Modulates Attention Network Function

ERIC Educational Resources Information Center

Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

2010-01-01

The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

Implementing Nonlinear Feedback Controllers Using DNA Strand Displacement Reactions.

PubMed

Sawlekar, Rucha; Montefusco, Francesco; Kulkarni, Vishwesh V; Bates, Declan G

2016-07-01

We show how an important class of nonlinear feedback controllers can be designed using idealized abstract chemical reactions and implemented via DNA strand displacement (DSD) reactions. Exploiting chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks, we show how a set of unimolecular and bimolecular reactions can be used to realize input-output dynamics that produce a nonlinear quasi sliding mode (QSM) feedback controller. The kinetics of the required chemical reactions can then be implemented as enzyme-free, enthalpy/entropy driven DNA reactions using a toehold mediated strand displacement mechanism via Watson-Crick base pairing and branch migration. We demonstrate that the closed loop response of the nonlinear QSM controller outperforms a traditional linear controller by facilitating much faster tracking response dynamics without introducing overshoots in the transient response. The resulting controller is highly modular and is less affected by retroactivity effects than standard linear designs.

Theoretical study of network design methodologies for the aerial relay system. [energy consumption and air traffic control

NASA Technical Reports Server (NTRS)

Rivera, J. M.; Simpson, R. W.

1980-01-01

The aerial relay system network design problem is discussed. A generalized branch and bound based algorithm is developed which can consider a variety of optimization criteria, such as minimum passenger travel time and minimum liner and feeder operating costs. The algorithm, although efficient, is basically useful for small size networks, due to its nature of exponentially increasing computation time with the number of variables.

Spreading activation in nonverbal memory networks.

PubMed

Foster, Paul S; Wakefield, Candias; Pryjmak, Scott; Roosa, Katelyn M; Branch, Kaylei K; Drago, Valeria; Harrison, David W; Ruff, Ronald

2017-09-01

Theories of spreading activation primarily involve semantic memory networks. However, the existence of separate verbal and visuospatial memory networks suggests that spreading activation may also occur in visuospatial memory networks. The purpose of the present investigation was to explore this possibility. Specifically, this study sought to create and describe the design frequency corpus and to determine whether this measure of visuospatial spreading activation was related to right hemisphere functioning and spreading activation in verbal memory networks. We used word frequencies taken from the Controlled Oral Word Association Test and design frequencies taken from the Ruff Figural Fluency Test as measures of verbal and visuospatial spreading activation, respectively. Average word and design frequencies were then correlated with measures of left and right cerebral functioning. The results indicated that a significant relationship exists between performance on a test of right posterior functioning (Block Design) and design frequency. A significant negative relationship also exists between spreading activation in semantic memory networks and design frequency. Based on our findings, the hypotheses were supported. Further research will need to be conducted to examine whether spreading activation exists in visuospatial memory networks as well as the parameters that might modulate this spreading activation, such as the influence of neurotransmitters.

High speed fiber optics local area networks: Design and implementation

NASA Technical Reports Server (NTRS)

Tobagi, Fouad A.

1988-01-01

The design of high speed local area networks (HSLAN) for communication among distributed devices requires solving problems in three areas: (1) the network medium and its topology; (2) the medium access control; and (3) the network interface. Considerable progress has been made in all areas. Accomplishments are divided into two groups according to their theoretical or experimental nature. A brief summary is given in Section 2, including references to papers which appeared in the literature, as well as to Ph.D. dissertations and technical reports published at Stanford University.

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

NASA Astrophysics Data System (ADS)

Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

2012-06-01

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

YADCLAN: yet another digitally-controlled linear artificial neuron.

PubMed

Frenger, Paul

2003-01-01

This paper updates the author's 1999 RMBS presentation on digitally controlled linear artificial neuron design. Each neuron is based on a standard operational amplifier having excitatory and inhibitory inputs, variable gain, an amplified linear analog output and an adjustable threshold comparator for digital output. This design employs a 1-wire serial network of digitally controlled potentiometers and resistors whose resistance values are set and read back under microprocessor supervision. This system embodies several unique and useful features, including: enhanced neuronal stability, dynamic reconfigurability and network extensibility. This artificial neuronal is being employed for feature extraction and pattern recognition in an advanced robotic application.

Outer synchronization of complex networks with internal delay and coupling delay via aperiodically intermittent pinning control

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Wang, Chunpeng; Xia, Zhiqiu

This paper concerns the outer synchronization problem between two complex delayed networks via the method of aperiodically intermittent pinning control. Apart from previous works, internal delay and coupling delay are both involved in this model, and the designed intermittent controllers can be aperiodic. The main work in this paper can be summarized as follows: First, two cases of aperiodically intermittent control with constant gain and adaptive gain are implemented, respectively. The intermittent control and pinning control are combined to reduce consumptions further. Then, based on the Lyapunov stability theory, synchronization protocols are given by strict derivation. Especially, the designed controllers are indeed simple and valid in application of theory to practice. Finally, numerical examples put the proposed control methods to the test.

Asynchronous sampled-data approach for event-triggered systems

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Memon, Azhar M.

2017-11-01

While aperiodically triggered network control systems save a considerable amount of communication bandwidth, they also pose challenges such as coupling between control and event-condition design, optimisation of the available resources such as control, communication and computation power, and time-delays due to computation and communication network. With this motivation, the paper presents separate designs of control and event-triggering mechanism, thus simplifying the overall analysis, asynchronous linear quadratic Gaussian controller which tackles delays and aperiodic nature of transmissions, and a novel event mechanism which compares the cost of the aperiodic system against a reference periodic implementation. The proposed scheme is simulated on a linearised wind turbine model for pitch angle control and the results show significant improvement against the periodic counterpart.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

GPSS and Modeling of Computer Communication Networks.

DTIC Science & Technology

1982-04-01

chains are used to alter the normal "flows" of transactions in a user defined manner. Transaction "flow" may be controlled on the basis of group ...authors refer to loops and rings interchangeably, including those who have designed loop networks with distributed control mechanisms [8,9,10,11,121...that detailed simulation of character by character transmission does not take place; rather, [ control message--data message-- control message! groupings

The Effect of Souvenaid on Functional Brain Network Organisation in Patients with Mild Alzheimer’s Disease: A Randomised Controlled Study

PubMed Central

de Waal, Hanneke; Stam, Cornelis J.; Lansbergen, Marieke M.; Wieggers, Rico L.; Kamphuis, Patrick J. G. H.; Scheltens, Philip; Maestú, Fernando; van Straaten, Elisabeth C. W.

2014-01-01

Background Synaptic loss is a major hallmark of Alzheimer’s disease (AD). Disturbed organisation of large-scale functional brain networks in AD might reflect synaptic loss and disrupted neuronal communication. The medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect, is designed to enhance synapse formation and function and has been shown to improve memory performance in patients with mild AD in two randomised controlled trials. Objective To explore the effect of Souvenaid compared to control product on brain activity-based networks, as a derivative of underlying synaptic function, in patients with mild AD. Design A 24-week randomised, controlled, double-blind, parallel-group, multi-country study. Participants 179 drug-naïve mild AD patients who participated in the Souvenir II study. Intervention Patients were randomised 1∶1 to receive Souvenaid or an iso-caloric control product once daily for 24 weeks. Outcome In a secondary analysis of the Souvenir II study, electroencephalography (EEG) brain networks were constructed and graph theory was used to quantify complex brain structure. Local brain network connectivity (normalised clustering coefficient gamma) and global network integration (normalised characteristic path length lambda) were compared between study groups, and related to memory performance. Results The network measures in the beta band were significantly different between groups: they decreased in the control group, but remained relatively unchanged in the active group. No consistent relationship was found between these network measures and memory performance. Conclusions The current results suggest that Souvenaid preserves the organisation of brain networks in patients with mild AD within 24 weeks, hypothetically counteracting the progressive network disruption over time in AD. The results strengthen the hypothesis that Souvenaid affects synaptic integrity and function. Secondly, we conclude that advanced EEG analysis, using the mathematical framework of graph theory, is useful and feasible for assessing the effects of interventions. Trial registration Dutch Trial Register NTR1975. PMID:24475144

Synchronization Control of Neural Networks With State-Dependent Coefficient Matrices.

PubMed

Zhang, Junfeng; Zhao, Xudong; Huang, Jun

2016-11-01

This brief is concerned with synchronization control of a class of neural networks with state-dependent coefficient matrices. Being different from the existing drive-response neural networks in the literature, a novel model of drive-response neural networks is established. The concepts of uniformly ultimately bounded (UUB) synchronization and convex hull Lyapunov function are introduced. Then, by using the convex hull Lyapunov function approach, the UUB synchronization design of the drive-response neural networks is proposed, and a delay-independent control law guaranteeing the bounded synchronization of the neural networks is constructed. All present conditions are formulated in terms of bilinear matrix inequalities. By comparison, it is shown that the neural networks obtained in this brief are less conservative than those ones in the literature, and the bounded synchronization is suitable for the novel drive-response neural networks. Finally, an illustrative example is given to verify the validity of the obtained results.

Design of a network for concurrent message passing systems

NASA Astrophysics Data System (ADS)

Song, Paul Y.

1988-08-01

We describe the design of the network design frame (NDF), a self-timed routing chip for a message-passing concurrent computer. The NDF uses a partitioned data path, low-voltage output drivers, and a distributed token-passing arbiter to provide a bandwidth of 450 Mbits/sec into the network. Wormhole routing and bidirectional virtual channels are used to provide low latency communications, less than 2us latency to deliver a 216 bit message across the diameter of a 1K node mess-connected machine. To support concurrent software systems, the NDF provides two logical networks, one for user messages and one for system messages. The two networks share the same set of physical wires. To facilitate the development of network nodes, the NDF is a design frame. The NDF circuitry is integrated into the pad frame of a chip leaving the center of the chip uncommitted. We define an analytic framework in which to study the effects of network size, network buffering capacity, bidirectional channels, and traffic on this class of networks. The response of the network to various combinations of these parameters are obtained through extensive simulation of the network model. Through simulation, we are able to observe the macro behavior of the network as opposed to the micro behavior of the NDF routing controller.

Centralized and distributed control architectures under Foundation Fieldbus network.

PubMed

Persechini, Maria Auxiliadora Muanis; Jota, Fábio Gonçalves

2013-01-01

This paper aims at discussing possible automation and control system architectures based on fieldbus networks in which the controllers can be implemented either in a centralized or in a distributed form. An experimental setup is used to demonstrate some of the addressed issues. The control and automation architecture is composed of a supervisory system, a programmable logic controller and various other devices connected to a Foundation Fieldbus H1 network. The procedures used in the network configuration, in the process modelling and in the design and implementation of controllers are described. The specificities of each one of the considered logical organizations are also discussed. Finally, experimental results are analysed using an algorithm for the assessment of control loops to compare the performances between the centralized and the distributed implementations. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Design of a patient-centered, multi-institutional healthcare information network using peer-to-peer communication in a highly distributed architecture.

PubMed

Geissbuhler, Antoine; Spahni, Stéphane; Assimacopoulos, André; Raetzo, Marc-André; Gobet, Gérard

2004-01-01

to design a community healthcare information network for all 450,000 citizen in the State of Geneva, Switzerland, connecting public and private healthcare professionals. Requirements include the decentralized storage of information at the source of its production, the creation of a virtual patient record at the time of the consultation, the control by the patient of the access rights to the information, and the interoperability with other similar networks at the national and european level. a participative approach and real-world pilot projects are used to design, test and validate key components of the network, including its technical architecture and the strategy for the management of access rights by the patients. a distributed architecture using peer-to-peer communication of information mediators can implement the various requirements while limiting to an absolute minimum the amount of centralized information. Access control can be managed by the patient with the help of a medical information mediator, the physician of trust.

Dual-mode ultraflow access networks: a hybrid solution for the access bottleneck

NASA Astrophysics Data System (ADS)

Kazovsky, Leonid G.; Shen, Thomas Shunrong; Dhaini, Ahmad R.; Yin, Shuang; De Leenheer, Marc; Detwiler, Benjamin A.

2013-12-01

Optical Flow Switching (OFS) is a promising solution for large Internet data transfers. In this paper, we introduce UltraFlow Access, a novel optical access network architecture that offers dual-mode service to its end-users: IP and OFS. With UltraFlow Access, we design and implement a new dual-mode control plane and a new dual-mode network stack to ensure efficient connection setup and reliable and optimal data transmission. We study the impact of the UltraFlow system's design on the network throughput. Our experimental results show that with an optimized system design, near optimal (around 10 Gb/s) OFS data throughput can be attained when the line rate is 10Gb/s.

Smart-Home Architecture Based on Bluetooth mesh Technology

NASA Astrophysics Data System (ADS)

Wan, Qing; Liu, Jianghua

2018-03-01

This paper describes the smart home network system based on Nordic nrf52832 device. Nrf52832 is new generation RF SOC device focus on sensor monitor and low power Bluetooth connection applications. In this smart home system, we set up a self-organizing network system which consists of one control node and a lot of monitor nodes. The control node manages the whole network works; the monitor nodes collect the sensor information such as light intensity, temperature, humidity, PM2.5, etc. Then update to the control node by Bluetooth mesh network. The design results show that the Bluetooth mesh wireless network system is flexible and construction cost is low, which is suitable for the communication characteristics of a smart home network. We believe it will be wildly used in the future.

SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.

PubMed

Chae, Seunghwan; Nguang, Sing Kiong

2014-07-01

In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Construct mine environment monitoring system based on wireless mesh network

NASA Astrophysics Data System (ADS)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

Design of Control Plane Architecture Based on Cloud Platform and Experimental Network Demonstration for Multi-domain SDON

NASA Astrophysics Data System (ADS)

Li, Ming; Yin, Hongxi; Xing, Fangyuan; Wang, Jingchao; Wang, Honghuan

2016-02-01

With the features of network virtualization and resource programming, Software Defined Optical Network (SDON) is considered as the future development trend of optical network, provisioning a more flexible, efficient and open network function, supporting intraconnection and interconnection of data centers. Meanwhile cloud platform can provide powerful computing, storage and management capabilities. In this paper, with the coordination of SDON and cloud platform, a multi-domain SDON architecture based on cloud control plane has been proposed, which is composed of data centers with database (DB), path computation element (PCE), SDON controller and orchestrator. In addition, the structure of the multidomain SDON orchestrator and OpenFlow-enabled optical node are proposed to realize the combination of centralized and distributed effective management and control platform. Finally, the functional verification and demonstration are performed through our optical experiment network.

Resonance Energy Transfer-Based Molecular Switch Designed Using a Systematic Design Process Based on Monte Carlo Methods and Markov Chains

NASA Astrophysics Data System (ADS)

Rallapalli, Arjun

A RET network consists of a network of photo-active molecules called chromophores that can participate in inter-molecular energy transfer called resonance energy transfer (RET). RET networks are used in a variety of applications including cryptographic devices, storage systems, light harvesting complexes, biological sensors, and molecular rulers. In this dissertation, we focus on creating a RET device called closed-diffusive exciton valve (C-DEV) in which the input to output transfer function is controlled by an external energy source, similar to a semiconductor transistor like the MOSFET. Due to their biocompatibility, molecular devices like the C-DEVs can be used to introduce computing power in biological, organic, and aqueous environments such as living cells. Furthermore, the underlying physics in RET devices are stochastic in nature, making them suitable for stochastic computing in which true random distribution generation is critical. In order to determine a valid configuration of chromophores for the C-DEV, we developed a systematic process based on user-guided design space pruning techniques and built-in simulation tools. We show that our C-DEV is 15x better than C-DEVs designed using ad hoc methods that rely on limited data from prior experiments. We also show ways in which the C-DEV can be improved further and how different varieties of C-DEVs can be combined to form more complex logic circuits. Moreover, the systematic design process can be used to search for valid chromophore network configurations for a variety of RET applications. We also describe a feasibility study for a technique used to control the orientation of chromophores attached to DNA. Being able to control the orientation can expand the design space for RET networks because it provides another parameter to tune their collective behavior. While results showed limited control over orientation, the analysis required the development of a mathematical model that can be used to determine the distribution of dipoles in a given sample of chromophore constructs. The model can be used to evaluate the feasibility of other potential orientation control techniques.

Wallops Ship Surveillance System

NASA Technical Reports Server (NTRS)

Smith, Donna C.

2011-01-01

Approved as a Wallops control center backup system, the Wallops Ship Surveillance Software is a day-of-launch risk analysis tool for spaceport activities. The system calculates impact probabilities and displays ship locations relative to boundary lines. It enables rapid analysis of possible flight paths to preclude the need to cancel launches and allow execution of launches in a timely manner. Its design is based on low-cost, large-customer- base elements including personal computers, the Windows operating system, C/C++ object-oriented software, and network interfaces. In conformance with the NASA software safety standard, the system is designed to ensure that it does not falsely report a safe-for-launch condition. To improve the current ship surveillance method, the system is designed to prevent delay of launch under a safe-for-launch condition. A single workstation is designated the controller of the official ship information and the official risk analysis. Copies of this information are shared with other networked workstations. The program design is divided into five subsystems areas: 1. Communication Link -- threads that control the networking of workstations; 2. Contact List -- a thread that controls a list of protected item (ocean vessel) information; 3. Hazard List -- threads that control a list of hazardous item (debris) information and associated risk calculation information; 4. Display -- threads that control operator inputs and screen display outputs; and 5. Archive -- a thread that controls archive file read and write access. Currently, most of the hazard list thread and parts of other threads are being reused as part of a new ship surveillance system, under the SureTrak project.

Group Centric Networking: Large Scale Over the Air Testing of Group Centric Networking

DTIC Science & Technology

2016-11-01

protocol designed to support groups of devices in a local region [4]. It attempts to use the wireless medium to broadcast minimal control information...1) Group Discovery: The goal of the group discovery algo- rithm is to find group nodes without globally flooding control messages. To facilitate this...Large Scale Over-the-Air Testing of Group Centric Networking Logan Mercer, Greg Kuperman, Andrew Hunter, Brian Proulx MIT Lincoln Laboratory

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Nark, Douglas M.; Jones, Michael G.

2011-01-01

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

Fixed-time synchronization of complex networks with nonidentical nodes and stochastic noise perturbations

NASA Astrophysics Data System (ADS)

Zhang, Wanli; Li, Chuandong; Huang, Tingwen; Huang, Junjian

2018-02-01

This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results.

Fabrication and Operation of Microfluidic Hanging-Drop Networks.

PubMed

Misun, Patrick M; Birchler, Axel K; Lang, Moritz; Hierlemann, Andreas; Frey, Olivier

2018-01-01

The hanging-drop network (HDN) is a technology platform based on a completely open microfluidic network at the bottom of an inverted, surface-patterned substrate. The platform is predominantly used for the formation, culturing, and interaction of self-assembled spherical microtissues (spheroids) under precisely controlled flow conditions. Here, we describe design, fabrication, and operation of microfluidic hanging-drop networks.

Sub-Network Access Control Technology Demonstrator: Software Design of the Network Management System

DTIC Science & Technology

2002-08-01

Canadian Operational Fleet. Requirements The proposed network management solution must provide the normal monitoring and configuration mechanisms generally...Joint Warrior Inter- operability Demonstrations (JWID) m and the Communication System Network Inter- Operability (CSNI) Navy Network Trials. In short...management functional area normally includes two main functions: fault isolation and diagnosis, and restoration of the system . In short, an operator

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks

PubMed Central

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P.; Gerstein, Mark

2010-01-01

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers’ continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems. PMID:20439753

Inferring topologies via driving-based generalized synchronization of two-layer networks

NASA Astrophysics Data System (ADS)

Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua

2016-05-01

The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.

Performance Evaluation of Reliable Multicast Protocol for Checkout and Launch Control Systems

NASA Technical Reports Server (NTRS)

Shu, Wei Wennie; Porter, John

2000-01-01

The overall objective of this project is to study reliability and performance of Real Time Critical Network (RTCN) for checkout and launch control systems (CLCS). The major tasks include reliability and performance evaluation of Reliable Multicast (RM) package and fault tolerance analysis and design of dual redundant network architecture.

Center for Neural Engineering at Tennessee State University, ASSERT Annual Progress Report.

DTIC Science & Technology

1995-07-01

neural networks . Their research topics are: (1) developing frequency dependent oscillatory neural networks ; (2) long term pontentiation learning rules...as applied to spatial navigation; (3) design and build a servo joint robotic arm and (4) neural network based prothesis control. One graduate student

Cooperative remote sensing and actuation using networked unmanned vehicles

NASA Astrophysics Data System (ADS)

Chao, Haiyang

This dissertation focuses on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes in the current information-rich world. The target scenarios are environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks, etc. AggieAir, a small and low-cost unmanned aircraft system, is designed based on the remote sensing requirements from environmental monitoring missions. The state estimation problem and the advanced lateral flight controller design problem are further attacked focusing on the small unmanned aerial vehicle (UAV) platform. Then the UAV-based remote sensing problem is focused with further flight test results. Given the measurements from unmanned vehicles, the actuation algorithms are needed for missions like the diffusion control. A consensus-based central Voronoi tessellation (CVT) algorithm is proposed for better control of the diffusion process. Finally, the dissertation conclusion and some new research suggestions are presented.

Resilient Wireless Sensor Networks Using Topology Control: A Review

PubMed Central

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

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-19

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-01

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

Performance analysis of Integrated Communication and Control System networks

NASA Technical Reports Server (NTRS)

Halevi, Y.; Ray, A.

1990-01-01

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

Modelling and analysis of gene regulatory network using feedback control theory

NASA Astrophysics Data System (ADS)

El-Samad, H.; Khammash, M.

2010-01-01

Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

Considerations in the design of a communication network for an autonomously managed power system

NASA Technical Reports Server (NTRS)

Mckee, J. W.; Whitehead, Norma; Lollar, Louis

1989-01-01

The considerations involved in designing a communication network for an autonomously managed power system intended for use in space vehicles are examined. An overview of the design and implementation of a communication network implemented in a breadboard power system is presented. An assumption that the monitoring and control devices are distributed but physically close leads to the selection of a multidrop cable communication system. The assumption of a high-quality communication cable in which few messages are lost resulted in a simple recovery procedure consisting of a time out and retransmit process.

A Control Simulation Method of High-Speed Trains on Railway Network with Irregular Influence

NASA Astrophysics Data System (ADS)

Yang, Li-Xing; Li, Xiang; Li, Ke-Ping

2011-09-01

Based on the discrete time method, an effective movement control model is designed for a group of highspeed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains' movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and rescheduling trains on the rail network.

Adaptation of a software development methodology to the implementation of a large-scale data acquisition and control system. [for Deep Space Network

NASA Technical Reports Server (NTRS)

Madrid, G. A.; Westmoreland, P. T.

1983-01-01

A progress report is presented on a program to upgrade the existing NASA Deep Space Network in terms of a redesigned computer-controlled data acquisition system for channelling tracking, telemetry, and command data between a California-based control center and three signal processing centers in Australia, California, and Spain. The methodology for the improvements is oriented towards single subsystem development with consideration for a multi-system and multi-subsystem network of operational software. Details of the existing hardware configurations and data transmission links are provided. The program methodology includes data flow design, interface design and coordination, incremental capability availability, increased inter-subsystem developmental synthesis and testing, system and network level synthesis and testing, and system verification and validation. The software has been implemented thus far to a 65 percent completion level, and the methodology being used to effect the changes, which will permit enhanced tracking and communication with spacecraft, has been concluded to feature effective techniques.

A Linear Programming Approach to Routing Control in Networks of Constrained Nonlinear Positive Systems with Concave Flow Rates

NASA Technical Reports Server (NTRS)

Arneson, Heather M.; Dousse, Nicholas; Langbort, Cedric

2014-01-01

We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment.We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its intended destination over a finite time horizon. We give sufficient conditions for the existence of a time-varying state-dependent routing strategy which ensures that the closed-loop system satisfies basic network properties of positivity, conservation and interconnection while ensuring that capacity constraints are satisfied, when possible, or adjusted if a solution cannot be found. These conditions are formulated as a linear programming problem. Instances of this linear programming problem can be solved iteratively to generate a solution to the finite horizon routing problem. Results are given for the application of this control design method to an example problem. Key words: linear programming; control of networks; positive systems; controller constraints and structure.

Cloud-based robot remote control system for smart factory

NASA Astrophysics Data System (ADS)

Wu, Zhiming; Li, Lianzhong; Xu, Yang; Zhai, Jingmei

2015-12-01

With the development of internet technologies and the wide application of robots, there is a prospect (trend/tendency) of integration between network and robots. A cloud-based robot remote control system over networks for smart factory is proposed, which enables remote users to control robots and then realize intelligent production. To achieve it, a three-layer system architecture is designed including user layer, service layer and physical layer. Remote control applications running on the cloud server is developed on Microsoft Azure. Moreover, DIV+ CSS technologies are used to design human-machine interface to lower maintenance cost and improve development efficiency. Finally, an experiment is implemented to verify the feasibility of the program.

Robust synthetic biology design: stochastic game theory approach.

PubMed

Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching

2009-07-15

Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.

Integrated communication and control systems. II - Design considerations

NASA Technical Reports Server (NTRS)

Ray, Asok; Halevi, Yoram

1988-01-01

The ICCS design issues for nonperiodic and stochastic delays are addressed and the framework for alternative design procedures is outlined. The impact of network-induced delays on system stability is investigated and their physical significance is demonstrated using a simulation. The negative effects of vacant sampling and message rejection at the controller are demonstrated.

Neural network for control of rearrangeable Clos networks.

PubMed

Park, Y K; Cherkassky, V

1994-09-01

Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant, regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reducing the network convergence time. The implementation aspects are also discussed to show the feasibility of the proposed approach.

3 x 3 free-space optical router based on crossbar network and its control algorithm

NASA Astrophysics Data System (ADS)

Hou, Peipei; Sun, Jianfeng; Yu, Zhou; Lu, Wei; Wang, Lijuan; Liu, Liren

2015-08-01

A 3 × 3 free-space optical router, which comprises optical switches and polarizing beam splitter (PBS) and based on crossbar network, is proposed in this paper. A control algorithm for the 3 × 3 free-space optical router is also developed to achieve rapid control without rearrangement. In order to test the performance of the network based on 3 × 3 free-space optical router and that of the algorithm developed for the optical router, experiments are designed. The experiment results show that the interconnection network based on the 3 × 3 free-space optical router has low cross talk, fast connection speed. Under the control of the algorithm developed, a non-block and real free interconnection network is obtained based on the 3 × 3 free-space optical router we proposed.

Quality of service policy control in virtual private networks

NASA Astrophysics Data System (ADS)

Yu, Yiqing; Wang, Hongbin; Zhou, Zhi; Zhou, Dongru

2004-04-01

This paper studies the QoS of VPN in an environment where the public network prices connection-oriented services based on source, destination and grade of service, and advertises these prices to its VPN customers (users). As different QoS technologies can produce different QoS, there are according different traffic classification rules and priority rules. The internet service provider (ISP) may need to build complex mechanisms separately for each node. In order to reduce the burden of network configuration, we need to design policy control technologies. We considers mainly directory server, policy server, policy manager and policy enforcers. Policy decision point (PDP) decide its control according to policy rules. In network, policy enforce point (PEP) decide its network controlled unit. For InterServ and DiffServ, we will adopt different policy control methods as following: (1) In InterServ, traffic uses resource reservation protocol (RSVP) to guarantee the network resource. (2) In DiffServ, policy server controls the DiffServ code points and per hop behavior (PHB), its PDP distributes information to each network node. Policy server will function as following: information searching; decision mechanism; decision delivering; auto-configuration. In order to prove the effectiveness of QoS policy control, we make the corrective simulation.

Traffic Management in ATM Networks Over Satellite Links

NASA Technical Reports Server (NTRS)

Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas

1999-01-01

This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

International Neural Network Society Annual Meeting (1994) Held in San Diego, California on 5-9 June 1994. Volume 1

DTIC Science & Technology

1994-06-09

Ethics and the Soul 1-221 P. Werbos A Net Program for Natural Language Comprehension 1-863 J. Weiss Applications Oral ANN Design of Image Processing...Controlling Nonlinear Dynamic Systems Using Neuro-Fuzzy Networks 1-787 E. Teixera, G. Laforga, H. Azevedo Neural Fuzzy Logics as a Tool for Design Ecological ...Discrete Neural Network 11-466 Z. Cheng-fu Representation of Number A Theory of Mathematical Modeling 11-479 J. Cristofano An Ecological Approach to

On-board processing architectures for satellite B-ISDN services

NASA Technical Reports Server (NTRS)

Inukai, Thomas; Shyy, Dong-Jye; Faris, Faris

1991-01-01

Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

Network interface unit design options performance analysis

NASA Technical Reports Server (NTRS)

Miller, Frank W.

1991-01-01

An analysis is presented of three design options for the Space Station Freedom (SSF) onboard Data Management System (DMS) Network Interface Unit (NIU). The NIU provides the interface from the Fiber Distributed Data Interface (FDDI) local area network (LAN) to the DMS processing elements. The FDDI LAN provides the primary means for command and control and low and medium rate telemetry data transfers on board the SSF. The results of this analysis provide the basis for the implementation of the NIU.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

PubMed

Luo, Shaohua; Wu, Songli; Gao, Ruizhen

2015-07-01

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Shaohua; Department of Mechanical Engineering, Chongqing Aerospace Polytechnic, Chongqing, 400021; Wu, Songli

2015-07-15

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in themore » closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.« less

A demand assignment control in international business satellite communications network

NASA Astrophysics Data System (ADS)

Nohara, Mitsuo; Takeuchi, Yoshio; Takahata, Fumio; Hirata, Yasuo

An experimental system is being developed for use in an international business satellite (IBS) communications network based on demand-assignment (DA) and TDMA techniques. This paper discusses its system design, in particular from the viewpoints of a network configuration, a DA control, and a satellite channel-assignment algorithm. A satellite channel configuration is also presented along with a tradeoff study on transmission rate, HPA output power, satellite resource efficiency, service quality, and so on.

Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Nomura, Hiroyoshi; Wakami, Noboru

1991-01-01

Whereas conventional fuzzy reasonings are associated with tuning problems, which are lack of membership functions and inference rule designs, a neural network driven fuzzy reasoning (NDF) capable of determining membership functions by neural network is formulated. In the antecedent parts of the neural network driven fuzzy reasoning, the optimum membership function is determined by a neural network, while in the consequent parts, an amount of control for each rule is determined by other plural neural networks. By introducing an algorithm of neural network driven fuzzy reasoning, inference rules for making a pendulum stand up from its lowest suspended point are determined for verifying the usefulness of the algorithm.

MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage

DTIC Science & Technology

2015-10-19

higher error rates in wireless networks result in a great deal of “false” congestion indications, resulting in underutilization of the network [4...approaches that are relevant to lossy wireless networks . Multipath TCP (MPTCP) schemes [9], [10] explore the design and implementation of multipath...attempts to “fix” TCP to work with lossy wireless networks using existing techniques. The authors have taken the view that because packet losses are

Speed synchronization control for integrated automotive motor-transmission powertrain system with random delays

NASA Astrophysics Data System (ADS)

Zhu, Xiaoyuan; Zhang, Hui; Fang, Zongde

2015-12-01

This paper presents a robust speed synchronization controller design for an integrated motor-transmission powertrain system in which the driving motor and multi-gearbox are directly coupled. As the controller area network (CAN) is commonly used in the vehicle powertrain system, the possible network-induced random delays in both feedback and forward channel are considered and modeled by using two Markov chains in the controller design process. For the application perspective, the control law adopted here is a generalized proportional-integral (PI) control. By employing the system-augmentation technique, a delay-free stochastic closed-loop system is obtained and the generalized PI controller design problem is converted to a static output feedback (SOF) controller design problem. Since there are external disturbances involved in the closed-loop system, the energy-to-peak performance is considered to guarantee the robustness of the controller. And the controlled output is chosen as the speed synchronization error. To further improve the transient response of the closed-loop system, the pole placement is also employed in the energy-to-peak performance based speed synchronization control. The mode-dependent control gains are obtained by using an iterative linear matrix inequality (LMI) algorithm. Simulation results show the effectiveness of the proposed control approach.

Neural control of magnetic suspension systems

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1993-01-01

The purpose of this research program is to design, build and test (in cooperation with NASA personnel from the NASA Langley Research Center) neural controllers for two different small air-gap magnetic suspension systems. The general objective of the program is to study neural network architectures for the purpose of control in an experimental setting and to demonstrate the feasibility of the concept. The specific objectives of the research program are: (1) to demonstrate through simulation and experimentation the feasibility of using neural controllers to stabilize a nonlinear magnetic suspension system; (2) to investigate through simulation and experimentation the performance of neural controllers designs under various types of parametric and nonparametric uncertainty; (3) to investigate through simulation and experimentation various types of neural architectures for real-time control with respect to performance and complexity; and (4) to benchmark in an experimental setting the performance of neural controllers against other types of existing linear and nonlinear compensator designs. To date, the first one-dimensional, small air-gap magnetic suspension system has been built, tested and delivered to the NASA Langley Research Center. The device is currently being stabilized with a digital linear phase-lead controller. The neural controller hardware is under construction. Two different neural network paradigms are under consideration, one based on hidden layer feedforward networks trained via back propagation and one based on using Gaussian radial basis functions trained by analytical methods related to stability conditions. Some advanced nonlinear control algorithms using feedback linearization and sliding mode control are in simulation studies.

Observer-Based Non-PDC Control for Networked T-S Fuzzy Systems With an Event-Triggered Communication.

PubMed

Peng, Chen; Ma, Shaodong; Xie, Xiangpeng

2017-02-07

This paper addresses the problem of an event-triggered non-parallel distribution compensation (PDC) control for networked Takagi-Sugeno (T-S) fuzzy systems, under consideration of the limited data transmission bandwidth and the imperfect premise matching membership functions. First, a unified event-triggered T-S fuzzy model is provided, in which: 1) a fuzzy observer with the imperfect premise matching is constructed to estimate the unmeasurable states of the studied system; 2) a fuzzy controller is designed following the same premise as the observer; and 3) an output-based event-triggering transmission scheme is designed to economize the restricted network resources. Different from the traditional PDC method, the synchronous premise between the fuzzy observer and the T-S fuzzy system are no longer needed in this paper. Second, by use of Lyapunov theory, a stability criterion and a stabilization condition are obtained for ensuring asymptotically stable of the studied system. On account of the imperfect premise matching conditions are well considered in the derivation of the above criteria, less conservation can be expected to enhance the design flexibility. Compared with some existing emulation-based methods, the controller gains are no longer required to be known a priori. Finally, the availability of proposed non-PDC design scheme is illustrated by the backing-up control of a truck-trailer system.

Region stability analysis and tracking control of memristive recurrent neural network.

PubMed

Bao, Gang; Zeng, Zhigang; Shen, Yanjun

2018-02-01

Memristor is firstly postulated by Leon Chua and realized by Hewlett-Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of [Formula: see text] sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Trajectory Control of Scale-Free Dynamical Networks with Exogenous Disturbances

NASA Astrophysics Data System (ADS)

Yang, Hong-Yong; Zhang, Shun; Zong, Guang-Deng

2011-01-01

In this paper, the trajectory control of multi-agent dynamical systems with exogenous disturbances is studied. Suppose multiple agents composing of a scale-free network topology, the performance of rejecting disturbances for the low degree node and high degree node is analyzed. Firstly, the consensus of multi-agent systems without disturbances is studied by designing a pinning control strategy on a part of agents, where this pinning control can bring multiple agents' states to an expected consensus track. Then, the influence of the disturbances is considered by developing disturbance observers, and disturbance observers based control (DOBC) are developed for disturbances generated by an exogenous system to estimate the disturbances. Asymptotical consensus of the multi-agent systems with disturbances under the composite controller can be achieved for scale-free network topology. Finally, by analyzing examples of multi-agent systems with scale-free network topology and exogenous disturbances, the verities of the results are proved. Under the DOBC with the designed parameters, the trajectory convergence of multi-agent systems is researched by pinning two class of the nodes. We have found that it has more stronger robustness to exogenous disturbances for the high degree node pinned than that of the low degree node pinned.

Development and Flight Testing of a Neural Network Based Flight Control System on the NF-15B Aircraft

NASA Technical Reports Server (NTRS)

Bomben, Craig R.; Smolka, James W.; Bosworth, John T.; Silliams-Hayes, Peggy S.; Burken, John J.; Larson, Richard R.; Buschbacher, Mark J.; Maliska, Heather A.

2006-01-01

The Intelligent Flight Control System (IFCS) project at the NASA Dryden Flight Research Center, Edwards AFB, CA, has been investigating the use of neural network based adaptive control on a unique NF-15B test aircraft. The IFCS neural network is a software processor that stores measured aircraft response information to dynamically alter flight control gains. In 2006, the neural network was engaged and allowed to learn in real time to dynamically alter the aircraft handling qualities characteristics in the presence of actual aerodynamic failure conditions injected into the aircraft through the flight control system. The use of neural network and similar adaptive technologies in the design of highly fault and damage tolerant flight control systems shows promise in making future aircraft far more survivable than current technology allows. This paper will present the results of the IFCS flight test program conducted at the NASA Dryden Flight Research Center in 2006, with emphasis on challenges encountered and lessons learned.

Topological Methods for Design and Control of Adaptive Stochastic Complex Systems - to Meet the Challenges of Resilient Urban Infrastructure

DTIC Science & Technology

2017-03-24

for Design and Control of Adaptive Stochastic Complex Systems John Baillieul∗ Contents 1 Executive Summary 2 2 Introduction and Issues to Be Addressed...difficult of real-world Systems-of-Systems challenges is the design and operational control of medical treatment networks that support forces operating...This report describes a brief research project on foundartional aspects of systems-of-systems design and operation. The overarching goal of the

Neural Networks for Rapid Design and Analysis

NASA Technical Reports Server (NTRS)

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

1998-01-01

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller.

PubMed

Gong, Shuqing; Yang, Shaofu; Guo, Zhenyuan; Huang, Tingwen

2018-06-01

The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Physical constraints on biological integral control design for homeostasis and sensory adaptation.

PubMed

Ang, Jordan; McMillen, David R

2013-01-22

Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

PubMed

Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin

2010-08-01

This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

The design and optimization for light-algae bioreactor controller based on Artificial Neural Network-Model Predictive Control

NASA Astrophysics Data System (ADS)

Hu, Dawei; Liu, Hong; Yang, Chenliang; Hu, Enzhu

As a subsystem of the bioregenerative life support system (BLSS), light-algae bioreactor (LABR) has properties of high reaction rate, efficiently synthesizing microalgal biomass, absorbing CO2 and releasing O2, so it is significant for BLSS to provide food and maintain gas balance. In order to manipulate the LABR properly, it has been designed as a closed-loop control system, and technology of Artificial Neural Network-Model Predictive Control (ANN-MPC) is applied to design the controller for LABR in which green microalgae, Spirulina platensis is cultivated continuously. The conclusion is drawn by computer simulation that ANN-MPC controller can intelligently learn the complicated dynamic performances of LABR, and automatically, robustly and self-adaptively regulate the light intensity illuminating on the LABR, hence make the growth of microalgae in the LABR be changed in line with the references, meanwhile provide appropriate damping to improve markedly the transient response performance of LABR.

Adaptive Neural Networks Prescribed Performance Control Design for Switched Interconnected Uncertain Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-06-28

In this paper, an adaptive neural networks (NNs)-based decentralized control scheme with the prescribed performance is proposed for uncertain switched nonstrict-feedback interconnected nonlinear systems. It is assumed that nonlinear interconnected terms and nonlinear functions of the concerned systems are unknown, and also the switching signals are unknown and arbitrary. A linear state estimator is constructed to solve the problem of unmeasured states. The NNs are employed to approximate unknown interconnected terms and nonlinear functions. A new output feedback decentralized control scheme is developed by using the adaptive backstepping design technique. The control design problem of nonlinear interconnected switched systems with unknown switching signals can be solved by the proposed scheme, and only a tuning parameter is needed for each subsystem. The proposed scheme can ensure that all variables of the control systems are semi-globally uniformly ultimately bounded and the tracking errors converge to a small residual set with the prescribed performance bound. The effectiveness of the proposed control approach is verified by some simulation results.

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

PubMed Central

Yang, Guisong; Liu, Shuai; He, Xingyu; Xiong, Naixue; Wu, Chunxue

2016-01-01

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density. PMID:27941662

Optical processing for future computer networks

NASA Technical Reports Server (NTRS)

Husain, A.; Haugen, P. R.; Hutcheson, L. D.; Warrior, J.; Murray, N.; Beatty, M.

1986-01-01

In the development of future data management systems, such as the NASA Space Station, a major problem represents the design and implementation of a high performance communication network which is self-correcting and repairing, flexible, and evolvable. To obtain the goal of designing such a network, it will be essential to incorporate distributed adaptive network control techniques. The present paper provides an outline of the functional and communication network requirements for the Space Station data management system. Attention is given to the mathematical representation of the operations being carried out to provide the required functionality at each layer of communication protocol on the model. The possible implementation of specific communication functions in optics is also considered.

Analyzing Feedback Control Systems

NASA Technical Reports Server (NTRS)

Bauer, Frank H.; Downing, John P.

1987-01-01

Interactive controls analysis (INCA) program developed to provide user-friendly environment for design and analysis of linear control systems, primarily feedback control. Designed for use with both small- and large-order systems. Using interactive-graphics capability, INCA user quickly plots root locus, frequency response, or time response of either continuous-time system or sampled-data system. Configuration and parameters easily changed, allowing user to design compensation networks and perform sensitivity analyses in very convenient manner. Written in Pascal and FORTRAN.

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

The Xpress Transfer Protocol (XTP): A tutorial (expanded version)

NASA Technical Reports Server (NTRS)

Sanders, Robert M.; Weaver, Alfred C.

1990-01-01

The Xpress Transfer Protocol (XTP) is a reliable, real-time, light weight transfer layer protocol. Current transport layer protocols such as DoD's Transmission Control Protocol (TCP) and ISO's Transport Protocol (TP) were not designed for the next generation of high speed, interconnected reliable networks such as fiber distributed data interface (FDDI) and the gigabit/second wide area networks. Unlike all previous transport layer protocols, XTP is being designed to be implemented in hardware as a VLSI chip set. By streamlining the protocol, combining the transport and network layers and utilizing the increased speed and parallelization possible with a VLSI implementation, XTP will be able to provide the end-to-end data transmission rates demanded in high speed networks without compromising reliability and functionality. This paper describes the operation of the XTP protocol and in particular, its error, flow and rate control; inter-networking addressing mechanisms; and multicast support features, as defined in the XTP Protocol Definition Revision 3.4.

Neural-network-designed pulse sequences for robust control of singlet-triplet qubits

NASA Astrophysics Data System (ADS)

Yang, Xu-Chen; Yung, Man-Hong; Wang, Xin

2018-04-01

Composite pulses are essential for universal manipulation of singlet-triplet spin qubits. In the absence of noise, they are required to perform arbitrary single-qubit operations due to the special control constraint of a singlet-triplet qubit, while in a noisy environment, more complicated sequences have been developed to dynamically correct the error. Tailoring these sequences typically requires numerically solving a set of nonlinear equations. Here we demonstrate that these pulse sequences can be generated by a well-trained, double-layer neural network. For sequences designed for the noise-free case, the trained neural network is capable of producing almost exactly the same pulses known in the literature. For more complicated noise-correcting sequences, the neural network produces pulses with slightly different line shapes, but the robustness against noises remains comparable. These results indicate that the neural network can be a judicious and powerful alternative to existing techniques in developing pulse sequences for universal fault-tolerant quantum computation.

Local synchronization of chaotic neural networks with sampled-data and saturating actuators.

PubMed

Wu, Zheng-Guang; Shi, Peng; Su, Hongye; Chu, Jian

2014-12-01

This paper investigates the problem of local synchronization of chaotic neural networks with sampled-data and actuator saturation. A new time-dependent Lyapunov functional is proposed for the synchronization error systems. The advantage of the constructed Lyapunov functional lies in the fact that it is positive definite at sampling times but not necessarily between sampling times, and makes full use of the available information about the actual sampling pattern. A local stability condition of the synchronization error systems is derived, based on which a sampled-data controller with respect to the actuator saturation is designed to ensure that the master neural networks and slave neural networks are locally asymptotically synchronous. Two optimization problems are provided to compute the desired sampled-data controller with the aim of enlarging the set of admissible initial conditions or the admissible sampling upper bound ensuring the local synchronization of the considered chaotic neural networks. A numerical example is used to demonstrate the effectiveness of the proposed design technique.

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE PAGES

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; ...

2017-06-06

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Networked Rectenna Array for Smart Material Actuators

NASA Technical Reports Server (NTRS)

Choi, Sang H.; Golembiewski, Walter T.; Song, Kyo D.

2000-01-01

The concept of microwave-driven smart material actuators is envisioned as the best option to alleviate the complexity associated with hard-wired control circuitry. Networked rectenna patch array receives and converts microwave power into a DC power for an array of smart actuators. To use microwave power effectively, the concept of a power allocation and distribution (PAD) circuit is adopted for networking a rectenna/actuator patch array. The PAD circuit is imbedded into a single embodiment of rectenna and actuator array. The thin-film microcircuit embodiment of PAD circuit adds insignificant amount of rigidity to membrane flexibility. Preliminary design and fabrication of PAD circuitry that consists of a few nodal elements were made for laboratory testing. The networked actuators were tested to correlate the network coupling effect, power allocation and distribution, and response time. The features of preliminary design are 16-channel computer control of actuators by a PCI board and the compensator for a power failure or leakage of one or more rectennas.

Network control processor for a TDMA system

NASA Astrophysics Data System (ADS)

Suryadevara, Omkarmurthy; Debettencourt, Thomas J.; Shulman, R. B.

Two unique aspects of designing a network control processor (NCP) to monitor and control a demand-assigned, time-division multiple-access (TDMA) network are described. The first involves the implementation of redundancy by synchronizing the databases of two geographically remote NCPs. The two sets of databases are kept in synchronization by collecting data on both systems, transferring databases, sending incremental updates, and the parallel updating of databases. A periodic audit compares the checksums of the databases to ensure synchronization. The second aspect involves the use of a tracking algorithm to dynamically reallocate TDMA frame space. This algorithm detects and tracks current and long-term load changes in the network. When some portions of the network are overloaded while others have excess capacity, the algorithm automatically calculates and implements a new burst time plan.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks using feasibly-implementable rate adaptivity. • A buffer-management algorithm that is designed to reduce the size of router buffers, and hence energy consumed. • A packet-scheduling algorithm designed to minimize packet-processing energy requirements. Additional research is recommended in at least two areas: further exploration of rate-adaptation in network switching equipment, including incorporation of rate-adaptation in actual hardware, allowing experimentation in operational networks; and development of control protocols that allow parts of networks to be shut down while minimizing disruption to traffic flow in the network. The research is an integral part of a large effort within Bell Laboratories, Alcatel-Lucent, aimed at dramatic improvements in the energy efficiency of telecommunication networks. This Study did not explicitly consider any commercialization opportunities.« less

Predictive control and estimation algorithms for the NASA/JPL 70-meter antennas

NASA Technical Reports Server (NTRS)

Gawronski, W.

1991-01-01

A modified output prediction procedure and a new controller design is presented based on the predictive control law. Also, a new predictive estimator is developed to complement the controller and to enhance system performance. The predictive controller is designed and applied to the tracking control of the Deep Space Network 70 m antennas. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

Vibration control of uncertain multiple launch rocket system using radial basis function neural network

NASA Astrophysics Data System (ADS)

Li, Bo; Rui, Xiaoting

2018-01-01

Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

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

NASA Astrophysics Data System (ADS)

Deng, Lei; Gong, Mengmeng; Zhu, Peiyong

2018-03-01

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

BGen: A UML Behavior Network Generator Tool

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

2010-01-01

BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

Distributed formation control of nonholonomic autonomous vehicle via RBF neural network

NASA Astrophysics Data System (ADS)

Yang, Shichun; Cao, Yaoguang; Peng, Zhaoxia; Wen, Guoguang; Guo, Konghui

2017-03-01

In this paper, RBF neural network consensus-based distributed control scheme is proposed for nonholonomic autonomous vehicles in a pre-defined formation along the specified reference trajectory. A variable transformation is first designed to convert the formation control problem into a state consensus problem. Then, the complete dynamics of the vehicles including inertia, Coriolis, friction model and unmodeled bounded disturbances are considered, which lead to the formation unstable when the distributed kinematic controllers are proposed based on the kinematics. RBF neural network torque controllers are derived to compensate for them. Some sufficient conditions are derived to accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov theory. Finally, simulation examples illustrate the effectiveness of the proposed controllers.

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

PubMed

Chen, Jiejie; Chen, Boshan; Zeng, Zhigang

2018-04-01

This paper investigates O(t -α )-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and differential inclusion theory, using a Razumikhin-type method, some sufficient conditions ensuring the global O(t -α )-synchronization of considered networks are established via a linear-type discontinuous control. Next, a new fractional differential inequality is established and two new discontinuous adaptive controller is designed to achieve Mittag-Leffler synchronization between the drive system and the response systems using this inequality. Finally, two numerical simulations are given to show the effectiveness of the theoretical results. Our approach and theoretical results have a leading significance in the design of synchronized fractional-order memristive neural networks circuits involving discontinuous activations and time-varying delays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Trade-offs between driving nodes and time-to-control in complex networks

PubMed Central

Pequito, Sérgio; Preciado, Victor M.; Barabási, Albert-László; Pappas, George J.

2017-01-01

Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, which we used to find that in many complex networks only a small fraction of driving (or driven) nodes is required to steer the network to a desired state within a relatively small time window. Furthermore, our empirical studies reveal that, even though synthetic network models are designed to present structural properties similar to those observed in real networks, their actuation spectra can be dramatically different. Thus, it supports the need to develop new synthetic network models able to replicate controllability properties of real-world networks. PMID:28054597

Trade-offs between driving nodes and time-to-control in complex networks

NASA Astrophysics Data System (ADS)

Pequito, Sérgio; Preciado, Victor M.; Barabási, Albert-László; Pappas, George J.

2017-01-01

Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, which we used to find that in many complex networks only a small fraction of driving (or driven) nodes is required to steer the network to a desired state within a relatively small time window. Furthermore, our empirical studies reveal that, even though synthetic network models are designed to present structural properties similar to those observed in real networks, their actuation spectra can be dramatically different. Thus, it supports the need to develop new synthetic network models able to replicate controllability properties of real-world networks.

Analytical Models of Cross-Layer Protocol Optimization in Real-Time Wireless Sensor Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

The real-time interactions among the nodes of a wireless sensor network (WSN) to cooperatively process data from multiple sensors are modeled. Quality-of-service (QoS) metrics are associated with the quality of fused information: throughput, delay, packet error rate, etc. Multivariate point process (MVPP) models of discrete random events in WSNs establish stochastic characteristics of optimal cross-layer protocols. Discrete-event, cross-layer interactions in mobile ad hoc network (MANET) protocols have been modeled using a set of concatenated design parameters and associated resource levels by the MVPPs. Characterization of the "best" cross-layer designs for a MANET is formulated by applying the general theory of martingale representations to controlled MVPPs. Performance is described in terms of concatenated protocol parameters and controlled through conditional rates of the MVPPs. Modeling limitations to determination of closed-form solutions versus explicit iterative solutions for ad hoc WSN controls are examined.

Embarked electrical network robust control based on singular perturbation model.

PubMed

Abdeljalil Belhaj, Lamya; Ait-Ahmed, Mourad; Benkhoris, Mohamed Fouad

2014-07-01

This paper deals with an approach of modelling in view of control for embarked networks which can be described as strongly coupled multi-sources, multi-loads systems with nonlinear and badly known characteristics. This model has to be representative of the system behaviour and easy to handle for easy regulators synthesis. As a first step, each alternator is modelled and linearized around an operating point and then it is subdivided into two lower order systems according to the singular perturbation theory. RST regulators are designed for each subsystem and tested by means of a software test-bench which allows predicting network behaviour in both steady and transient states. Finally, the designed controllers are implanted on an experimental benchmark constituted by two alternators supplying loads in order to test the dynamic performances in realistic conditions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Optimizing digital elevation models (DEMs) accuracy for planning and design of mobile communication networks

NASA Astrophysics Data System (ADS)

Hassan, Mahmoud A.

2004-02-01

Digital elevation models (DEMs) are important tools in the planning, design and maintenance of mobile communication networks. This research paper proposes a method for generating high accuracy DEMs based on SPOT satellite 1A stereo pair images, ground control points (GCP) and Erdas OrthoBASE Pro image processing software. DEMs with 0.2911 m mean error were achieved for the hilly and heavily populated city of Amman. The generated DEM was used to design a mobile communication network resulted in a minimum number of radio base transceiver stations, maximum number of covered regions and less than 2% of dead zones.

Exponential lag function projective synchronization of memristor-based multidirectional associative memory neural networks via hybrid control

NASA Astrophysics Data System (ADS)

Yuan, Manman; Wang, Weiping; Luo, Xiong; Li, Lixiang; Kurths, Jürgen; Wang, Xiao

2018-03-01

This paper is concerned with the exponential lag function projective synchronization of memristive multidirectional associative memory neural networks (MMAMNNs). First, we propose a new model of MMAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying discrete delays and distributed time delays. Second, we design two kinds of hybrid controllers. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the controllers are carefully designed to confirm the process of different types of synchronization in the MMAMNNs. Third, sufficient criteria guaranteeing the synchronization of system are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

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

PubMed

Xia, Kewei; Huo, Wei

2016-05-01

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

Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework.

PubMed

Cai, Zuowei; Huang, Lihong; Guo, Zhenyuan; Zhang, Lingling; Wan, Xuting

2015-08-01

This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani's fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive-response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things.

PubMed

Yi, Meng; Chen, Qingkui; Xiong, Neal N

2016-11-03

This paper considers the distributed access and control problem of massive wireless sensor networks' data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

A Novel Instructional Approach to the Design of Standard Controllers: Using Inversion Formulae

ERIC Educational Resources Information Center

Ntogramatzidis, Lorenzo; Zanasi, Roberto; Cuoghi, Stefania

2014-01-01

This paper describes a range of design techniques for standard compensators (Lead-Lag networks and PID controllers) that have been applied to the teaching of many undergraduate control courses throughout Italy over the last twenty years, but that have received little attention elsewhere. These techniques hinge upon a set of simple formulas--herein…

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

SVM-based tree-type neural networks as a critic in adaptive critic designs for control.

PubMed

Deb, Alok Kanti; Jayadeva; Gopal, Madan; Chandra, Suresh

2007-07-01

In this paper, we use the approach of adaptive critic design (ACD) for control, specifically, the action-dependent heuristic dynamic programming (ADHDP) method. A least squares support vector machine (SVM) regressor has been used for generating the control actions, while an SVM-based tree-type neural network (NN) is used as the critic. After a failure occurs, the critic and action are retrained in tandem using the failure data. Failure data is binary classification data, where the number of failure states are very few as compared to the number of no-failure states. The difficulty of conventional multilayer feedforward NNs in learning this type of classification data has been overcome by using the SVM-based tree-type NN, which due to its feature to add neurons to learn misclassified data, has the capability to learn any binary classification data without a priori choice of the number of neurons or the structure of the network. The capability of the trained controller to handle unforeseen situations is demonstrated.

Dillard Drive Middle & Elementary School, Raleigh, North Carolina.

ERIC Educational Resources Information Center

Design Cost Data, 2001

2001-01-01

Presents design features of the Dillard Drive Middle & Elementary School (North Carolina) that incorporates daylighting in the majority of the classrooms, the gymnasium, dining room, and media center. The design also uses advanced lighting controls, fiber optic networking, automatic environmental controls, and an energy management system that…

The Use of Decentralized Control in the Design of a Large Segmented Space Reflector

NASA Technical Reports Server (NTRS)

Ryaciotaki-Boussalis, Helen; Mirmirani, Maj; Rad, Khosrow; Morales, Mauricio; Velazquez, Efrain; Chassiakos, Anastasios; Luzardo, Jose-Alberto

1997-01-01

The 3-dimensional model for a segmented reflector telescope is developed using finite element techniques. The structure is decomposed into six subsystems. System control design using neural networks is performed. Performance evaluation is demonstrated via simulation using PRO-MATLAB and SIMULINK.

Engineering Design of ITER Prototype Fast Plant System Controller

NASA Astrophysics Data System (ADS)

Goncalves, B.; Sousa, J.; Carvalho, B.; Rodrigues, A. P.; Correia, M.; Batista, A.; Vega, J.; Ruiz, M.; Lopez, J. M.; Rojo, R. Castro; Wallander, A.; Utzel, N.; Neto, A.; Alves, D.; Valcarcel, D.

2011-08-01

The ITER control, data access and communication (CODAC) design team identified the need for two types of plant systems. A slow control plant system is based on industrial automation technology with maximum sampling rates below 100 Hz, and a fast control plant system is based on embedded technology with higher sampling rates and more stringent real-time requirements than that required for slow controllers. The latter is applicable to diagnostics and plant systems in closed-control loops whose cycle times are below 1 ms. Fast controllers will be dedicated industrial controllers with the ability to supervise other fast and/or slow controllers, interface to actuators and sensors and, if necessary, high performance networks. Two prototypes of a fast plant system controller specialized for data acquisition and constrained by ITER technological choices are being built using two different form factors. This prototyping activity contributes to the Plant Control Design Handbook effort of standardization, specifically regarding fast controller characteristics. Envisaging a general purpose fast controller design, diagnostic use cases with specific requirements were analyzed and will be presented along with the interface with CODAC and sensors. The requirements and constraints that real-time plasma control imposes on the design were also taken into consideration. Functional specifications and technology neutral architecture, together with its implications on the engineering design, were considered. The detailed engineering design compliant with ITER standards was performed and will be discussed in detail. Emphasis will be given to the integration of the controller in the standard CODAC environment. Requirements for the EPICS IOC providing the interface to the outside world, the prototype decisions on form factor, real-time operating system, and high-performance networks will also be discussed, as well as the requirements for data streaming to CODAC for visualization and archiving.

Converging Redundant Sensor Network Information for Improved Building Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dale Tiller; D. Phil; Gregor Henze

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-planmore » 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.« less

Packet Controller For Wireless Headset

NASA Technical Reports Server (NTRS)

Christensen, Kurt K.; Swanson, Richard J.

1993-01-01

Packet-message controller implements communications protocol of network of wireless headsets. Designed for headset application, readily adapted to other uses; slight modification enables controller to implement Integrated Services Digital Network (ISDN) X.25 protocol, giving far-reaching applications in telecommunications. Circuit converts continuous voice signals into digital packets of data and vice versa. Operates in master or slave mode. Controller reduced to single complementary metal oxide/semiconductor integrated-circuit chip. Occupies minimal space in headset and consumes little power, extending life of headset battery.

Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Dibley, Ryan P.

2003-01-01

Neural networks were used to model wing bending-moment loads, torsion loads, and control surface hinge-moments of the Active Aeroelastic Wing (AAW) aircraft. Accurate loads models are required for the development of control laws designed to increase roll performance through wing twist while not exceeding load limits. Inputs to the model include aircraft rates, accelerations, and control surface positions. Neural networks were chosen to model aircraft loads because they can account for uncharacterized nonlinear effects while retaining the capability to generalize. The accuracy of the neural network models was improved by first developing linear loads models to use as starting points for network training. Neural networks were then trained with flight data for rolls, loaded reversals, wind-up-turns, and individual control surface doublets for load excitation. Generalization was improved by using gain weighting and early stopping. Results are presented for neural network loads models of four wing loads and four control surface hinge moments at Mach 0.90 and an altitude of 15,000 ft. An average model prediction error reduction of 18.6 percent was calculated for the neural network models when compared to the linear models. This paper documents the input data conditioning, input parameter selection, structure, training, and validation of the neural network models.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks

PubMed Central

Rialle, Stéphanie; Felicori, Liza; Dias-Lopes, Camila; Pérès, Sabine; El Atia, Sanaâ; Thierry, Alain R.; Amar, Patrick; Molina, Franck

2010-01-01

Motivation: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. Results: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. Availability and implementation: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/ Contact: stephanie.rialle@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20628073

An FPGA-Based Silicon Neuronal Network with Selectable Excitability Silicon Neurons

PubMed Central

Li, Jing; Katori, Yuichi; Kohno, Takashi

2012-01-01

This paper presents a digital silicon neuronal network which simulates the nerve system in creatures and has the ability to execute intelligent tasks, such as associative memory. Two essential elements, the mathematical-structure-based digital spiking silicon neuron (DSSN) and the transmitter release based silicon synapse, allow us to tune the excitability of silicon neurons and are computationally efficient for hardware implementation. We adopt mixed pipeline and parallel structure and shift operations to design a sufficient large and complex network without excessive hardware resource cost. The network with 256 full-connected neurons is built on a Digilent Atlys board equipped with a Xilinx Spartan-6 LX45 FPGA. Besides, a memory control block and USB control block are designed to accomplish the task of data communication between the network and the host PC. This paper also describes the mechanism of associative memory performed in the silicon neuronal network. The network is capable of retrieving stored patterns if the inputs contain enough information of them. The retrieving probability increases with the similarity between the input and the stored pattern increasing. Synchronization of neurons is observed when the successful stored pattern retrieval occurs. PMID:23269911

Reliability and availability evaluation of Wireless Sensor Networks for industrial applications.

PubMed

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements.

Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications

PubMed Central

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements. PMID:22368497

Design and Performance of the Acts Gigabit Satellite Network High Data-Rate Ground Station

NASA Technical Reports Server (NTRS)

Hoder, Doug; Kearney, Brian

1995-01-01

The ACTS High Data-Rate Ground stations were built to support the ACTS Gigabit Satellite Network (GSN). The ACTS GSN was designed to provide fiber-compatible SONET service to remote nodes and networks through a wideband satellite system. The ACTS satellite is unique in its extremely wide bandwidth, and electronically controlled spot beam antennas. This paper discusses the requirements, design and performance of the RF section of the ACTS High Data-Rate Ground Stations and constituent hardware. The ACTS transponder systems incorporate highly nonlinear hard limiting. This introduced a major complexity in to the design and subsequent modification of the ground stations. A discussion of the peculiarities of the A CTS spacecraft transponder system and their impact is included.

Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

PubMed

Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

2015-07-01

The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

NASA Technical Reports Server (NTRS)

Principe, Jose C.

2007-01-01

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

GLOBECOM '88 - IEEE Global Telecommunications Conference and Exhibition, Hollywood, FL, Nov. 28-Dec. 1, 1988, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Various papers on communications for the information age are presented. Among the general topics considered are: telematic services and terminals, satellite communications, telecommunications mangaement network, control of integrated broadband networks, advances in digital radio systems, the intelligent network, broadband networks and services deployment, future switch architectures, performance analysis of computer networks, advances in spread spectrum, optical high-speed LANs, and broadband switching and networks. Also addressed are: multiple access protocols, video coding techniques, modulation and coding, photonic switching, SONET terminals and applications, standards for video coding, digital switching, progress in MANs, mobile and portable radio, software design for improved maintainability, multipath propagation and advanced countermeasure, data communication, network control and management, fiber in the loop, network algorithm and protocols, and advances in computer communications.

Evaluating the performance of vehicular platoon control under different network topologies of initial states

NASA Astrophysics Data System (ADS)

Li, Yongfu; Li, Kezhi; Zheng, Taixiong; Hu, Xiangdong; Feng, Huizong; Li, Yinguo

2016-05-01

This study proposes a feedback-based platoon control protocol for connected autonomous vehicles (CAVs) under different network topologies of initial states. In particularly, algebraic graph theory is used to describe the network topology. Then, the leader-follower approach is used to model the interactions between CAVs. In addition, feedback-based protocol is designed to control the platoon considering the longitudinal and lateral gaps simultaneously as well as different network topologies. The stability and consensus of the vehicular platoon is analyzed using the Lyapunov technique. Effects of different network topologies of initial states on convergence time and robustness of platoon control are investigated. Results from numerical experiments demonstrate the effectiveness of the proposed protocol with respect to the position and velocity consensus in terms of the convergence time and robustness. Also, the findings of this study illustrate the convergence time of the control protocol is associated with the initial states, while the robustness is not affected by the initial states significantly.

Multi-layer neural networks for robot control

NASA Technical Reports Server (NTRS)

Pourboghrat, Farzad

1989-01-01

Two neural learning controller designs for manipulators are considered. The first design is based on a neural inverse-dynamics system. The second is the combination of the first one with a neural adaptive state feedback system. Both types of controllers enable the manipulator to perform any given task very well after a period of training and to do other untrained tasks satisfactorily. The second design also enables the manipulator to compensate for unpredictable perturbations.

Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering

NASA Astrophysics Data System (ADS)

Doursat, René

Exploding growth growth in computational systems forces us to gradually replace rigid design and control with decentralization and autonomy. Information technologies will progress, instead, by"meta-designing" mechanisms of system self-assembly, self-regulation and evolution. Nature offers a great variety of efficient complex systems, in which numerous small elements form large-scale, adaptive patterns. The new engineering challenge is to recreate this self-organization and let it freely generate innovative designs under guidance. This article presents an original model of artificial system growth inspired by embryogenesis. A virtual organism is a lattice of cells that proliferate, migrate and self-pattern into differentiated domains. Each cell's fate is controlled by an internal gene regulatory network network. Embryomorphic engineering emphasizes hyperdistributed architectures, and their development as a prerequisite of evolutionary design.

A probabilistic approach to identify putative drug targets in biochemical networks.

PubMed

Murabito, Ettore; Smallbone, Kieran; Swinton, Jonathan; Westerhoff, Hans V; Steuer, Ralf

2011-06-06

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual components, responds to specific perturbations in different physiological conditions. Proteins exerting little control over normal cells and larger control over altered cells may be considered as good candidates for drug targets. The application of network-based drug design would greatly benefit from using an explicit computational model describing the dynamics of the system under investigation. However, creating a fully characterized kinetic model is not an easy task, even for relatively small networks, as it is still significantly hampered by the lack of data about kinetic mechanisms and parameters values. Here, we propose a Monte Carlo approach to identify the differences between flux control profiles of a metabolic network in different physiological states, when information about the kinetics of the system is partially or totally missing. Based on experimentally accessible information on metabolic phenotypes, we develop a novel method to determine probabilistic differences in the flux control coefficients between the two observable phenotypes. Knowledge of how differences in flux control are distributed among the different enzymatic steps is exploited to identify points of fragility in one of the phenotypes. Using a prototypical cancerous phenotype as an example, we demonstrate how our approach can assist researchers in developing compounds with high efficacy and low toxicity. © 2010 The Royal Society

Rational design of functional and tunable oscillating enzymatic networks

NASA Astrophysics Data System (ADS)

Semenov, Sergey N.; Wong, Albert S. Y.; van der Made, R. Martijn; Postma, Sjoerd G. J.; Groen, Joost; van Roekel, Hendrik W. H.; de Greef, Tom F. A.; Huck, Wilhelm T. S.

2015-02-01

Life is sustained by complex systems operating far from equilibrium and consisting of a multitude of enzymatic reaction networks. The operating principles of biology's regulatory networks are known, but the in vitro assembly of out-of-equilibrium enzymatic reaction networks has proved challenging, limiting the development of synthetic systems showing autonomous behaviour. Here, we present a strategy for the rational design of programmable functional reaction networks that exhibit dynamic behaviour. We demonstrate that a network built around autoactivation and delayed negative feedback of the enzyme trypsin is capable of producing sustained oscillating concentrations of active trypsin for over 65 h. Other functions, such as amplification, analog-to-digital conversion and periodic control over equilibrium systems, are obtained by linking multiple network modules in microfluidic flow reactors. The methodology developed here provides a general framework to construct dissipative, tunable and robust (bio)chemical reaction networks.

Network-Cognizant Design of Decentralized Volt/VAR Controllers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri A; Bernstein, Andrey; Zhao, Changhong

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 aremore » reported to corroborate the technical findings.« less

OXC management and control system architecture with scalability, maintenance, and distributed managing environment

NASA Astrophysics Data System (ADS)

Park, Soomyung; Joo, Seong-Soon; Yae, Byung-Ho; Lee, Jong-Hyun

2002-07-01

In this paper, we present the Optical Cross-Connect (OXC) Management Control System Architecture, which has the scalability and robust maintenance and provides the distributed managing environment in the optical transport network. The OXC system we are developing, which is divided into the hardware and the internal and external software for the OXC system, is made up the OXC subsystem with the Optical Transport Network (OTN) sub layers-hardware and the optical switch control system, the signaling control protocol subsystem performing the User-to-Network Interface (UNI) and Network-to-Network Interface (NNI) signaling control, the Operation Administration Maintenance & Provisioning (OAM&P) subsystem, and the network management subsystem. And the OXC management control system has the features that can support the flexible expansion of the optical transport network, provide the connectivity to heterogeneous external network elements, be added or deleted without interrupting OAM&P services, be remotely operated, provide the global view and detail information for network planner and operator, and have Common Object Request Broker Architecture (CORBA) based the open system architecture adding and deleting the intelligent service networking functions easily in future. To meet these considerations, we adopt the object oriented development method in the whole developing steps of the system analysis, design, and implementation to build the OXC management control system with the scalability, the maintenance, and the distributed managing environment. As a consequently, the componentification for the OXC operation management functions of each subsystem makes the robust maintenance, and increases code reusability. Also, the component based OXC management control system architecture will have the flexibility and scalability in nature.

GMPLS-based control plane for optical networks: early implementation experience

NASA Astrophysics Data System (ADS)

Liu, Hang; Pendarakis, Dimitrios; Komaee, Nooshin; Saha, Debanjan

2002-07-01

Generalized Multi-Protocol Label Switching (GMPLS) extends MPLS signaling and Internet routing protocols to provide a scalable, interoperable, distributed control plane, which is applicable to multiple network technologies such as optical cross connects (OXCs), photonic switches, IP routers, ATM switches, SONET and DWDM systems. It is intended to facilitate automatic service provisioning and dynamic neighbor and topology discovery across multi-vendor intelligent transport networks, as well as their clients. Efforts to standardize such a distributed common control plane have reached various stages in several bodies such as the IETF, ITU and OIF. This paper describes the design considerations and architecture of a GMPLS-based control plane that we have prototyped for core optical networks. Functional components of GMPLS signaling and routing are integrated in this architecture with an application layer controller module. Various requirements including bandwidth, network protection and survivability, traffic engineering, optimal utilization of network resources, and etc. are taken into consideration during path computation and provisioning. Initial experiments with our prototype demonstrate the feasibility and main benefits of GMPLS as a distributed control plane for core optical networks. In addition to such feasibility results, actual adoption and deployment of GMPLS as a common control plane for intelligent transport networks will depend on the successful completion of relevant standardization activities, extensive interoperability testing as well as the strengthening of appropriate business drivers.

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.

PubMed

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-03-07

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

Predictive functional control for active queue management in congested TCP/IP networks.

PubMed

Bigdeli, N; Haeri, M

2009-01-01

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE PAGES

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano; ...

2017-08-07

Our 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 themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

Our 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 themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

An extended smart utilization medium access control (ESU-MAC) protocol for ad hoc wireless systems

NASA Astrophysics Data System (ADS)

Vashishtha, Jyoti; Sinha, Aakash

2006-05-01

The demand for spontaneous setup of a wireless communication system has increased in recent years for areas like battlefield, disaster relief operations etc., where a pre-deployment of network infrastructure is difficult or unavailable. A mobile ad-hoc network (MANET) is a promising solution, but poses a lot of challenges for all the design layers, specifically medium access control (MAC) layer. Recent existing works have used the concepts of multi-channel and power control in designing MAC layer protocols. SU-MAC developed by the same authors, efficiently uses the 'available' data and control bandwidth to send control information and results in increased throughput via decreasing contention on the control channel. However, SU-MAC protocol was limited for static ad-hoc network and also faced the busy-receiver node problem. We present the Extended SU-MAC (ESU-MAC) protocol which works mobile nodes. Also, we significantly improve the scheme of control information exchange in ESU-MAC to overcome the busy-receiver node problem and thus, further avoid the blockage of control channel for longer periods of time. A power control scheme is used as before to reduce interference and to effectively re-use the available bandwidth. Simulation results show that ESU-MAC protocol is promising for mobile, ad-hoc network in terms of reduced contention at the control channel and improved throughput because of channel re-use. Results show a considerable increase in throughput compared to SU-MAC which could be attributed to increased accessibility of control channel and improved utilization of data channels due to superior control information exchange scheme.

GrDHP: a general utility function representation for dual heuristic dynamic programming.

PubMed

Ni, Zhen; He, Haibo; Zhao, Dongbin; Xu, Xin; Prokhorov, Danil V

2015-03-01

A general utility function representation is proposed to provide the required derivable and adjustable utility function for the dual heuristic dynamic programming (DHP) design. Goal representation DHP (GrDHP) is presented with a goal network being on top of the traditional DHP design. This goal network provides a general mapping between the system states and the derivatives of the utility function. With this proposed architecture, we can obtain the required derivatives of the utility function directly from the goal network. In addition, instead of a fixed predefined utility function in literature, we conduct an online learning process for the goal network so that the derivatives of the utility function can be adaptively tuned over time. We provide the control performance of both the proposed GrDHP and the traditional DHP approaches under the same environment and parameter settings. The statistical simulation results and the snapshot of the system variables are presented to demonstrate the improved learning and controlling performance. We also apply both approaches to a power system example to further demonstrate the control capabilities of the GrDHP approach.

A Mobile Satellite Experiment (MSAT-X) network definition

NASA Technical Reports Server (NTRS)

Wang, Charles C.; Yan, Tsun-Yee

1990-01-01

The network architecture development of the Mobile Satellite Experiment (MSAT-X) project for the past few years is described. The results and findings of the network research activities carried out under the MSAT-X project are summarized. A framework is presented upon which the Mobile Satellite Systems (MSSs) operator can design a commercial network. A sample network configuration and its capability are also included under the projected scenario. The Communication Interconnection aspect of the MSAT-X network is discussed. In the MSAT-X network structure two basic protocols are presented: the channel access protocol, and the link connection protocol. The error-control techniques used in the MSAT-X project and the packet structure are also discussed. A description of two testbeds developed for experimentally simulating the channel access protocol and link control protocol, respectively, is presented. A sample network configuration and some future network activities of the MSAT-X project are also presented.

Feasibility of Decentralized Linear-Quadratic-Gaussian Control of Autonomous Distributed Spacecraft

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1999-01-01

A distributed satellite formation, modeled as an arbitrary number of fully connected nodes in a network, could be controlled using a decentralized controller framework that distributes operations in parallel over the network. For such problems, a solution that minimizes data transmission requirements, in the context of linear-quadratic-Gaussian (LQG) control theory, was given by Speyer. This approach is advantageous because it is non-hierarchical, detected failures gracefully degrade system performance, fewer local computations are required than for a centralized controller, and it is optimal with respect to the standard LQG cost function. Disadvantages of the approach are the need for a fully connected communications network, the total operations performed over all the nodes are greater than for a centralized controller, and the approach is formulated for linear time-invariant systems. To investigate the feasibility of the decentralized approach to satellite formation flying, a simple centralized LQG design for a spacecraft orbit control problem is adapted to the decentralized framework. The simple design uses a fixed reference trajectory (an equatorial, Keplerian, circular orbit), and by appropriate choice of coordinates and measurements is formulated as a linear time-invariant system.

Computational Methods for Design, Estimation and Real-Time Control of PDE Systems with Applications to Mobile Sensor Networks

DTIC Science & Technology

2013-08-14

TIME CONTROL OF PDE SYSTEMS WITH APPLICATIONS TO MOBILE SENSOR NETWORKS Finall Report: AFOSR Grant...linear time invariant (LTI) control problem. If the control is a linear function of the states, then the closed loop system then takes the form[ żr u̇...Ar2 A r 3 0T 0 ] − [ Br 1 ] K ) ︸ ︷︷ ︸ Ac [ zr u ] . (3) As the purpose of the control law is to stabilize the system , it is desired to have

Real-time controller for foot-drop correction by using surface electromyography sensor.

PubMed

Al Mashhadany, Yousif I; Abd Rahim, Nasrudin

2013-04-01

Foot drop is a disease caused mainly by muscle paralysis, which incapacitates the nerves generating the impulses that control feet in a heel strike. The incapacity may stem from lesions that affect the brain, the spinal cord, or peripheral nerves. The foot becomes dorsiflexed, affecting normal walking. A design and analysis of a controller for such legs is the subject of this article. Surface electromyography electrodes are connected to the skin surface of the human muscle and work on the mechanics of human muscle contraction. The design uses real surface electromyography signals for estimation of the joint angles. Various-speed flexions and extensions of the leg were analyzed. The two phases of the design began with surface electromyography of real human leg electromyography signal, which was subsequently filtered, amplified, and normalized to the maximum amplitude. Parameters extracted from the surface electromyography signal were then used to train an artificial neural network for prediction of the joint angle. The artificial neural network design included various-speed identification of the electromyography signal and estimation of the angles of the knee and ankle joints by a recognition process that depended on the parameters of the real surface electromyography signal measured through real movements. The second phase used artificial neural network estimation of the control signal, for calculation of the electromyography signal to be stimulated for the leg muscle to move the ankle joint. Satisfactory simulation (MATLAB/Simulink version 2012a) and implementation results verified the design feasibility.

Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations: state feedback control and impulsive control schemes.

PubMed

Ding, Xiaoshuai; Cao, Jinde; Zhao, Xuan; Alsaadi, Fuad E

2017-08-01

This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

A continually online-trained neural network controller for brushless DC motor drives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

Effect of various features on the life cycle cost of the timing/synchronization subsystem of the DCS digital communications network

NASA Technical Reports Server (NTRS)

Kimsey, D. B.

1978-01-01

The effect on the life cycle cost of the timing subsystem was examined, when these optional features were included in various combinations. The features included mutual control, directed control, double-ended reference links, independence of clock error measurement and correction, phase reference combining, self-organization, smoothing for link and nodal dropouts, unequal reference weightings, and a master in a mutual control network. An overall design of a microprocessor-based timing subsystem was formulated. The microprocessor (8080) implements the digital filter portion of a digital phase locked loop, as well as other control functions such as organization of the network through communication with processors at neighboring nodes.

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

NASA Technical Reports Server (NTRS)

Burken, John J.; Larson, Richard R.

2009-01-01

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

Performance management of multiple access communication networks

NASA Astrophysics Data System (ADS)

Lee, Suk; Ray, Asok

1993-12-01

This paper focuses on conceptual design, development, and implementation of a performance management tool for computer communication networks to serve large-scale integrated systems. The objective is to improve the network performance in handling various types of messages by on-line adjustment of protocol parameters. The techniques of perturbation analysis of Discrete Event Dynamic Systems (DEDS), stochastic approximation (SA), and learning automata have been used in formulating the algorithm of performance management. The efficacy of the performance management tool has been demonstrated on a network testbed. The conceptual design presented in this paper offers a step forward to bridging the gap between management standards and users' demands for efficient network operations since most standards such as ISO (International Standards Organization) and IEEE address only the architecture, services, and interfaces for network management. The proposed concept of performance management can also be used as a general framework to assist design, operation, and management of various DEDS such as computer integrated manufacturing and battlefield C(sup 3) (Command, Control, and Communications).

Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

NASA Astrophysics Data System (ADS)

Wu, Zhengping; Wu, Hao

With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

Control of fluxes in metabolic networks

PubMed Central

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

2016-01-01

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

On an LAS-integrated soft PLC system based on WorldFIP fieldbus.

PubMed

Liang, Geng; Li, Zhijun; Li, Wen; Bai, Yan

2012-01-01

Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

PCDAS Version 2. 2: Remote network control and data acquisition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fishbaugher, M.J.

1987-09-01

This manual is intended for both technical and non-technical people who want to use the PCDAS remote network control and data acquisition software. If you are unfamiliar with remote data collection hardware systems designed at Pacific Northwest Laboratory (PNL), this introduction should answer your basic questions. Even if you have some experience with the PNL-designed Field Data Acquisition Systems (FDAS), it would be wise to review this material before attempting to set up a network. This manual was written based on the assumption that you have a rudimentary understanding of personal computer (PC) operations using Disk Operating System (DOS) versionmore » 2.0 or greater (IBM 1984). You should know how to create subdirectories and get around the subdirectory tree.« less

The Deep Space Network

NASA Technical Reports Server (NTRS)

1974-01-01

The objectives, functions, and organization, of the Deep Space Network are summarized. Deep Space stations, ground communications, and network operations control capabilities are described. The network is designed for two-way communications with unmanned spacecraft traveling approximately 1600 km from earth to the farthest planets in the solar system. It has provided tracking and data acquisition support for the following projects: Ranger, Surveyor, Mariner, Pioneer, Apollo, Helios, Viking, and the Lunar Orbiter.

Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages.

PubMed

Komarova, Natalia L; van den Driessche, P

2018-05-01

Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages. We focus on "minimal" networks that are those that have the smallest possible numbers of controls. For such minimal networks, the number of controls must be equal to the number of compartments, and the reducibility/irreducibility of the network (whether or not it can be split into smaller independent sub-networks) is defined by a matrix comprised of the cell number increments induced by each of the controlled processes in each of the compartments. Using the formalism of digraphs, we show that in two-compartment lineages, reducible systems must contain two 1-cycles, and irreducible systems one 1-cycle and one 2-cycle; stability follows from the signs of the controls and does not require magnitude restrictions. In three-compartment systems, irreducible digraphs have a tree structure or have one 3-cycle and at least two more shorter cycles, at least one of which is a 1-cycle. With further work and proper biological validation, our results may serve as a first step toward an understanding of ways in which these networks become dysregulated in cancer.

Network-based production quality control

NASA Astrophysics Data System (ADS)

Kwon, Yongjin; Tseng, Bill; Chiou, Richard

2007-09-01

This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.

Hyperactivity of the default-mode network in first-episode, drug-naive schizophrenia at rest revealed by family-based case-control and traditional case-control designs.

PubMed

Guo, Wenbin; Liu, Feng; Chen, Jindong; Wu, Renrong; Li, Lehua; Zhang, Zhikun; Chen, Huafu; Zhao, Jingping

2017-03-01

Abnormal regional activity and functional connectivity of the default-mode network (DMN) have been reported in schizophrenia. However, previous studies may have been biased by unmatched case-control design. To limit such bias, the present study used both the family-based case-control design and the traditional case-control design to investigate abnormal regional activity of the DMN in patients with schizophrenia at rest.Twenty-eight first-episode, drug-naive patients with schizophrenia, 28 age-, sex-matched unaffected siblings of the patients (family-based controls, FBC), and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scans. The group-independent component analysis and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze the data.Patients with schizophrenia show increased fALFF in an overlapped region of the right superior medial prefrontal cortex (MPFC) relative to the FBC and the HC. Compared with the HC, the patients and the FBC exhibit increased fALFF in an overlapped region of the left posterior cingulate cortex/precuneus (PCC/PCu). Furthermore, the z values of the 2 overlapped regions can separate the patients from the FBC/HC, and separate the patients/FBC from the HC with relatively high sensitivity and specificity.Both the family-based case-control and traditional case-control designs reveal hyperactivity of the DMN in first-episode, drug-naive patients with paranoid schizophrenia, which highlights the importance of the DMN in the neurobiology of schizophrenia. Family-based case-control design can limit the confounding effects of environmental factors in schizophrenia. Combination of the family-based case-control and traditional case-control designs may be a viable option for the neuroimaging studies.

Space station common module network topology and hardware development

NASA Technical Reports Server (NTRS)

Anderson, P.; Braunagel, L.; Chwirka, S.; Fishman, M.; Freeman, K.; Eason, D.; Landis, D.; Lech, L.; Martin, J.; Mccorkle, J.

1990-01-01

Conceptual space station common module power management and distribution (SSM/PMAD) network layouts and detailed network evaluations were developed. Individual pieces of hardware to be developed for the SSM/PMAD test bed were identified. A technology assessment was developed to identify pieces of equipment requiring development effort. Equipment lists were developed from the previously selected network schematics. Additionally, functional requirements for the network equipment as well as other requirements which affected the suitability of specific items for use on the Space Station Program were identified. Assembly requirements were derived based on the SSM/PMAD developed requirements and on the selected SSM/PMAD network concepts. Basic requirements and simplified design block diagrams are included. DC remote power controllers were successfully integrated into the DC Marshall Space Flight Center breadboard. Two DC remote power controller (RPC) boards experienced mechanical failure of UES 706 stud-mounted diodes during mechanical installation of the boards into the system. These broken diodes caused input to output shorting of the RPC's. The UES 706 diodes were replaced on these RPC's which eliminated the problem. The DC RPC's as existing in the present breadboard configuration do not provide ground fault protection because the RPC was designed to only switch the hot side current. If ground fault protection were to be implemented, it would be necessary to design the system so the RPC switched both the hot and the return sides of power.

Evolutionary transitions in controls reconcile adaptation with continuity of evolution.

PubMed

Badyaev, Alexander V

2018-05-19

Evolution proceeds by accumulating functional solutions, necessarily forming an uninterrupted lineage from past solutions of ancestors to the current design of extant forms. At the population level, this process requires an organismal architecture in which the maintenance of local adaptation does not preclude the ability to innovate in the same traits and their continuous evolution. Representing complex traits as networks enables us to visualize a fundamental principle that resolves tension between adaptation and continuous evolution: phenotypic states encompassing adaptations traverse the continuous multi-layered landscape of past physical, developmental and functional associations among traits. The key concept that captures such traversing is network controllability - the ability to move a network from one state into another while maintaining its functionality (reflecting evolvability) and to efficiently propagate information or products through the network within a phenotypic state (maintaining its robustness). Here I suggest that transitions in network controllability - specifically in the topology of controls - help to explain how robustness and evolvability are balanced during evolution. I will focus on evolutionary transitions in degeneracy of metabolic networks - a ubiquitous property of phenotypic robustness where distinct pathways achieve the same end product - to suggest that associated changes in network controls is a common rule underlying phenomena as distinct as phenotypic plasticity, organismal accommodation of novelties, genetic assimilation, and macroevolutionary diversification. Capitalizing on well understood principles by which network structure translates into function of control nodes, I show that accumulating redundancy in one type of network controls inevitably leads to the emergence of another type of controls, forming evolutionary cycles of network controllability that, ultimately, reconcile local adaptation with continuity of evolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

From Design for Dominance to Design for Dialogue

ERIC Educational Resources Information Center

Keitges, Mark J.

2012-01-01

The increasing complexity of the network society is the result of a particular approach to design: that of mastery, control, ease of use and interconnectedness. The author analyzes this design approach for its negative and positive aspects, which he labels as "designing for dominance" and "designing for dialogue", respectively. Both of these…

F-15 IFCS Intelligent Flight Control System

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2008-01-01

This viewgraph presentation gives a detailed description of the F-15 aircraft, flight tests, aircraft performance and overall advanced neural network based flight control technologies for aerospace systems designs.

Challenges of CAC in Heterogeneous Wireless Cognitive Networks

NASA Astrophysics Data System (ADS)

Wang, Jiazheng; Fu, Xiuhua

Call admission control (CAC) is known as an effective functionality in ensuring the QoS of wireless networks. The vision of next generation wireless networks has led to the development of new call admission control (CAC) algorithms specifically designed for heterogeneous wireless Cognitive networks. However, there will be a number of challenges created by dynamic spectrum access and scheduling techniques associated with the cognitive systems. In this paper for the first time, we recommend that the CAC policies should be distinguished between primary users and secondary users. The classification of different methods of cac policies in cognitive networks contexts is proposed. Although there have been some researches within the umbrella of Joint CAC and cross-layer optimization for wireless networks, the advent of the cognitive networks adds some additional problems. We present the conceptual models for joint CAC and cross-layer optimization respectively. Also, the benefit of Cognition can only be realized fully if application requirements and traffic flow contexts are determined or inferred in order to know what modes of operation and spectrum bands to use at each point in time. The process model of Cognition involved per-flow-based CAC is presented. Because there may be a number of parameters on different levels affecting a CAC decision and the conditions for accepting or rejecting a call must be computed quickly and frequently, simplicity and practicability are particularly important for designing a feasible CAC algorithm. In a word, a more thorough understanding of CAC in heterogeneous wireless cognitive networks may help one to design better CAC algorithms.

Image sensor system with bio-inspired efficient coding and adaptation.

PubMed

Okuno, Hirotsugu; Yagi, Tetsuya

2012-08-01

We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

Onboard connectivity network for command-and-control aircraft

NASA Astrophysics Data System (ADS)

Artz, Timothy J.

1993-02-01

Command and control (C2) aircraft are host to an array of communications, information processing, and electronic control systems. The previous method of interconnecting this equipment involves point-to-point wiring harnesses between devices. A fiber optic broadband bus can be used to improve this situation by consolidating equipment connections on a shared medium. This network, known as the Onboard Connectivity Network (OCN), is being prototypes for application on the U.S. Government's Special Air Mission aircraft. Significant weight reduction and simplified future systems integration are the primary benefits of the OCN. The OCN design integrates voice, data, control, and video communications on a 3GHZ single mode fiber backbone. Communications within the aircraft use 500 MHz coaxial cable subnetworks connected to the backbone. The entire network is a dual redundant system for enhanced reliability. Node topologies are based on VMEbus to encourage use of commercial products and facilitate future evolution of the backbone topology. Network encryption technologies are being developed for OCN communications security. Automated workstations will be implemented to control and switch communications assets and to provide a technical control, test, and monitoring function.

Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer.

PubMed

Du, Jialu; Hu, Xin; Liu, Hongbo; Chen, C L Philip

2015-11-01

This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorporating the high-gain observer and radial basis function (RBF) neural networks in vectorial backstepping method. The high-gain observer provides the estimations of the ship position and heading as well as velocities. The RBF neural networks are employed to compensate for the uncertainties of ship dynamics. The adaptive laws incorporating a leakage term are designed to estimate the weights of RBF neural networks and the bounds of unknown time-variant environmental disturbances. In contrast to the existing results of dynamic positioning (DP) controllers, the proposed control scheme relies only on the ship position and heading measurements and does not require a priori knowledge of the ship dynamics and external disturbances. By means of Lyapunov functions, it is theoretically proved that our output feedback controller can control a ship's position and heading to the arbitrarily small neighborhood of the desired target values while guaranteeing that all signals in the closed-loop DP control system are uniformly ultimately bounded. Finally, simulations involving two ships are carried out, and simulation results demonstrate the effectiveness of the proposed control scheme.

Simulator design for advanced ISDN satellite design and experiments

NASA Technical Reports Server (NTRS)

Pepin, Gerald R.

1992-01-01

This simulation design task completion report documents the simulation techniques associated with the network models of both the Interim Service ISDN (integrated services digital network) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures. The ISIS network model design represents satellite systems like the Advanced Communication Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) program, moves all control and switching functions on-board the next generation ISDN communication satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete events simulation experiments will be performed with these models using various traffic scenarios, design parameters and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.

Local area network with fault-checking, priorities, and redundant backup

NASA Technical Reports Server (NTRS)

Morales, Sergio (Inventor); Friedman, Gary L. (Inventor)

1989-01-01

This invention is a redundant error detecting and correcting local area networked computer system having a plurality of nodes each including a network connector board within the node for connecting to an interfacing transceiver operably attached to a network cable. There is a first network cable disposed along a path to interconnect the nodes. The first network cable includes a plurality of first interfacing transceivers attached thereto. A second network cable is disposed in parallel with the first cable and, in like manner, includes a plurality of second interfacing transceivers attached thereto. There are a plurality of three position switches each having a signal input, three outputs for individual selective connection to the input, and a control input for receiving signals designating which of the outputs is to be connected to the signal input. Each of the switches includes means for designating a response address for responding to addressed signals appearing at the control input and each of the switches further has its signal input connected to a respective one of the input/output lines from the nodes. Also, one of the three outputs is connected to a repective one of the plurality of first interfacing transceivers. There is master switch control means having an output connected to the control inputs of the plurality of three position switches and an input for receiving directive signals for outputting addressed switch position signals to the three position switches as well as monitor and control computer means having a pair of network connector boards therein connected to respective ones of one of the first interfacing transceivers and one of the second interfacing transceivers and an output connected to the input of the master switch means for monitoring the status of the networked computer system by sending messages to the nodes and receiving and verifying messages therefrom and for sending control signals to the master switch to cause the master switch to cause respective ones of the nodes to use a desired one of the first and second cables for transmitting and receiving messages and for disconnecting desired ones of the nodes from both cables.

Drainpipe network management information system design based on GIS and SCADA technique

NASA Astrophysics Data System (ADS)

Gu, Ze-Yu; Zhao, De-An

2011-02-01

Achieving urban drainpipe network integration of geographical information system (GIS) and supervisory control and data acquisition (SCADA) technology is described in this paper. The system design's plans are put forward, which have realized GIS and SCADA system supplementary in the technology and strengthened the model visible analysis ability. It is verified by practical cases that the system has more practical values and a good prospect.

Establish a Data Transmission Platform of the Rig Based on the Distributed Network

NASA Astrophysics Data System (ADS)

Bao, Zefu; Li, Tao

In order to control in real-time ,closed-loop feedback the information, saving the money and labor,we distribute a platform of network data. It through the establishment of the platform in the oil drilling to achieve the easiest route of each device of the rig that conveying timely. The design proposed the platform to transfer networking data by PA which allows the rig control for optimal use. Against the idea,achieving first through on-site cabling and the establishment of data transmission module in the rig monitoring system. The results of standard field application show that the platform solve the problem of rig control.

Prediction-based association control scheme in dense femtocell networks.

PubMed

Sung, Nak Woon; Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system's effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective.

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Smart Collision Avoidance and Hazard Routing Mechanism for Intelligent Transport Network

NASA Astrophysics Data System (ADS)

Singh, Gurpreet; Gupta, Pooja; Wahab, Mohd Helmy Abd

2017-08-01

The smart vehicular ad-hoc network is the network that consists of vehicles for smooth movement and better management of the vehicular connectivity across the given network. This research paper aims to propose a set of solution for the VANETs consisting of the automatic driven vehicles, also called as the autonomous car. Such vehicular networks are always prone to collision due to the natural or un-natural reasons which must be solved before the large-scale deployment of the autonomous transport systems. The newly designed intelligent transport movement control mechanism is based upon the intelligent data propagation along with the vehicle collision and traffic jam prevention schema [8], which may help the future designs of smart cities to become more robust and less error-prone. In the proposed model, the focus is on designing a new dynamic and robust hazard routing protocol for intelligent vehicular networks for improvement of the overall performance in various aspects. It is expected to improve the overall transmission delay as well as the number of collisions or adversaries across the vehicular network zone.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Energy Efficient, Cross-Layer Enabled, Dynamic Aggregation Networks for Next Generation Internet

NASA Astrophysics Data System (ADS)

Wang, Michael S.

Today, the Internet traffic is growing at a near exponential rate, driven predominately by data center-based applications and Internet-of-Things services. This fast-paced growth in Internet traffic calls into question the ability of the existing optical network infrastructure to support this continued growth. The overall optical networking equipment efficiency has not been able to keep up with the traffic growth, creating a energy gap that makes energy and cost expenditures scale linearly with the traffic growth. The implication of this energy gap is that it is infeasible to continue using existing networking equipment to meet the growing bandwidth demand. A redesign of the optical networking platform is needed. The focus of this dissertation is on the design and implementation of energy efficient, cross-layer enabled, dynamic optical networking platforms, which is a promising approach to address the exponentially growing Internet bandwidth demand. Chapter 1 explains the motivation for this work by detailing the huge Internet traffic growth and the unsustainable energy growth of today's networking equipment. Chapter 2 describes the challenges and objectives of enabling agile, dynamic optical networking platforms and the vision of the Center for Integrated Access Networks (CIAN) to realize these objectives; the research objectives of this dissertation and the large body of related work in this field is also summarized. Chapter 3 details the design and implementation of dynamic networking platforms that support wavelength switching granularity. The main contribution of this work involves the experimental validation of deep cross-layer communication across the optical performance monitoring (OPM), data, and control planes. The first experiment shows QoS-aware video streaming over a metro-scale test-bed through optical power monitoring of the transmission wavelength and cross-layer feedback control of the power level. The second experiment extends the performance monitoring capabilities to include real-time monitoring of OSNR and polarization mode dispersion (PMD) to enable dynamic wavelength switching and selective restoration. Chapter 4 explains the author?s contributions in designing dynamic networking at the sub-wavelength switching granularity, which can provide greater network efficiency due to its finer granularity. To support dynamic switching, regeneration, adding/dropping, and control decisions on each individual packet, the cross-layer enabled node architecture is enhanced with a FPGA controller that brings much more precise timing and control to the switching, OPM, and control planes. Furthermore, QoS-aware packet protection and dynamic switching, dropping, and regeneration functionalities were experimentally demonstrated in a multi-node network. Chapter 5 describes a technique to perform optical grooming, a process of optically combining multiple incoming data streams into a single data stream, which can simultaneously achieve greater bandwidth utilization and increased spectral efficiency. In addition, an experimental demonstration highlighting a fully functioning multi-node, agile optical networking platform is detailed. Finally, a summary and discussion of future work is provided in Chapter 6. The future of the Internet is very exciting, filled with not-yet-invented applications and services driven by cloud computing and Internet-of-Things. The author is cautiously optimistic that agile, dynamically reconfigurable optical networking is the solution to realizing this future.

Automated and comprehensive link engineering supporting branched, ring, and mesh network topologies

NASA Astrophysics Data System (ADS)

Farina, J.; Khomchenko, D.; Yevseyenko, D.; Meester, J.; Richter, A.

2016-02-01

Link design, while relatively easy in the past, can become quite cumbersome with complex channel plans and equipment configurations. The task of designing optical transport systems and selecting equipment is often performed by an applications or sales engineer using simple tools, such as custom Excel spreadsheets. Eventually, every individual has their own version of the spreadsheet as well as their own methodology for building the network. This approach becomes unmanageable very quickly and leads to mistakes, bending of the engineering rules and installations that do not perform as expected. We demonstrate a comprehensive planning environment, which offers an efficient approach to unify, control and expedite the design process by controlling libraries of equipment and engineering methodologies, automating the process and providing the analysis tools necessary to predict system performance throughout the system and for all channels. In addition to the placement of EDFAs and DCEs, performance analysis metrics are provided at every step of the way. Metrics that can be tracked include power, CD and OSNR, SPM, XPM, FWM and SBS. Automated routine steps assist in design aspects such as equalization, padding and gain setting for EDFAs, the placement of ROADMs and transceivers, and creating regeneration points. DWDM networks consisting of a large number of nodes and repeater huts, interconnected in linear, branched, mesh and ring network topologies, can be designed much faster when compared with conventional design methods. Using flexible templates for all major optical components, our technology-agnostic planning approach supports the constant advances in optical communications.

A Process Management System for Networked Manufacturing

NASA Astrophysics Data System (ADS)

Liu, Tingting; Wang, Huifen; Liu, Linyan

With the development of computer, communication and network, networked manufacturing has become one of the main manufacturing paradigms in the 21st century. Under the networked manufacturing environment, there exist a large number of cooperative tasks susceptible to alterations, conflicts caused by resources and problems of cost and quality. This increases the complexity of administration. Process management is a technology used to design, enact, control, and analyze networked manufacturing processes. It supports efficient execution, effective management, conflict resolution, cost containment and quality control. In this paper we propose an integrated process management system for networked manufacturing. Requirements of process management are analyzed and architecture of the system is presented. And a process model considering process cost and quality is developed. Finally a case study is provided to explain how the system runs efficiently.

Experimental demonstration of software defined data center optical networks with Tbps end-to-end tunability

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Zhang, Jie; Ji, Yuefeng; Li, Hui; Wang, Huitao; Ge, Chao

2015-10-01

The end-to-end tunability is important to provision elastic channel for the burst traffic of data center optical networks. Then, how to complete the end-to-end tunability based on elastic optical networks? Software defined networking (SDN) based end-to-end tunability solution is proposed for software defined data center optical networks, and the protocol extension and implementation procedure are designed accordingly. For the first time, the flexible grid all optical networks with Tbps end-to-end tunable transport and switch system have been online demonstrated for data center interconnection, which are controlled by OpenDayLight (ODL) based controller. The performance of the end-to-end tunable transport and switch system has been evaluated with wavelength number tuning, bit rate tuning, and transmit power tuning procedure.

Synthetic gene circuits for metabolic control: design trade-offs and constraints

PubMed Central

Oyarzún, Diego A.; Stan, Guy-Bart V.

2013-01-01

A grand challenge in synthetic biology is to push the design of biomolecular circuits from purely genetic constructs towards systems that interface different levels of the cellular machinery, including signalling networks and metabolic pathways. In this paper, we focus on a genetic circuit for feedback regulation of unbranched metabolic pathways. The objective of this feedback system is to dampen the effect of flux perturbations caused by changes in cellular demands or by engineered pathways consuming metabolic intermediates. We consider a mathematical model for a control circuit with an operon architecture, whereby the expression of all pathway enzymes is transcriptionally repressed by the metabolic product. We address the existence and stability of the steady state, the dynamic response of the network under perturbations, and their dependence on common tuneable knobs such as the promoter characteristic and ribosome binding site (RBS) strengths. Our analysis reveals trade-offs between the steady state of the enzymes and the intermediates, together with a separation principle between promoter and RBS design. We show that enzymatic saturation imposes limits on the parameter design space, which must be satisfied to prevent metabolite accumulation and guarantee the stability of the network. The use of promoters with a broad dynamic range and a small leaky expression enlarges the design space. Simulation results with realistic parameter values also suggest that the control circuit can effectively upregulate enzyme production to compensate flux perturbations. PMID:23054953

Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

NASA Astrophysics Data System (ADS)

Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

2018-06-01

This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

I/O impedance controller

DOEpatents

Ruesch, Rodney; Jenkins, Philip N.; Ma, Nan

2004-03-09

There is disclosed apparatus and apparatus for impedance control to provide for controlling the impedance of a communication circuit using an all-digital impedance control circuit wherein one or more control bits are used to tune the output impedance. In one example embodiment, the impedance control circuit is fabricated using circuit components found in a standard macro library of a computer aided design system. According to another example embodiment, there is provided a control for an output driver on an integrated circuit ("IC") device to provide for forming a resistor divider network with the output driver and a resistor off the IC device so that the divider network produces an output voltage, comparing the output voltage of the divider network with a reference voltage, and adjusting the output impedance of the output driver to attempt to match the output voltage of the divider network and the reference voltage. Also disclosed is over-sampling the divider network voltage, storing the results of the over sampling, repeating the over-sampling and storing, averaging the results of multiple over sampling operations, controlling the impedance with a plurality of bits forming a word, and updating the value of the word by only one least significant bit at a time.

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

PubMed

Fon, Warren; Matheny, Matthew H; Li, Jarvis; Krayzman, Lev; Cross, Michael C; D'Souza, Raissa M; Crutchfield, James P; Roukes, Michael L

2017-10-11

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

Attack-tolerant networked control system: an approach for detection the controller stealthy hijacking attack

NASA Astrophysics Data System (ADS)

Atta Yaseen, Amer; Bayart, Mireille

2017-01-01

In this work, a new approach will be introduced as a development for the attack-tolerant scheme in the Networked Control System (NCS). The objective is to be able to detect an attack such as the Stuxnet case where the controller is reprogrammed and hijacked. Besides the ability to detect the stealthy controller hijacking attack, the advantage of this approach is that there is no need for a priori mathematical model of the controller. In order to implement the proposed scheme, a specific detector for the controller hijacking attack is designed. The performance of this scheme is evaluated be connected the detector to NCS with basic security elements such as Data Encryption Standard (DES), Message Digest (MD5), and timestamp. The detector is tested along with networked PI controller under stealthy hijacking attack. The test results of the proposed method show that the hijacked controller can be significantly detected and recovered.

Modeling and simulation of permanent magnet synchronous motor based on neural network control strategy

NASA Astrophysics Data System (ADS)

Luo, Bingyang; Chi, Shangjie; Fang, Man; Li, Mengchao

2017-03-01

Permanent magnet synchronous motor is used widely in industry, the performance requirements wouldn't be met by adopting traditional PID control in some of the occasions with high requirements. In this paper, a hybrid control strategy - nonlinear neural network PID and traditional PID parallel control are adopted. The high stability and reliability of traditional PID was combined with the strong adaptive ability and robustness of neural network. The permanent magnet synchronous motor will get better control performance when switch different working modes according to different controlled object conditions. As the results showed, the speed response adopting the composite control strategy in this paper was faster than the single control strategy. And in the case of sudden disturbance, the recovery time adopting the composite control strategy designed in this paper was shorter, the recovery ability and the robustness were stronger.

Hybrid function projective synchronization in complex dynamical networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; Hu, Xiao-peng

2014-02-15

This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

Kennedy Space Center network documentation system

NASA Technical Reports Server (NTRS)

Lohne, William E.; Schuerger, Charles L.

1995-01-01

The Kennedy Space Center Network Documentation System (KSC NDS) is being designed and implemented by NASA and the KSC contractor organizations to provide a means of network tracking, configuration, and control. Currently, a variety of host and client platforms are in use as a result of each organization having established its own network documentation system. The solution is to incorporate as many existing 'systems' as possible in the effort to consolidate and standardize KSC-wide documentation.

Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems

PubMed Central

Martins, Goncalo; Moondra, Arul; Dubey, Abhishek; Bhattacharjee, Anirban; Koutsoukos, Xenofon D.

2016-01-01

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems. PMID:27463718

Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems.

PubMed

Martins, Goncalo; Moondra, Arul; Dubey, Abhishek; Bhattacharjee, Anirban; Koutsoukos, Xenofon D

2016-07-25

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems.

Networked control of microgrid system of systems

NASA Astrophysics Data System (ADS)

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.

A Novel Design of an Automatic Lighting Control System for a Wireless Sensor Network with Increased Sensor Lifetime and Reduced Sensor Numbers

PubMed Central

Mohamaddoust, Reza; Haghighat, Abolfazl Toroghi; Sharif, Mohamad Javad Motahari; Capanni, Niccolo

2011-01-01

Wireless sensor networks (WSN) are currently being applied to energy conservation applications such as light control. We propose a design for such a system called a Lighting Automatic Control System (LACS). The LACS system contains a centralized or distributed architecture determined by application requirements and space usage. The system optimizes the calculations and communications for lighting intensity, incorporates user illumination requirements according to their activities and performs adjustments based on external lighting effects in external sensor and external sensor-less architectures. Methods are proposed for reducing the number of sensors required and increasing the lifetime of those used, for considerably reduced energy consumption. Additionally we suggest methods for improving uniformity of illuminance distribution on a workplane’s surface, which improves user satisfaction. Finally simulation results are presented to verify the effectiveness of our design. PMID:22164114

A novel design of an automatic lighting control system for a wireless sensor network with increased sensor lifetime and reduced sensor numbers.

PubMed

Mohamaddoust, Reza; Haghighat, Abolfazl Toroghi; Sharif, Mohamad Javad Motahari; Capanni, Niccolo

2011-01-01

Wireless sensor networks (WSN) are currently being applied to energy conservation applications such as light control. We propose a design for such a system called a lighting automatic control system (LACS). The LACS system contains a centralized or distributed architecture determined by application requirements and space usage. The system optimizes the calculations and communications for lighting intensity, incorporates user illumination requirements according to their activities and performs adjustments based on external lighting effects in external sensor and external sensor-less architectures. Methods are proposed for reducing the number of sensors required and increasing the lifetime of those used, for considerably reduced energy consumption. Additionally we suggest methods for improving uniformity of illuminance distribution on a workplane's surface, which improves user satisfaction. Finally simulation results are presented to verify the effectiveness of our design.

Cyber-Defense Return on Investment for NAVFAC Energy Technologies

DTIC Science & Technology

2017-12-01

Stakeholder input is important to properly develop a tool that reflects the legitimate concerns of those who routinely design , operate, and use control ...cybersecurity results with no control system network connectivity at all. Both are extreme scenarios, unless electrical engineers can design a...support of a Department of Defense (DOD) effort to improve cyber- security in relation to DOD installation control systems. Space and Naval Warfare

Neural network based adaptive control for nonlinear dynamic regimes

NASA Astrophysics Data System (ADS)

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.

Design of the smart home system based on the optimal routing algorithm and ZigBee network.

PubMed

Jiang, Dengying; Yu, Ling; Wang, Fei; Xie, Xiaoxia; Yu, Yongsheng

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system.

Finite-time mixed outer synchronization of complex networks with coupling time-varying delay.

PubMed

He, Ping; Ma, Shu-Hua; Fan, Tao

2012-12-01

This article is concerned with the problem of finite-time mixed outer synchronization (FMOS) of complex networks with coupling time-varying delay. FMOS is a recently developed generalized synchronization concept, i.e., in which different state variables of the corresponding nodes can evolve into finite-time complete synchronization, finite-time anti-synchronization, and even amplitude finite-time death simultaneously for an appropriate choice of the controller gain matrix. Some novel stability criteria for the synchronization between drive and response complex networks with coupling time-varying delay are derived using the Lyapunov stability theory and linear matrix inequalities. And a simple linear state feedback synchronization controller is designed as a result. Numerical simulations for two coupled networks of modified Chua's circuits are then provided to demonstrate the effectiveness and feasibility of the proposed complex networks control and synchronization schemes and then compared with the proposed results and the previous schemes for accuracy.

Design of the smart home system based on the optimal routing algorithm and ZigBee network

PubMed Central

Xie, Xiaoxia

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system. PMID:29131868

Experiments in Neural-Network Control of a Free-Flying Space Robot

NASA Technical Reports Server (NTRS)

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

Leveraging contact network structure in the design of cluster randomized trials.

PubMed

Harling, Guy; Wang, Rui; Onnela, Jukka-Pekka; De Gruttola, Victor

2017-02-01

In settings like the Ebola epidemic, where proof-of-principle trials have provided evidence of efficacy but questions remain about the effectiveness of different possible modes of implementation, it may be useful to conduct trials that not only generate information about intervention effects but also themselves provide public health benefit. Cluster randomized trials are of particular value for infectious disease prevention research by virtue of their ability to capture both direct and indirect effects of intervention, the latter of which depends heavily on the nature of contact networks within and across clusters. By leveraging information about these networks-in particular the degree of connection across randomized units, which can be obtained at study baseline-we propose a novel class of connectivity-informed cluster trial designs that aim both to improve public health impact (speed of epidemic control) and to preserve the ability to detect intervention effects. We several designs for cluster randomized trials with staggered enrollment, in each of which the order of enrollment is based on the total number of ties (contacts) from individuals within a cluster to individuals in other clusters. Our designs can accommodate connectivity based either on the total number of external connections at baseline or on connections only to areas yet to receive the intervention. We further consider a "holdback" version of the designs in which control clusters are held back from re-randomization for some time interval. We investigate the performance of these designs in terms of epidemic control outcomes (time to end of epidemic and cumulative incidence) and power to detect intervention effect, by simulating vaccination trials during an SEIR-type epidemic outbreak using a network-structured agent-based model. We compare results to those of a traditional Stepped Wedge trial. In our simulation studies, connectivity-informed designs lead to a 20% reduction in cumulative incidence compared to comparable traditional study designs, but have little impact on epidemic length. Power to detect intervention effect is reduced in all connectivity-informed designs, but "holdback" versions provide power that is very close to that of a traditional Stepped Wedge approach. Incorporating information about cluster connectivity in the design of cluster randomized trials can increase their public health impact, especially in acute outbreak settings. Using this information helps control outbreaks-by minimizing the number of cross-cluster infections-with very modest cost in terms of power to detect effectiveness.

H∞ output tracking control of discrete-time nonlinear systems via standard neural network models.

PubMed

Liu, Meiqin; Zhang, Senlin; Chen, Haiyang; Sheng, Weihua

2014-10-01

This brief proposes an output tracking control for a class of discrete-time nonlinear systems with disturbances. A standard neural network model is used to represent discrete-time nonlinear systems whose nonlinearity satisfies the sector conditions. H∞ control performance for the closed-loop system including the standard neural network model, the reference model, and state feedback controller is analyzed using Lyapunov-Krasovskii stability theorem and linear matrix inequality (LMI) approach. The H∞ controller, of which the parameters are obtained by solving LMIs, guarantees that the output of the closed-loop system closely tracks the output of a given reference model well, and reduces the influence of disturbances on the tracking error. Three numerical examples are provided to show the effectiveness of the proposed H∞ output tracking design approach.

Numerical design and optimization of hydraulic resistance and wall shear stress inside pressure-driven microfluidic networks.

PubMed

Damiri, Hazem Salim; Bardaweel, Hamzeh Khalid

2015-11-07

Microfluidic networks represent the milestone of microfluidic devices. Recent advancements in microfluidic technologies mandate complex designs where both hydraulic resistance and pressure drop across the microfluidic network are minimized, while wall shear stress is precisely mapped throughout the network. In this work, a combination of theoretical and modeling techniques is used to construct a microfluidic network that operates under minimum hydraulic resistance and minimum pressure drop while constraining wall shear stress throughout the network. The results show that in order to minimize the hydraulic resistance and pressure drop throughout the network while maintaining constant wall shear stress throughout the network, geometric and shape conditions related to the compactness and aspect ratio of the parent and daughter branches must be followed. Also, results suggest that while a "local" minimum hydraulic resistance can be achieved for a geometry with an arbitrary aspect ratio, a "global" minimum hydraulic resistance occurs only when the aspect ratio of that geometry is set to unity. Thus, it is concluded that square and equilateral triangular cross-sectional area microfluidic networks have the least resistance compared to all rectangular and isosceles triangular cross-sectional microfluidic networks, respectively. Precise control over wall shear stress through the bifurcations of the microfluidic network is demonstrated in this work. Three multi-generation microfluidic network designs are considered. In these three designs, wall shear stress in the microfluidic network is successfully kept constant, increased in the daughter-branch direction, or decreased in the daughter-branch direction, respectively. For the multi-generation microfluidic network with constant wall shear stress, the design guidelines presented in this work result in identical profiles of wall shear stresses not only within a single generation but also through all the generations of the microfluidic network under investigation. The results obtained in this work are consistent with previously reported data and suitable for a wide range of lab-on-chip applications.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model

PubMed Central

2013-01-01

Background High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. Methods/Design A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants’ online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Discussion Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. Trial registration ClinicalTrials.gov NCT01142804 PMID:23945138

Control and communication co-design: analysis and practice on performance improvement in distributed measurement and control system based on fieldbus and Ethernet.

PubMed

Liang, Geng

2015-01-01

In this paper, improving control performance of a networked control system by reducing DTD in a different perspective was investigated. Two different network architectures for system implementation were presented. Analysis and improvement dealing with DTD for the experimental control system were expounded. Effects of control scheme configuration on DTD in the form of FB were investigated and corresponding improvements by reallocation of FB and re-arrangement of schedule table are proposed. Issues of DTD in hybrid network were investigated and corresponding approaches to improve performance including (1) reducing DTD in PLC or PAC by way of IEC61499 and (2) cascade Smith predictive control with BPNN-based identification were proposed and investigated. Control effects under the proposed methodologies were also given. Experimental and field practices validated these methodologies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Synchronization of hybrid coupled reaction-diffusion neural networks with time delays via generalized intermittent control with spacial sampled-data.

PubMed

Lu, Binglong; Jiang, Haijun; Hu, Cheng; Abdurahman, Abdujelil

2018-05-04

The exponential synchronization of hybrid coupled reaction-diffusion neural networks with time delays is discussed in this article. At first, a generalized intermittent control with spacial sampled-data is introduced, which is intermittent in time and data sampling in space. This type of control strategy not only can unify the traditional periodic intermittent control and the aperiodic case, but also can lower the update rate of the controller in both temporal and spatial domains. Next, based on the designed control protocol and the Lyapunov-Krasovskii functional approach, some novel and readily verified criteria are established to guarantee the exponential synchronization of the considered networks. These criteria depend on the diffusion coefficients, coupled strengths, time delays as well as control parameters. Finally, the effectiveness of the proposed control strategy is shown by a numerical example. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.

PubMed

Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min

2014-01-01

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

Acute pharmacologically induced shifts in serotonin availability abolish emotion-selective responses to negative face emotions in distinct brain networks.

PubMed

Grady, Cheryl L; Siebner, Hartwig R; Hornboll, Bettina; Macoveanu, Julian; Paulson, Olaf B; Knudsen, Gitte M

2013-05-01

Pharmacological manipulation of serotonin availability can alter the processing of facial expressions of emotion. Using a within-subject design, we measured the effect of serotonin on the brain's response to aversive face emotions with functional MRI while 20 participants judged the gender of neutral, fearful and angry faces. In three separate and counterbalanced sessions, participants received citalopram (CIT) to raise serotonin levels, underwent acute tryptophan depletion (ATD) to lower serotonin, or were studied without pharmacological challenge (Control). An analysis designed to identify distributed brain responses identified two brain networks with modulations of activity related to face emotion and serotonin level. The first network included the left amygdala, bilateral striatum, and fusiform gyri. During the Control session this network responded only to fearful faces; increasing serotonin decreased this response to fear, whereas reducing serotonin enhanced the response of this network to angry faces. The second network involved bilateral amygdala and ventrolateral prefrontal cortex, and these regions also showed increased activity to fear during the Control session. Both drug challenges enhanced the neural response of this set of regions to angry faces, relative to Control, and CIT also enhanced activity for neutral faces. The net effect of these changes in both networks was to abolish the selective response to fearful expressions. These results suggest that a normal level of serotonin is critical for maintaining a differentiated brain response to threatening face emotions. Lower serotonin leads to a broadening of a normally fear-specific response to anger, and higher levels reduce the differentiated brain response to aversive face emotions. Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.

Design of fuzzy systems using neurofuzzy networks.

PubMed

Figueiredo, M; Gomide, F

1999-01-01

This paper introduces a systematic approach for fuzzy system design based on a class of neural fuzzy networks built upon a general neuron model. The network structure is such that it encodes the knowledge learned in the form of if-then fuzzy rules and processes data following fuzzy reasoning principles. The technique provides a mechanism to obtain rules covering the whole input/output space as well as the membership functions (including their shapes) for each input variable. Such characteristics are of utmost importance in fuzzy systems design and application. In addition, after learning, it is very simple to extract fuzzy rules in the linguistic form. The network has universal approximation capability, a property very useful in, e.g., modeling and control applications. Here we focus on function approximation problems as a vehicle to illustrate its usefulness and to evaluate its performance. Comparisons with alternative approaches are also included. Both, nonnoisy and noisy data have been studied and considered in the computational experiments. The neural fuzzy network developed here and, consequently, the underlying approach, has shown to provide good results from the accuracy, complexity, and system design points of view.

A computer tool to support in design of industrial Ethernet.

PubMed

Lugli, Alexandre Baratella; Santos, Max Mauro Dias; Franco, Lucia Regina Horta Rodrigues

2009-04-01

This paper presents a computer tool to support in the project and development of an industrial Ethernet network, verifying the physical layer (cables-resistance and capacitance, scan time, network power supply-POE's concept "Power Over Ethernet" and wireless), and occupation rate (amount of information transmitted to the network versus the controller network scan time). These functions are accomplished without a single physical element installed in the network, using only simulation. The computer tool has a software that presents a detailed vision of the network to the user, besides showing some possible problems in the network, and having an extremely friendly environment.

Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)—A Survey

PubMed Central

Karuppiah Ramachandran, Vignesh Raja; Ayele, Eyuel D.; Meratnia, Nirvana; Havinga, Paul J. M.

2016-01-01

With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close as possible to the source, these implantable devices are able to save lives. A wireless link between medical sensors and implantable medical devices is essential in the case of closed-loop medical devices, in which symptoms of the diseases are monitored by sensors that are not placed in close proximity of the therapeutic device. Medium Access Control (MAC) is crucial to make it possible for several medical devices to communicate using a shared wireless medium in such a way that minimum delay, maximum throughput, and increased network life-time are guaranteed. To guarantee this Quality of Service (QoS), the MAC protocols control the main sources of limited resource wastage, namely the idle-listening, packet collisions, over-hearing, and packet loss. Traditional MAC protocols designed for body sensor networks are not directly applicable to Implantable Body Sensor Networks (IBSN) because of the dynamic nature of the radio channel within the human body and the strict QoS requirements of IBSN applications. Although numerous MAC protocols are available in the literature, the majority of them are designed for Body Sensor Network (BSN) and Wireless Sensor Network (WSN). To the best of our knowledge, there is so far no research paper that explores the impact of these MAC protocols specifically for IBSN. MAC protocols designed for implantable devices are still in their infancy and one of their most challenging objectives is to be ultra-low-power. One of the technological solutions to achieve this objective so is to integrate the concept of Wake-up radio (WuR) into the MAC design. In this survey, we present a taxonomy of MAC protocols based on their use of WuR technology and identify their bottlenecks to be used in IBSN applications. Furthermore, we present a number of open research challenges and requirements for designing an energy-efficient and reliable wireless communication protocol for IBSN. PMID:27916822

Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)-A Survey.

PubMed

Karuppiah Ramachandran, Vignesh Raja; Ayele, Eyuel D; Meratnia, Nirvana; Havinga, Paul J M

2016-11-29

With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close as possible to the source, these implantable devices are able to save lives. A wireless link between medical sensors and implantable medical devices is essential in the case of closed-loop medical devices, in which symptoms of the diseases are monitored by sensors that are not placed in close proximity of the therapeutic device. Medium Access Control (MAC) is crucial to make it possible for several medical devices to communicate using a shared wireless medium in such a way that minimum delay, maximum throughput, and increased network life-time are guaranteed. To guarantee this Quality of Service (QoS), the MAC protocols control the main sources of limited resource wastage, namely the idle-listening, packet collisions, over-hearing, and packet loss. Traditional MAC protocols designed for body sensor networks are not directly applicable to Implantable Body Sensor Networks (IBSN) because of the dynamic nature of the radio channel within the human body and the strict QoS requirements of IBSN applications. Although numerous MAC protocols are available in the literature, the majority of them are designed for Body Sensor Network (BSN) and Wireless Sensor Network (WSN). To the best of our knowledge, there is so far no research paper that explores the impact of these MAC protocols specifically for IBSN. MAC protocols designed for implantable devices are still in their infancy and one of their most challenging objectives is to be ultra-low-power. One of the technological solutions to achieve this objective so is to integrate the concept of Wake-up radio (WuR) into the MAC design. In this survey, we present a taxonomy of MAC protocols based on their use of WuR technology and identify their bottlenecks to be used in IBSN applications. Furthermore, we present a number of open research challenges and requirements for designing an energy-efficient and reliable wireless communication protocol for IBSN.

Neural computing thermal comfort index PMV for the indoor environment intelligent control system

NASA Astrophysics Data System (ADS)

Liu, Chang; Chen, Yifei

2013-03-01

Providing indoor thermal comfort and saving energy are two main goals of indoor environmental control system. An intelligent comfort control system by combining the intelligent control and minimum power control strategies for the indoor environment is presented in this paper. In the system, for realizing the comfort control, the predicted mean vote (PMV) is designed as the control goal, and with chastening formulas of PMV, it is controlled to optimize for improving indoor comfort lever by considering six comfort related variables. On the other hand, a RBF neural network based on genetic algorithm is designed to calculate PMV for better performance and overcoming the nonlinear feature of the PMV calculation better. The formulas given in the paper are presented for calculating the expected output values basing on the input samples, and the RBF network model is trained depending on input samples and the expected output values. The simulation result is proved that the design of the intelligent calculation method is valid. Moreover, this method has a lot of advancements such as high precision, fast dynamic response and good system performance are reached, it can be used in practice with requested calculating error.

Consensus positive position feedback control for vibration attenuation of smart structures

NASA Astrophysics Data System (ADS)

Omidi, Ehsan; Nima Mahmoodi, S.

2015-04-01

This paper presents a new network-based approach for active vibration control in smart structures. In this approach, a network with known topology connects collocated actuator/sensor elements of the smart structure to one another. Each of these actuators/sensors, i.e., agent or node, is enhanced by a separate multi-mode positive position feedback (PPF) controller. The decentralized PPF controlled agents collaborate with each other in the designed network, under a certain consensus dynamics. The consensus constraint forces neighboring agents to cooperate with each other such that the disagreement between the time-domain actuation of the agents is driven to zero. The controller output of each agent is calculated using state-space variables; hence, optimal state estimators are designed first for the proposed observer-based consensus PPF control. The consensus controller is numerically investigated for a flexible smart structure, i.e., a thin aluminum beam that is clamped at its both ends. Results demonstrate that the consensus law successfully imposes synchronization between the independently controlled agents, as the disagreements between the decentralized PPF controller variables converge to zero in a short time. The new consensus PPF controller brings extra robustness to vibration suppression in smart structures, where malfunctions of an agent can be compensated for by referencing the neighboring agents’ performance. This is demonstrated in the results by comparing the new controller with former centralized PPF approach.

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

PubMed

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.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control

PubMed Central

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

2018-01-01

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. PMID:29320466

The Technology of Suppressing Harmonics with Complex Neural Network is Applied to Microgrid

NASA Astrophysics Data System (ADS)

Zhang, Jing; Li, Zhan-Ying; Wang, Yan-ping; Li, Yang; Zong, Ke-yong

2018-03-01

According to the traits of harmonics in microgrid, a new CANN controller which combines BP and RBF neural network is proposed to control APF to detect and suppress harmonics. This controller has the function of current prediction. By simulation in Matlab / Simulink, this design can shorten the delay time nearly 0.02s (a power supply current cycle) in comparison with the traditional controller based on ip-iq method. The new controller also has higher compensation accuracy and better dynamic tracking traits, it can greatly suppress the harmonics and improve the power quality.

Performance, implementation and network management techniques for a European CDMA-based land-mobile satellite system

NASA Astrophysics Data System (ADS)

Arenaccio, S.; Vernucci, A.; Padovani, R.; Arcidiacono, A.

Results of a detailed comparative performance assessment between two candidate access solutions for the provision of land-mobile services, i.e., FDMA and CDMA, for the European Land-Mobile Satellite Services (LMSS) provision are presented. The design of the CDMA access system and the network architecture, system procedures, network control, operation in fading environments, and implementation aspects of the system are described. The CDMA system is shown to yield superior traffic capability, despite the absence of polarization reuse due to payload design, especially in the second-generation era (multiple spot-beams). In this case, the advantage was found to be largely dependent on the traffic distribution across spot beams. Power control techniques are proposed to cope with the geographical disadvantage suffered by mobile stations located at the beam borders to compensate for fadings.

Temporal Heterogeneity and the Value of Slowness in Robotic Systems

DTIC Science & Technology

2015-11-01

DIMENSIONS OF HETEROGENEITY By now, we have become reasonably good at designing distributed control strategies for teams of networked agents in order...possible is the recent emergence of a relatively mature theory of how to coordinate control decisions across teams of networked agents. In fact...Loris, illustrated in Figure 2. Figure 2: Slow mammals that serve as bio-inspiration for SlowBot Behavior [Wikipedia] Top: Tree

Second-Order Consensus in Multiagent Systems via Distributed Sliding Mode Control.

PubMed

Yu, Wenwu; Wang, He; Cheng, Fei; Yu, Xinghuo; Wen, Guanghui

2016-11-22

In this paper, the new decoupled distributed sliding-mode control (DSMC) is first proposed for second-order consensus in multiagent systems, which finally solves the fundamental unknown problem for sliding-mode control (SMC) design of coupled networked systems. A distributed full-order sliding-mode surface is designed based on the homogeneity with dilation for reaching second-order consensus in multiagent systems, under which the sliding-mode states are decoupled. Then, the SMC is applied to the decoupled sliding-mode states to reach their origin in finite time, which is the sliding-mode surface. The states of agents can first reach the designed sliding-mode surface in finite time and then move to the second-order consensus state along the surface in finite time as well. The DSMC designed in this paper can eliminate the influence of singularity problems and weaken the influence of chattering, which is still very difficult in the SMC systems. In addition, DSMC proposes a general decoupling framework for designing SMC in networked multiagent systems. Simulations are presented to verify the theoretical results in this paper.

Cluster synchronization of community network with distributed time delays via impulsive control

NASA Astrophysics Data System (ADS)

Leng, Hui; Wu, Zhao-Yan

2016-11-01

Cluster synchronization is an important dynamical behavior in community networks and deserves further investigations. A community network with distributed time delays is investigated in this paper. For achieving cluster synchronization, an impulsive control scheme is introduced to design proper controllers and an adaptive strategy is adopted to make the impulsive controllers unified for different networks. Through taking advantage of the linear matrix inequality technique and constructing Lyapunov functions, some synchronization criteria with respect to the impulsive gains, instants, and system parameters without adaptive strategy are obtained and generalized to the adaptive case. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results. Project supported by the National Natural Science Foundation of China (Grant No. 61463022), the Natural Science Foundation of Jiangxi Province, China (Grant No. 20161BAB201021), and the Natural Science Foundation of Jiangxi Educational Committee, China (Grant No. GJJ14273).

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of topology on network evolution

NASA Astrophysics Data System (ADS)

Oikonomou, Panos; Cluzel, Philippe

2006-08-01

The ubiquity of scale-free topology in nature raises the question of whether this particular network design confers an evolutionary advantage. A series of studies has identified key principles controlling the growth and the dynamics of scale-free networks. Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems. Applying a training algorithm, we characterize how networks with distinct topologies evolve towards a pre-established target function through a process of random mutations and selection. We find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. Whereas homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously. Remarkably, this latter property is robust to variations of the degree exponent. In contrast, homogeneous random networks require a specific tuning of their connectivity to optimize their ability to evolve. These results highlight an organizing principle that governs the evolution of complex networks and that can improve the design of engineered systems.

Cyber situational awareness and differential hardening

NASA Astrophysics Data System (ADS)

Dwivedi, Anurag; Tebben, Dan

2012-06-01

The advent of cyber threats has created a need for a new network planning, design, architecture, operations, control, situational awareness, management, and maintenance paradigms. Primary considerations include the ability to assess cyber attack resiliency of the network, and rapidly detect, isolate, and operate during deliberate simultaneous attacks against the network nodes and links. Legacy network planning relied on automatic protection of a network in the event of a single fault or a very few simultaneous faults in mesh networks, but in the future it must be augmented to include improved network resiliency and vulnerability awareness to cyber attacks. Ability to design a resilient network requires the development of methods to define, and quantify the network resiliency to attacks, and to be able to develop new optimization strategies for maintaining operations in the midst of these newly emerging cyber threats. Ways to quantify resiliency, and its use in visualizing cyber vulnerability awareness and in identifying node or link criticality, are presented in the current work, as well as a methodology of differential network hardening based on the criticality profile of cyber network components.

NASA Integrated Network Monitor and Control Software Architecture

NASA Technical Reports Server (NTRS)

Shames, Peter; Anderson, Michael; Kowal, Steve; Levesque, Michael; Sindiy, Oleg; Donahue, Kenneth; Barnes, Patrick

2012-01-01

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation office (SCaN) has commissioned a series of trade studies to define a new architecture intended to integrate the three existing networks that it operates, the Deep Space Network (DSN), Space Network (SN), and Near Earth Network (NEN), into one integrated network that offers users a set of common, standardized, services and interfaces. The integrated monitor and control architecture utilizes common software and common operator interfaces that can be deployed at all three network elements. This software uses state-of-the-art concepts such as a pool of re-programmable equipment that acts like a configurable software radio, distributed hierarchical control, and centralized management of the whole SCaN integrated network. For this trade space study a model-based approach using SysML was adopted to describe and analyze several possible options for the integrated network monitor and control architecture. This model was used to refine the design and to drive the costing of the four different software options. This trade study modeled the three existing self standing network elements at point of departure, and then described how to integrate them using variations of new and existing monitor and control system components for the different proposed deployments under consideration. This paper will describe the trade space explored, the selected system architecture, the modeling and trade study methods, and some observations on useful approaches to implementing such model based trade space representation and analysis.

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-01-01

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power. PMID:24608008

Multiplex congruence network of natural numbers.

PubMed

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-31

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.

Multiplex congruence network of natural numbers

NASA Astrophysics Data System (ADS)

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-01

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Router Agent Technology for Policy-Based Network Management

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

2011-01-01

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

DoD Comprehensive Military Unmanned Aerial Vehicle Smart Device Ground Control Station Threat Model

DTIC Science & Technology

2015-04-01

design , imple- mentation, and test evaluation were interviewed to evaluate the existing gaps in the DoD processes for cybersecurity. This group exposed...such as antenna design and signal reception have made satellite communication networks a viable solution for smart devices on the battlefield...DoD Comprehensive Military Unmanned AERIAL VEHICLE SMART DEVICE GROUND CONTROL STATION THREAT MODEL  Image designed by Diane Fleischer Report

Social Networks of Lesbian, Gay, Bisexual, and Transgender Older Adults

PubMed Central

Erosheva, Elena A.; Kim, Hyun-Jun; Emlet, Charles; Fredriksen-Goldsen, Karen I.

2015-01-01

Purpose This study examines global social networks—including friendship, support, and acquaintance networks—of lesbian, gay, bisexual, and transgender (LGBT) older adults. Design and Methods Utilizing data from a large community-based study, we employ multiple regression analyses to examine correlates of social network size and diversity. Results Controlling for background characteristics, network size was positively associated with being female, transgender identity, employment, higher income, having a partner or a child, identity disclosure to a neighbor, engagement in religious activities, and service use. Controlling in addition for network size, network diversity was positively associated with younger age, being female, transgender identity, identity disclosure to a friend, religious activity, and service use. Implications According to social capital theory, social networks provide a vehicle for social resources that can be beneficial for successful aging and well-being. This study is a first step at understanding the correlates of social network size and diversity among LGBT older adults. PMID:25882129

Marketplace Plans With Narrow Physician Networks Feature Lower Monthly Premiums Than Plans With Larger Networks.

PubMed

Polsky, Daniel; Cidav, Zuleyha; Swanson, Ashley

2016-10-01

The introduction of health insurance Marketplaces under the Affordable Care Act has been associated with growth of restricted provider networks. The value of this plan design strategy, including its association with lower premiums, is uncertain. We used data from all silver plans offered in the 2014 health insurance exchanges in the fifty states and the District of Columbia to estimate the association between the breadth of a provider network and plan premiums. We found that within a market, for plans of otherwise equivalent design and controlling for issuer-specific pricing strategy, a plan with an extra-small network had a monthly premium that was 6.7 percent less expensive than that of a plan with a large network. Because narrow networks remain an important strategy available to insurance companies to offer lower-cost plans on health insurance Marketplaces, the success of health insurance coverage expansions may be tied to the successful implementation of narrow networks. Project HOPE—The People-to-People Health Foundation, Inc.

BIO-Plex Information System Concept

NASA Technical Reports Server (NTRS)

Jones, Harry; Boulanger, Richard; Arnold, James O. (Technical Monitor)

1999-01-01

This paper describes a suggested design for an integrated information system for the proposed BIO-Plex (Bioregenerative Planetary Life Support Systems Test Complex) at Johnson Space Center (JSC), including distributed control systems, central control, networks, database servers, personal computers and workstations, applications software, and external communications. The system will have an open commercial computing and networking, architecture. The network will provide automatic real-time transfer of information to database server computers which perform data collection and validation. This information system will support integrated, data sharing applications for everything, from system alarms to management summaries. Most existing complex process control systems have information gaps between the different real time subsystems, between these subsystems and central controller, between the central controller and system level planning and analysis application software, and between the system level applications and management overview reporting. An integrated information system is vitally necessary as the basis for the integration of planning, scheduling, modeling, monitoring, and control, which will allow improved monitoring and control based on timely, accurate and complete data. Data describing the system configuration and the real time processes can be collected, checked and reconciled, analyzed and stored in database servers that can be accessed by all applications. The required technology is available. The only opportunity to design a distributed, nonredundant, integrated system is before it is built. Retrofit is extremely difficult and costly.

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

PubMed Central

Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

2016-01-01

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design. PMID:26950129

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks.

PubMed

Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

2016-03-03

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

The Life-Changing Magic of Nonlinearity in Network Control

NASA Astrophysics Data System (ADS)

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.

Theory, Design, and Algorithms for Optimal Control of wireless Networks

DTIC Science & Technology

2010-06-09

The implementation of network-centric warfare technologies is an abiding, critical interest of Air Force Science and Technology efforts for the Warfighter. Wireless communications, strategic signaling are areas of critical Air Force Mission need. Autonomous networks of multiple, heterogeneous Throughput enhancement and robust connectivity in communications and sensor networks are critical factors in net-centric USAF operations. This research directly supports the Air Force vision of information dominance and the development of anywhere, anytime operational readiness.

Design Issues for Traffic Management for the ATM UBR + Service for TCP Over Satellite Networks

NASA Technical Reports Server (NTRS)

Jain, Raj

1999-01-01

This project was a comprehensive research program for developing techniques for improving the performance of Internet protocols over Asynchronous Transfer Mode (ATM) based satellite networks. Among the service categories provided by ATM networks, the most commonly used category for data traffic is the unspecified bit rate (UBR) service. UBR allows sources to send data into the network without any feedback control. The project resulted in the numerous ATM Forum contributions and papers.

Interfacing a high performance disk array file server to a Gigabit LAN

NASA Technical Reports Server (NTRS)

Seshan, Srinivasan; Katz, Randy H.

1993-01-01

Our previous prototype, RAID-1, identified several bottlenecks in typical file server architectures. The most important bottleneck was the lack of a high-bandwidth path between disk, memory, and the network. Workstation servers, such as the Sun-4/280, have very slow access to peripherals on busses far from the CPU. For the RAID-2 system, we addressed this problem by designing a crossbar interconnect, Xbus board, that provides a 40MB/s path between disk, memory, and the network interfaces. However, this interconnect does not provide the system CPU with low latency access to control the various interfaces. To provide a high data rate to clients on the network, we were forced to carefully and efficiently design the network software. A block diagram of the system hardware architecture is given. In the following subsections, we describe pieces of the RAID-2 file server hardware that had a significant impact on the design of the network interface.

Optical implementation of (3, 3, 2) regular rectangular CC-Banyan optical network

NASA Astrophysics Data System (ADS)

Yang, Junbo; Su, Xianyu

2007-07-01

CC-Banyan network plays an important role in the optical interconnection network. Based on previous reports of (2, 2, 3) the CC-Banyan network, another rectangular-Banyan network, i.e. (3, 3, 2) rectangular CC-Banyan network, has been discussed. First, according to its construction principle, the topological graph and the routing rule of (3, 3, 2) rectangular CC-Banyan network have been proposed. Then, the optically experimental setup of (3, 3, 2) rectangular CC-Banyan network has been designed and achieved. Each stage of node switch consists of phase spatial light modulator (PSLM) and polarizing beam-splitter (PBS), and fiber has been used to perform connection between adjacent stages. PBS features that s-component (perpendicular to the incident plane) of the incident light beam is reflected, and p-component (parallel to the incident plane) passes through it. According to switching logic, under the control of external electrical signals, PSLM functions to control routing paths of the signal beams, i.e. the polarization of each optical signal is rotated or not rotated 90° by a programmable PSLM. Finally, the discussion and analysis show that the experimental setup designed here can realize many functions such as optical signal switch and permutation. It has advantages of large number of input/output-ports, compact in structure, and low energy loss. Hence, the experimental setup can be used in optical communication and optical information processing.

A Smart City Application: A Fully Controlled Street Lighting Isle Based on Raspberry-Pi Card, a ZigBee Sensor Network and WiMAX

PubMed Central

Leccese, Fabio; Cagnetti, Marco; Trinca, Daniele

2014-01-01

A smart city application has been realized and tested. It is a fully remote controlled isle of lamp posts based on new technologies. It has been designed and organized in different hierarchical layers, which perform local activities to physically control the lamp posts and transmit information with another for remote control. Locally, each lamp post uses an electronic card for management and a ZigBee tlc network transmits data to a central control unit, which manages the whole isle. The central unit is realized with a Raspberry-Pi control card due to its good computing performance at very low price. Finally, a WiMAX connection was tested and used to remotely control the smart grid, thus overcoming the distance limitations of commercial Wi-Fi networks. The isle has been realized and tested for some months in the field. PMID:25529206

A smart city application: a fully controlled street lighting isle based on Raspberry-Pi card, a ZigBee sensor network and WiMAX.

PubMed

Leccese, Fabio; Cagnetti, Marco; Trinca, Daniele

2014-12-18

A smart city application has been realized and tested. It is a fully remote controlled isle of lamp posts based on new technologies. It has been designed and organized in different hierarchical layers, which perform local activities to physically control the lamp posts and transmit information with another for remote control. Locally, each lamp post uses an electronic card for management and a ZigBee tlc network transmits data to a central control unit, which manages the whole isle. The central unit is realized with a Raspberry-Pi control card due to its good computing performance at very low price. Finally, a WiMAX connection was tested and used to remotely control the smart grid, thus overcoming the distance limitations of commercial Wi-Fi networks. The isle has been realized and tested for some months in the field.

Direct heuristic dynamic programming for damping oscillations in a large power system.

PubMed

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

76 FR 36861 - Special Conditions: Gulfstream Model GVI Airplane; Electronic Systems Security Isolation or...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-23

... incorporate the following novel or unusual design features: Digital systems architecture composed of several connected networks. The proposed architecture and network configuration may be used for, or interfaced with... navigation systems (aircraft control domain), 2. Airline business and administrative support (airline...

Prediction-based association control scheme in dense femtocell networks

PubMed Central

Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

An Evaluation of optional timing/synchronization features to support selection of an optimum design for the DCS digital communication network

NASA Technical Reports Server (NTRS)

Bradley, D. B.; Cain, J. B., III; Williard, M. W.

1978-01-01

The task was to evaluate the ability of a set of timing/synchronization subsystem features to provide a set of desirable characteristics for the evolving Defense Communications System digital communications network. The set of features related to the approaches by which timing/synchronization information could be disseminated throughout the network and the manner in which this information could be utilized to provide a synchronized network. These features, which could be utilized in a large number of different combinations, included mutual control, directed control, double ended reference links, independence of clock error measurement and correction, phase reference combining, and self organizing.

Design development of a neural network-based telemetry monitor

NASA Technical Reports Server (NTRS)

Lembeck, Michael F.

1992-01-01

This paper identifies the requirements and describes an architectural framework for an artificial neural network-based system that is capable of fulfilling monitoring and control requirements of future aerospace missions. Incorporated into this framework are a newly developed training algorithm and the concept of cooperative network architectures. The feasibility of such an approach is demonstrated for its ability to identify faults in low frequency waveforms.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-05-30

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-01-01

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control. PMID:28556817

Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication

PubMed Central

Yan, Zheping; Xu, Da; Chen, Tao; Zhang, Wei; Liu, Yibo

2018-01-01

Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV sensor networks. Distributed leader-follower formation controllers are designed based on a state feedback and consensus algorithm. Considering that each vehicle is subject to model uncertainties and current disturbances, a second-order integral UUV model with a nonlinear function is established using the state feedback linearized method under current disturbances. For unstable communication among UUVs, communication failure and acoustic link noise interference are considered. Two-layer random switching communication topologies are proposed to solve the problem of communication failure. For acoustic link noise interference, accurate representation of valid communication information and noise stripping when designing controllers is necessary. Effective communication topology weights are designed to represent the validity of communication information interfered by noise. Utilizing state feedback and noise stripping, sufficient conditions for design formation controllers are proposed to ensure UUV formation achieves consensus under model uncertainties, current disturbances, and unstable communication. The stability of formation controllers is proven by the Lyapunov-Razumikhin theorem, and the validity is verified by simulation results. PMID:29473919

Cyber-Physical System Security With Deceptive Virtual Hosts for Industrial Control Networks

DOE PAGES

Vollmer, Todd; Manic, Milos

2014-05-01

A challenge facing industrial control network administrators is protecting the typically large number of connected assets for which they are responsible. These cyber devices may be tightly coupled with the physical processes they control and human induced failures risk dire real-world consequences. Dynamic virtual honeypots are effective tools for observing and attracting network intruder activity. This paper presents a design and implementation for self-configuring honeypots that passively examine control system network traffic and actively adapt to the observed environment. In contrast to prior work in the field, six tools were analyzed for suitability of network entity information gathering. Ettercap, anmore » established network security tool not commonly used in this capacity, outperformed the other tools and was chosen for implementation. Utilizing Ettercap XML output, a novel four-step algorithm was developed for autonomous creation and update of a Honeyd configuration. This algorithm was tested on an existing small campus grid and sensor network by execution of a collaborative usage scenario. Automatically created virtual hosts were deployed in concert with an anomaly behavior (AB) system in an attack scenario. Virtual hosts were automatically configured with unique emulated network stack behaviors for 92% of the targeted devices. The AB system alerted on 100% of the monitored emulated devices.« less

Design Criteria For Networked Image Analysis System

NASA Astrophysics Data System (ADS)

Reader, Cliff; Nitteberg, Alan

1982-01-01

Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

Methods for the design of vasomotor symptom trials: the menopausal strategies: finding lasting answers to symptoms and health network.

PubMed

Newton, Katherine M; Carpenter, Janet S; Guthrie, Katherine A; Anderson, Garnet L; Caan, Bette; Cohen, Lee S; Ensrud, Kristine E; Freeman, Ellen W; Joffe, Hadine; Sternfeld, Barbara; Reed, Susan D; Sherman, Sheryl; Sammel, Mary D; Kroenke, Kurt; Larson, Joseph C; Lacroix, Andrea Z

2014-01-01

This report describes the Menopausal Strategies: Finding Lasting Answers to Symptoms and Health network and methodological issues addressed in designing and implementing vasomotor symptom trials. Established in response to a National Institutes of Health request for applications, the network was charged with conducting rapid throughput randomized trials of novel and understudied available interventions postulated to alleviate vasomotor and other menopausal symptoms. Included are descriptions of and rationale for criteria used for interventions and study selection, common eligibility and exclusion criteria, common primary and secondary outcome measures, consideration of placebo response, establishment of a biorepository, trial duration, screening and recruitment, statistical methods, and quality control. All trial designs are presented, including the following: (1) a randomized, double-blind, placebo-controlled clinical trial designed to evaluate the effectiveness of the selective serotonin reuptake inhibitor escitalopram in reducing vasomotor symptom frequency and severity; (2) a two-by-three factorial design trial to test three different interventions (yoga, exercise, and ω-3 supplementation) for the improvement of vasomotor symptom frequency and bother; and (3) a three-arm comparative efficacy trial of the serotonin-norepinephrine reuptake inhibitor venlafaxine and low-dose oral estradiol versus placebo for reducing vasomotor symptom frequency. The network's structure and governance are also discussed. The methods used in and the lessons learned from the Menopausal Strategies: Finding Lasting Answers to Symptoms and Health trials are shared to encourage and support the conduct of similar trials and to encourage collaborations with other researchers.

Toward a new task assignment and path evolution (TAPE) for missile defense system (MDS) using intelligent adaptive SOM with recurrent neural networks (RNNs).

PubMed

Wang, Chi-Hsu; Chen, Chun-Yao; Hung, Kun-Neng

2015-06-01

In this paper, a new adaptive self-organizing map (SOM) with recurrent neural network (RNN) controller is proposed for task assignment and path evolution of missile defense system (MDS). We address the problem of N agents (defending missiles) and D targets (incoming missiles) in MDS. A new RNN controller is designed to force an agent (or defending missile) toward a target (or incoming missile), and a monitoring controller is also designed to reduce the error between RNN controller and ideal controller. A new SOM with RNN controller is then designed to dispatch agents to their corresponding targets by minimizing total damaging cost. This is actually an important application of the multiagent system. The SOM with RNN controller is the main controller. After task assignment, the weighting factors of our new SOM with RNN controller are activated to dispatch the agents toward their corresponding targets. Using the Lyapunov constraints, the weighting factors for the proposed SOM with RNN controller are updated to guarantee the stability of the path evolution (or planning) system. Excellent simulations are obtained using this new approach for MDS, which show that our RNN has the lowest average miss distance among the several techniques.

Control of fluxes in metabolic networks.

PubMed

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

2016-07-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. © 2016 Basler et al.; Published by Cold Spring Harbor Laboratory Press.

SDN Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Rhett

The SDN Project completed on time and on budget and successfully accomplished 100% of the scope of work outlined in the original Statement of Project Objective (SOPO). The SDN Project formed an alliance between Ameren Corporation, University of Illinois Urbana- Champaign (UIUC), Pacific Northwest National Laboratories (PNNL), and Schweitzer Engineering Laboratories, Inc. (SEL). The objective of the SDN Project is to address Topic Area of Interest 2: Sustain critical energy delivery functions while responding to a cyber-intrusion under Funding Opportunity Announcement DE-FOA-0000797. The goal of the project is to design and commercially release technology that provides a method to sustainmore » critical energy delivery functions during a cyber intrusion and to do this control system operators need the ability to quickly identify and isolate the affected network areas, and re-route critical information and control flows around. The objective of the SDN Project is to develop a Flow Controller that monitors, configures, and maintains the safe, reliable network traffic flows of all the local area networks (LANs) on a control system in the Energy sector. The SDN team identified the core attributes of a control system and produced an SDN flow controller that has the same core attributes enabling networks to be designed, configured and deployed that maximize the whitelisted, deny-bydefault and purpose built networks. This project researched, developed and commercially released technology that: Enables all field networks be to configured and monitored as if they are a single asset to be protected; Enables greatly improved and even precalculated response actions to reliability and cyber events; Supports pre-configured localized response actions tailored to provide resilience against failures and centralized response to cyber-attacks that improve network reliability and availability; Architecturally enables the right subject matter experts, who are usually the information technology and operational technology engineers, to be the ones centrally administering the technology and responding to events; Simplifies network configuration, improving deterministic Ethernet transport times, and providing instant visualization on where the communication circuits are and how all circuits are impacted when changes (e.g., configuration changes, failures or intrusions) happen, allowing operators to minimize downtime; and Improves the ability to identify deviations in network behavior resulting in detection and analysis of potential cyber intrusions and faster response times Results: This project has forever changed the way critical infrastructure networks are designed, secured, deployed and maintained. The cybersecurity and performance advantages achieved are significant, simply put traditional networking has been obsoleted while the team maintained Ethernet interoperability avoiding any legacy concerns. The team commercially released technology that accomplished all the cybersecurity goals outlined in the SOPO and completed it by executing the project management plan approved in the initial contract. The resulting Energy sector SDN flow controller model number is SEL-5056 and can be freely downloaded from the www.SELinc.com website. This technology not only improves the cybersecurity of control systems but has measured results that it improves the performance and reliability of the control system as well. This means the system owners can confidently apply it to their systems knowing that it will, “first do no harm” but actually improve the system as well. Success of the project is best measured by the sales and deployment of the technology. System owners in industrial, electric, defense, and oil and gas only months after commercial release have approved plans for deployment.« less

Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Woo, Simon S.; James, Mark; Paloulian, George K.

2012-01-01

As communication and networking technologies advance, networks will become highly complex and heterogeneous, interconnecting different network domains. There is a need to provide user authentication and data protection in order to further facilitate critical mission operations, especially in the tactical and mission-critical net-centric networking environment. The Autonomous Information Unit (AIU) technology was designed to provide the fine-grain data access and user control in a net-centric system-testing environment to meet these objectives. The AIU is a fundamental capability designed to enable fine-grain data access and user control in the cross-domain networking environments, where an AIU is composed of the mission data, metadata, and policy. An AIU provides a mechanism to establish trust among deployed AIUs based on recombining shared secrets, authentication and verify users with a username, X.509 certificate, enclave information, and classification level. AIU achieves data protection through (1) splitting data into multiple information pieces using the Shamir's secret sharing algorithm, (2) encrypting each individual information piece using military-grade AES-256 encryption, and (3) randomizing the position of the encrypted data based on the unbiased and memory efficient in-place Fisher-Yates shuffle method. Therefore, it becomes virtually impossible for attackers to compromise data since attackers need to obtain all distributed information as well as the encryption key and the random seeds to properly arrange the data. In addition, since policy can be associated with data in the AIU, different user access and data control strategies can be included. The AIU technology can greatly enhance information assurance and security management in the bandwidth-limited and ad hoc net-centric environments. In addition, AIU technology can be applicable to general complex network domains and applications where distributed user authentication and data protection are necessary. AIU achieves fine-grain data access and user control, reducing the security risk significantly, simplifying the complexity of various security operations, and providing the high information assurance across different network domains.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

PubMed

Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

2013-08-14

High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. ClinicalTrials.gov NCT01142804.

Online intelligent controllers for an enzyme recovery plant: design methodology and performance.

PubMed

Leite, M S; Fujiki, T L; Silva, F V; Fileti, A M F

2010-12-27

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity.

Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

PubMed Central

Leite, M. S.; Fujiki, T. L.; Silva, F. V.; Fileti, A. M. F.

2010-01-01

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity. PMID:21234106

Synchronization in node of complex networks consist of complex chaotic system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Qiang, E-mail: qiangweibeihua@163.com; Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin; Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024

2014-07-15

A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

The Temporal Resolution of Flight Attitude Control in Dragonflies and Locusts: Lessons for the Design of Flapping-Wing MAVs

DTIC Science & Technology

2007-12-04

central nevous system , consisting of a self- excited neuronal network. Even in the absence of any sensory inputs this network will 4 produce, in two...is not necessary in smaller systems . Introduction Conventional aircraft can be designed such that steady-state aerodynamics apply. Thus, it is...active damping by visual inputs, whereas the same is not necessary in smaller systems . 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17

Distributed Learning and Information Dynamics In Networked Autonomous Systems

DTIC Science & Technology

2015-11-20

2009 to June 30, 2015 4. TITLE AND SUBTITLE DISTRIBUTED LEARNING AND INFORMATION DYNAMICS IN NETWORKED AUTONOMOUS SYSTEMS 5a. CONTRACT NUMBER 5b...AUTONOMOUS SYSTEMS AFOSR Grant #FA9550–09–1–0538 PI: Eric Feron (current) Jeff S. Shamma (former) Georgia Institute of Technology Atlanta, GA 30332 1...Control. Design of event-based optimal remote estimation systems : We have proposed two new for- mulations to study the design of optimal remote

The driving regulators of the connectivity protein network of brain malignancies

NASA Astrophysics Data System (ADS)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Wildburger, Norelle C.; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

An important problem in modern therapeutics at the proteomic level remains to identify therapeutic targets in a plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presents the application of novel modern control concepts, such as pinning controllability and observability applied to the glioma cancer stem cells (GSCs) protein graph network with known and novel association to glioblastoma (GBM). The theoretical frameworks provides us with the minimal number of "driver nodes", which are necessary, and their location to determine the full control over the obtained graph network in order to provide a change in the network's dynamics from an initial state (disease) to a desired state (non-disease). The achieved results will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, to design and test novel therapeutic solutions.

A Comparison Between Publish-and-Subscribe and Client-Server Models in Distributed Control System Networks

NASA Technical Reports Server (NTRS)

Boulanger, Richard P., Jr.; Kwauk, Xian-Min; Stagnaro, Mike; Kliss, Mark (Technical Monitor)

1998-01-01

The BIO-Plex control system requires real-time, flexible, and reliable data delivery. There is no simple "off-the-shelf 'solution. However, several commercial packages will be evaluated using a testbed at ARC for publish- and-subscribe and client-server communication architectures. Point-to-point communication architecture is not suitable for real-time BIO-Plex control system. Client-server architecture provides more flexible data delivery. However, it does not provide direct communication among nodes on the network. Publish-and-subscribe implementation allows direct information exchange among nodes on the net, providing the best time-critical communication. In this work Network Data Delivery Service (NDDS) from Real-Time Innovations, Inc. ARTIE will be used to implement publish-and subscribe architecture. It offers update guarantees and deadlines for real-time data delivery. Bridgestone, a data acquisition and control software package from National Instruments, will be tested for client-server arrangement. A microwave incinerator located at ARC will be instrumented with a fieldbus network of control devices. BridgeVIEW will be used to implement an enterprise server. An enterprise network consisting of several nodes at ARC and a WAN connecting ARC and RISC will then be setup to evaluate proposed control system architectures. Several network configurations will be evaluated for fault tolerance, quality of service, reliability and efficiency. Data acquired from these network evaluation tests will then be used to determine preliminary design criteria for the BIO-Plex distributed control system.

A new switching control for finite-time synchronization of memristor-based recurrent neural networks.

PubMed

Gao, Jie; Zhu, Peiyong; Alsaedi, Ahmed; Alsaadi, Fuad E; Hayat, Tasawar

2017-02-01

In this paper, finite-time synchronization (FTS) of memristor-based recurrent neural networks (MNNs) with time-varying delays is investigated by designing a new switching controller. First, by using the differential inclusions theory and set-valued maps, sufficient conditions to ensure FTS of MNNs are obtained under the two cases of 0<α<1 and α=0, and it is derived that α=0 is the critical value of 0<α<1. Next, it is discussed deeply on the relation between the parameter α and the synchronization time. Then, a new controller with a switching parameter α is designed which can shorten the synchronization time. Finally, some numerical simulation examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2016 Elsevier Ltd. All rights reserved.

PV-Diesel Hybrid SCADA Experiment Network Design

NASA Technical Reports Server (NTRS)

Kalu, Alex; Durand, S.; Emrich, Carol; Ventre, G.; Wilson, W.; Acosta, R.

1999-01-01

The essential features of an experimental network for renewable power system satellite based supervisory, control and data acquisition (SCADA) are communication links, controllers, diagnostic equipment and a hybrid power system. Required components for implementing the network consist of two satellite ground stations, to satellite modems, two 486 PCs, two telephone receivers, two telephone modems, two analog telephone lines, one digital telephone line, a hybrid-power system equipped with controller and a satellite spacecraft. In the technology verification experiment (TVE) conducted by Savannah State University and Florida Solar Energy Center, the renewable energy hybrid system is the Apex-1000 Mini-Hybrid which is equipped with NGC3188 for user interface and remote control and the NGC2010 for monitoring and basic control tasks. This power system is connected to a satellite modem via a smart interface, RS232. Commands are sent to the power system control unit through a control PC designed as PC1. PC1 is thus connected to a satellite model through RS232. A second PC, designated PC2, the diagnostic PC is connected to both satellite modems via separate analog telephone lines for checking modems'health. PC2 is also connected to PC1 via a telephone line. Due to the unavailability of a second ground station for the ACTS, one ground station is used to serve both the sending and receiving functions in this experiment. Signal is sent from the control PC to the Hybrid system at a frequency f(sub 1), different from f(sub 2), the signal from the hybrid system to the control PC. f(sub l) and f(sub 2) are sufficiently separated to avoid interference.

F-15 IFCS: Intelligent Flight Control System

NASA Technical Reports Server (NTRS)

Bosworth, John

2007-01-01

This viewgraph presentation describes the F-15 Intelligent Flight Control System (IFCS). The goals of this project include: 1) Demonstrate revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions; and 2) Demonstrate advance neural network-based flight control technology for new aerospace systems designs.

Regular Topologies for Gigabit Wide-Area Networks. Volume 1

NASA Technical Reports Server (NTRS)

Shacham, Nachum; Denny, Barbara A.; Lee, Diane S.; Khan, Irfan H.; Lee, Danny Y. C.; McKenney, Paul

1994-01-01

In general terms, this project aimed at the analysis and design of techniques for very high-speed networking. The formal objectives of the project were to: (1) Identify switch and network technologies for wide-area networks that interconnect a large number of users and can provide individual data paths at gigabit/s rates; (2) Quantitatively evaluate and compare existing and proposed architectures and protocols, identify their strength and growth potentials, and ascertain the compatibility of competing technologies; and (3) Propose new approaches to existing architectures and protocols, and identify opportunities for research to overcome deficiencies and enhance performance. The project was organized into two parts: 1. The design, analysis, and specification of techniques and protocols for very-high-speed network environments. In this part, SRI has focused on several key high-speed networking areas, including Forward Error Control (FEC) for high-speed networks in which data distortion is the result of packet loss, and the distribution of broadband, real-time traffic in multiple user sessions. 2. Congestion Avoidance Testbed Experiment (CATE). This part of the project was done within the framework of the DARTnet experimental T1 national network. The aim of the work was to advance the state of the art in benchmarking DARTnet's performance and traffic control by developing support tools for network experimentation, by designing benchmarks that allow various algorithms to be meaningfully compared, and by investigating new queueing techniques that better satisfy the needs of best-effort and reserved-resource traffic. This document is the final technical report describing the results obtained by SRI under this project. The report consists of three volumes: Volume 1 contains a technical description of the network techniques developed by SRI in the areas of FEC and multicast of real-time traffic. Volume 2 describes the work performed under CATE. Volume 3 contains the source code of all software developed under CATE.

Finite-time synchronization of complex networks with non-identical nodes and impulsive disturbances

NASA Astrophysics Data System (ADS)

Zhang, Wanli; Li, Chuandong; He, Xing; Li, Hongfei

2018-01-01

This paper investigates the finite-time synchronization of complex networks (CNs) with non-identical nodes and impulsive disturbances. By utilizing stability theories, new 1-norm-based analytical techniques and suitable comparison, systems, several sufficient conditions are obtained to realize the synchronization goal in finite time. State feedback controllers with and without the sign function are designed. Results show that the controllers with sign function can reduce the conservativeness of control gains and the controllers without sign function can overcome the chattering phenomenon. Numerical simulations are offered to verify the effectiveness of the theoretical analysis.

Crossbar Switches For Optical Data-Communication Networks

NASA Technical Reports Server (NTRS)

Monacos, Steve P.

1994-01-01

Optoelectronic and electro-optical crossbar switches called "permutation engines" (PE's) developed to route packets of data through fiber-optic communication networks. Basic network concept described in "High-Speed Optical Wide-Area Data-Communication Network" (NPO-18983). Nonblocking operation achieved by decentralized switching and control scheme. Each packet routed up or down in each column of this 5-input/5-output permutation engine. Routing algorithm ensures each packet arrives at its designated output port without blocking any other packet that does not contend for same output port.

SDN control of optical nodes in metro networks for high capacity inter-datacentre links

NASA Astrophysics Data System (ADS)

Magalhães, Eduardo; Perry, Philip; Barry, Liam

2017-11-01

Worldwide demand for bandwidth has been growing fast for some years and continues to do so. To cover this, mega datacentres need scalable connectivity to provide rich connectivity to handle the heavy traffic across them. Therefore, hardware infrastructures must be able to play different roles according to service and traffic requirements. In this context, software defined networking (SDN) decouples the network control and forwarding functions enabling the network control to become directly programmable and the underlying infrastructure to be abstracted for applications and network services. In addition, elastic optical networking (EON) technologies enable efficient spectrum utilization by allocating variable bandwidth to each user according to their actual needs. In particular, flexible transponders and reconfigurable optical add/drop multiplexers (ROADMs) are key elements since they can offer degrees of freedom to self adapt accordingly. Thus, it is crucial to design control methods in order to optimize the hardware utilization and offer high reconfigurability, flexibility and adaptability. In this paper, we propose and analyze, using a simulation framework, a method of capacity maximization through optical power profile manipulation for inter datacentre links that use existing metropolitan optical networks by exploiting the global network view afforded by SDN. Results show that manipulating the loss profiles of the ROADMs in the metro-network can yield optical signal-to-noise ratio (OSNR) improvements up to 10 dB leading to an increase in 112% in total capacity.

Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems

NASA Technical Reports Server (NTRS)

Esogbue, Augustine O.

1998-01-01

The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of these are in progress in our laboratory while others await additional support. All of these enhancements will improve the attractiveness of the controller as an effective tool for the on line control of an array of complex process environments.

Data Transfer Advisor with Transport Profiling Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Liu, Qiang; Yun, Daqing

The network infrastructures have been rapidly upgraded in many high-performance networks (HPNs). However, such infrastructure investment has not led to corresponding performance improvement in big data transfer, especially at the application layer, largely due to the complexity of optimizing transport control on end hosts. We design and implement ProbData, a PRofiling Optimization Based DAta Transfer Advisor, to help users determine the most effective data transfer method with the most appropriate control parameter values to achieve the best data transfer performance. ProbData employs a profiling optimization based approach to exploit the optimal operational zone of various data transfer methods in supportmore » of big data transfer in extreme scale scientific applications. We present a theoretical framework of the optimized profiling approach employed in ProbData as wellas its detailed design and implementation. The advising procedure and performance benefits of ProbData are illustrated and evaluated by proof-of-concept experiments in real-life networks.« less

Cross-layer protocols optimized for real-time multimedia services in energy-constrained mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2003-07-01

Mobile ad hoc networking (MANET) supports self-organizing, mobile infrastructures and enables an autonomous network of mobile nodes that can operate without a wired backbone. Ad hoc networks are characterized by multihop, wireless connectivity via packet radios and by the need for efficient dynamic protocols. All routers are mobile and can establish connectivity with other nodes only when they are within transmission range. Importantly, ad hoc wireless nodes are resource-constrained, having limited processing, memory, and battery capacity. Delivery of high quality-ofservice (QoS), real-time multimedia services from Internet-based applications over a MANET is a challenge not yet achieved by proposed Internet Engineering Task Force (IETF) ad hoc network protocols in terms of standard performance metrics such as end-to-end throughput, packet error rate, and delay. In the distributed operations of route discovery and maintenance, strong interaction occurs across MANET protocol layers, in particular, the physical, media access control (MAC), network, and application layers. The QoS requirements are specified for the service classes by the application layer. The cross-layer design must also satisfy the battery-limited energy constraints, by minimizing the distributed power consumption at the nodes and of selected routes. Interactions across the layers are modeled in terms of the set of concatenated design parameters including associated energy costs. Functional dependencies of the QoS metrics are described in terms of the concatenated control parameters. New cross-layer designs are sought that optimize layer interdependencies to achieve the "best" QoS available in an energy-constrained, time-varying network. The protocol design, based on a reactive MANET protocol, adapts the provisioned QoS to dynamic network conditions and residual energy capacities. The cross-layer optimization is based on stochastic dynamic programming conditions derived from time-dependent models of MANET packet flows. Regulation of network behavior is modeled by the optimal control of the conditional rates of multivariate point processes (MVPPs); these rates depend on the concatenated control parameters through a change of probability measure. The MVPP models capture behavior of many service applications, e.g., voice, video and the self-similar behavior of Internet data sessions. Performance verification of the cross-layer protocols, derived from the dynamic programming conditions, can be achieved by embedding the conditions in a reactive routing protocol for MANETs, in a simulation environment, such as the wireless extension of ns-2. A canonical MANET scenario consists of a distributed collection of battery-powered laptops or hand-held terminals, capable of hosting multimedia applications. Simulation details and performance tradeoffs, not presented, remain for a sequel to the paper.

Intelligent failure-tolerant control

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1991-01-01

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods.

SCM: A method to improve network service layout efficiency with network evolution.

PubMed

Zhao, Qi; Zhang, Chuanhao; Zhao, Zheng

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of "software defined network + network function virtualization" (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently.

A Compartmentalized Out-of-Equilibrium Enzymatic Reaction Network for Sustained Autonomous Movement

PubMed Central

2016-01-01

Every living cell is a compartmentalized out-of-equilibrium system exquisitely able to convert chemical energy into function. In order to maintain homeostasis, the flux of metabolites is tightly controlled by regulatory enzymatic networks. A crucial prerequisite for the development of lifelike materials is the construction of synthetic systems with compartmentalized reaction networks that maintain out-of-equilibrium function. Here, we aim for autonomous movement as an example of the conversion of feedstock molecules into function. The flux of the conversion is regulated by a rationally designed enzymatic reaction network with multiple feedforward loops. By compartmentalizing the network into bowl-shaped nanocapsules the output of the network is harvested as kinetic energy. The entire system shows sustained and tunable microscopic motion resulting from the conversion of multiple external substrates. The successful compartmentalization of an out-of-equilibrium reaction network is a major first step in harnessing the design principles of life for construction of adaptive and internally regulated lifelike systems. PMID:27924313

Networks consolidation program: Maintenance and Operations (M&O) staffing estimates

NASA Technical Reports Server (NTRS)

Goodwin, J. P.

1981-01-01

The Mark IV-A consolidate deep space and high elliptical Earth orbiter (HEEO) missions tracking and implements centralized control and monitoring at the deep space communications complexes (DSCC). One of the objectives of the network design is to reduce maintenance and operations (M&O) costs. To determine if the system design meets this objective an M&O staffing model for Goldstone was developed which was used to estimate the staffing levels required to support the Mark IV-A configuration. The study was performed for the Goldstone complex and the program office translated these estimates for the overseas complexes to derive the network estimates.

Group consensus control for networked multi-agent systems with communication delays.

PubMed

An, Bao-Ran; Liu, Guo-Ping; Tan, Chong

2018-05-01

This paper investigates group consensus problems in networked multi-agent systems (NMAS) with communication delays. Based on the sed state prediction scheme, the group consensus control protocol is designed to compensate the communication delay actively. In light of algebraic graph theories and matrix theories, necessary and(or) sufficient conditions of group consensus with respect to a given admissible control set are obtained for the NMAS with communication delays under mild assumptions. Finally, simulations are performed to demonstrate the effectiveness of the theoretical results. Copyright © 2018 ISA. All rights reserved.

Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

PubMed

Wang, Leimin; Shen, Yi; Sheng, Yin

2016-04-01

This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is designed to realize the finite-time robust stabilization of DNNs with discontinuous activations and parameter uncertainties, and the upper bound of the settling time functional for stabilization is estimated. Finally, two examples are provided to demonstrate the effectiveness of the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design, Specification, and Synthesis of Aircraft Electric Power Systems Control Logic

NASA Astrophysics Data System (ADS)

Xu, Huan

Cyber-physical systems integrate computation, networking, and physical processes. Substantial research challenges exist in the design and verification of such large-scale, distributed sensing, actuation, and control systems. Rapidly improving technology and recent advances in control theory, networked systems, and computer science give us the opportunity to drastically improve our approach to integrated flow of information and cooperative behavior. Current systems rely on text-based specifications and manual design. Using new technology advances, we can create easier, more efficient, and cheaper ways of developing these control systems. This thesis will focus on design considerations for system topologies, ways to formally and automatically specify requirements, and methods to synthesize reactive control protocols, all within the context of an aircraft electric power system as a representative application area. This thesis consists of three complementary parts: synthesis, specification, and design. The first section focuses on the synthesis of central and distributed reactive controllers for an aircraft elec- tric power system. This approach incorporates methodologies from computer science and control. The resulting controllers are correct by construction with respect to system requirements, which are formulated using the specification language of linear temporal logic (LTL). The second section addresses how to formally specify requirements and introduces a domain-specific language for electric power systems. A software tool automatically converts high-level requirements into LTL and synthesizes a controller. The final sections focus on design space exploration. A design methodology is proposed that uses mixed-integer linear programming to obtain candidate topologies, which are then used to synthesize controllers. The discrete-time control logic is then verified in real-time by two methods: hardware and simulation. Finally, the problem of partial observability and dynamic state estimation is explored. Given a set placement of sensors on an electric power system, measurements from these sensors can be used in conjunction with control logic to infer the state of the system.

A high performance long-reach passive optical network with a novel excess bandwidth distribution scheme

NASA Astrophysics Data System (ADS)

Chao, I.-Fen; Zhang, Tsung-Min

2015-06-01

Long-reach passive optical networks (LR-PONs) have been considered to be promising solutions for future access networks. In this paper, we propose a distributed medium access control (MAC) scheme over an advantageous LR-PON network architecture that reroutes the control information from and back to all ONUs through an (N + 1) × (N + 1) star coupler (SC) deployed near the ONUs, thereby overwhelming the extremely long propagation delay problem in LR-PONs. In the network, the control slot is designed to contain all bandwidth requirements of all ONUs and is in-band time-division-multiplexed with a number of data slots within a cycle. In the proposed MAC scheme, a novel profit-weight-based dynamic bandwidth allocation (P-DBA) scheme is presented. The algorithm is designed to efficiently and fairly distribute the amount of excess bandwidth based on a profit value derived from the excess bandwidth usage of each ONU, which resolves the problems of previously reported DBA schemes that are either unfair or inefficient. The simulation results show that the proposed decentralized algorithms exhibit a nearly three-order-of-magnitude improvement in delay performance compared to the centralized algorithms over LR-PONs. Moreover, the newly proposed P-DBA scheme guarantees low delay performance and fairness even when under attack by the malevolent ONU irrespective of traffic loads and burstiness.

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Okayama optical polarimetry and spectroscopy system (OOPS) II. Network-transparent control software.

NASA Astrophysics Data System (ADS)

Sasaki, T.; Kurakami, T.; Shimizu, Y.; Yutani, M.

Control system of the OOPS (Okayama Optical Polarimetry and Spectroscopy system) is designed to integrate several instruments whose controllers are distributed over a network; the OOPS instrument, a CCD camera and data acquisition unit, the 91 cm telescope, an autoguider, a weather monitor, and an image display tool SAOimage. With the help of message-based communication, the control processes cooperate with related processes to perform an astronomical observation under supervising control by a scheduler process. A logger process collects status data of all the instruments to distribute them to related processes upon request. Software structure of each process is described.

Performance Evaluation and Control of Distributed Computer Communication Networks.

DTIC Science & Technology

1985-09-01

Zukerman, S. Katz, P. Rodriguez, R. Pazos , S. Resheff, Z. Tsai, Z. Zhang, L. Jong, V. Minh. Other participants are the following visiting... Pazos -Rangel "Bandwidth Allocation and Routing in ISDN’s," IEEE Communications Magazine, February 1984. Abstract The goal of communications network design...location and routing for integrated networks - is formulated, and efficient methods for its solution are presented. (2) R.A. Pazos -Rangel "Evaluation

Implementation of remote monitoring and managing switches

NASA Astrophysics Data System (ADS)

Leng, Junmin; Fu, Guo

2010-12-01

In order to strengthen the safety performance of the network and provide the big convenience and efficiency for the operator and the manager, the system of remote monitoring and managing switches has been designed and achieved using the advanced network technology and present network resources. The fast speed Internet Protocol Cameras (FS IP Camera) is selected, which has 32-bit RSIC embedded processor and can support a number of protocols. An Optimal image compress algorithm Motion-JPEG is adopted so that high resolution images can be transmitted by narrow network bandwidth. The architecture of the whole monitoring and managing system is designed and implemented according to the current infrastructure of the network and switches. The control and administrative software is projected. The dynamical webpage Java Server Pages (JSP) development platform is utilized in the system. SQL (Structured Query Language) Server database is applied to save and access images information, network messages and users' data. The reliability and security of the system is further strengthened by the access control. The software in the system is made to be cross-platform so that multiple operating systems (UNIX, Linux and Windows operating systems) are supported. The application of the system can greatly reduce manpower cost, and can quickly find and solve problems.

Load capacity improvements in nucleic acid based systems using partially open feedback control.

PubMed

Kulkarni, Vishwesh; Kharisov, Evgeny; Hovakimyan, Naira; Kim, Jongmin

2014-08-15

Synthetic biology is facilitating novel methods and components to build in vivo and in vitro circuits to better understand and re-engineer biological networks. Recently, Kim and Winfree have synthesized a remarkably elegant network of transcriptional oscillators in vitro using a modular architecture of synthetic gene analogues and a few enzymes that, in turn, could be used to drive a variety of downstream circuits and nanodevices. However, these oscillators are sensitive to initial conditions and downstream load processes. Furthermore, the oscillations are not sustained since the inherently closed design suffers from enzyme deactivation, NTP fuel exhaustion, and waste product build up. In this paper, we show that a partially open architecture in which an [Symbol: see text]1 adaptive controller, implemented inside an in silico computer that resides outside the wet-lab apparatus, can ensure sustained tunable oscillations in two specific designs of the Kim-Winfree oscillator networks. We consider two broad cases of operation: (1) the oscillator network operating in isolation and (2) the oscillator network driving a DNA tweezer subject to a variable load. In both scenarios, our simulation results show a significant improvement in the tunability and robustness of these oscillator networks. Our approach can be easily adopted to improve the loading capacity of a wide range of synthetic biological devices.

Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach.

PubMed

Liu, Derong; Wang, Ding; Li, Hongliang

2014-02-01

In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.

Model-based design of RNA hybridization networks implemented in living cells

PubMed Central

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter

2017-01-01

Abstract Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. PMID:28934501

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Configuration development for ROMENET

NASA Astrophysics Data System (ADS)

Rhue, Lawrence

1989-10-01

A plan prepared by RJO Enterprises and BBN Communications Corporation (BBNCC) for the design of ROMENET, a DDN-like testbed for the Rome Air Development Center (RADC) Wide Area Networks (WAN) laboratory is presented. The ROMENET is intended to provide RADC with the ability to test and evaluate the performance and vulnerability of the Defense Data Network (DDN) technologies in support of specific Major Command programs and activities at RADC. It will also support experimentation with packet switched network technologies and includes facilities to analytically evaluate the performance of the network and its associated equipment and media. In addition, ROMENET will provide a simulation vehicle for controlled interference or jamming into the media for vulnerability assessment. Through interfaces with the RADC Battle Management Laboratory (BML), ROMENET will allow the Air Force to assess the restorative and performance characteristics of the network under stressed conditions. The closed environment of ROMENET makes it ideal for creating and testing routing algorithms and network control protocols.