WorldWideScience

Sample records for neural feedback systems

  1. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  2. Neural networks for feedback feedforward nonlinear control systems.

    Science.gov (United States)

    Parisini, T; Zoppoli, R

    1994-01-01

    This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

  3. Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

    Science.gov (United States)

    Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

    2015-01-01

    Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

  4. Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system

    International Nuclear Information System (INIS)

    Sabahi, Kamel; Teshnehlab, Mohammad; Shoorhedeli, Mahdi Aliyari

    2009-01-01

    In this study, a new adaptive controller based on modified feedback error learning (FEL) approaches is proposed for load frequency control (LFC) problem. The FEL strategy consists of intelligent and conventional controllers in feedforward and feedback paths, respectively. In this strategy, a conventional feedback controller (CFC), i.e. proportional, integral and derivative (PID) controller, is essential to guarantee global asymptotic stability of the overall system; and an intelligent feedforward controller (INFC) is adopted to learn the inverse of the controlled system. Therefore, when the INFC learns the inverse of controlled system, the tracking of reference signal is done properly. Generally, the CFC is designed at nominal operating conditions of the system and, therefore, fails to provide the best control performance as well as global stability over a wide range of changes in the operating conditions of the system. So, in this study a supervised controller (SC), a lookup table based controller, is addressed for tuning of the CFC. During abrupt changes of the power system parameters, the SC adjusts the PID parameters according to these operating conditions. Moreover, for improving the performance of overall system, a recurrent fuzzy neural network (RFNN) is adopted in INFC instead of the conventional neural network, which was used in past studies. The proposed FEL controller has been compared with the conventional feedback error learning controller (CFEL) and the PID controller through some performance indices

  5. The Neural Feedback Response to Error As a Teaching Signal for the Motor Learning System

    Science.gov (United States)

    Shadmehr, Reza

    2016-01-01

    When we experience an error during a movement, we update our motor commands to partially correct for this error on the next trial. How does experience of error produce the improvement in the subsequent motor commands? During the course of an erroneous reaching movement, proprioceptive and visual sensory pathways not only sense the error, but also engage feedback mechanisms, resulting in corrective motor responses that continue until the hand arrives at its goal. One possibility is that this feedback response is co-opted by the learning system and used as a template to improve performance on the next attempt. Here we used electromyography (EMG) to compare neural correlates of learning and feedback to test the hypothesis that the feedback response to error acts as a template for learning. We designed a task in which mixtures of error-clamp and force-field perturbation trials were used to deconstruct EMG time courses into error-feedback and learning components. We observed that the error-feedback response was composed of excitation of some muscles, and inhibition of others, producing a complex activation/deactivation pattern during the reach. Despite this complexity, across muscles the learning response was consistently a scaled version of the error-feedback response, but shifted 125 ms earlier in time. Across people, individuals who produced a greater feedback response to error, also learned more from error. This suggests that the feedback response to error serves as a teaching signal for the brain. Individuals who learn faster have a better teacher in their feedback control system. SIGNIFICANCE STATEMENT Our sensory organs transduce errors in behavior. To improve performance, we must generate better motor commands. How does the nervous system transform an error in sensory coordinates into better motor commands in muscle coordinates? Here we show that when an error occurs during a movement, the reflexes transform the sensory representation of error into motor

  6. Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

    Directory of Open Access Journals (Sweden)

    Bahita Mohamed

    2011-01-01

    Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

  7. Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

    Science.gov (United States)

    Xu, Bin; Yang, Chenguang; Pan, Yongping

    2015-10-01

    This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.

  8. Control of uncertain systems by feedback linearization with neural networks augmentation. Part II. Controller validation by numerical simulation

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2010-09-01

    Full Text Available The paper was conceived in two parts. Part I, previously published in this journal, highlighted the main steps of adaptive output feedback control for non-affine uncertain systems, having a known relative degree. The main paradigm of this approach was the feedback linearization (dynamic inversion with neural network augmentation. Meanwhile, based on new contributions of the authors, a new paradigm, that of robust servomechanism problem solution, has been added to the controller architecture. The current Part II of the paper presents the validation of the controller hereby obtained by using the longitudinal channel of a hovering VTOL-type aircraft as mathematical model.

  9. Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

    Science.gov (United States)

    Wang, W.; Wang, D.; Peng, Z. H.

    2017-09-01

    Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

  10. Online Recorded Data-Based Composite Neural Control of Strict-Feedback Systems With Application to Hypersonic Flight Dynamics.

    Science.gov (United States)

    Xu, Bin; Yang, Daipeng; Shi, Zhongke; Pan, Yongping; Chen, Badong; Sun, Fuchun

    2017-09-25

    This paper investigates the online recorded data-based composite neural control of uncertain strict-feedback systems using the backstepping framework. In each step of the virtual control design, neural network (NN) is employed for uncertainty approximation. In previous works, most designs are directly toward system stability ignoring the fact how the NN is working as an approximator. In this paper, to enhance the learning ability, a novel prediction error signal is constructed to provide additional correction information for NN weight update using online recorded data. In this way, the neural approximation precision is highly improved, and the convergence speed can be faster. Furthermore, the sliding mode differentiator is employed to approximate the derivative of the virtual control signal, and thus, the complex analysis of the backstepping design can be avoided. The closed-loop stability is rigorously established, and the boundedness of the tracking error can be guaranteed. Through simulation of hypersonic flight dynamics, the proposed approach exhibits better tracking performance.

  11. Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  13. Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding

    2017-08-29

    This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.

  14. Globally Stable Adaptive Backstepping Neural Network Control for Uncertain Strict-Feedback Systems With Tracking Accuracy Known a Priori.

    Science.gov (United States)

    Chen, Weisheng; Ge, Shuzhi Sam; Wu, Jian; Gong, Maoguo

    2015-09-01

    This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is given a priori. In contrast to the classical adaptive backstepping NN control schemes, this paper analyzes the convergence of the tracking error using Barbalat's Lemma via some nonnegative functions rather than the positive-definite Lyapunov functions. Thus, the accuracy of the ultimate tracking error can be determined and adjusted accurately a priori, and the closed-loop system is guaranteed to be globally uniformly ultimately bounded. The main technical novelty is to construct three new n th-order continuously differentiable functions, which are used to design the control law, the virtual control variables, and the adaptive laws. Finally, two simulation examples are given to illustrate the effectiveness and advantages of the proposed control method.

  15. Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

    Science.gov (United States)

    de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

    2008-11-01

    A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes.

  16. Policy Feedback System (PFS)

    Data.gov (United States)

    Social Security Administration — The Policy Feedback System (PFS) is a web application developed by the Office of Disability Policy Management Information (ODPMI) team that gathers empirical data...

  17. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  18. Decorrelation of Neural-Network Activity by Inhibitory Feedback

    Science.gov (United States)

    Einevoll, Gaute T.; Diesmann, Markus

    2012-01-01

    Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between

  19. Feedback System Theory

    Science.gov (United States)

    1978-11-01

    R 2. GOVT A $ SION NO. 3 RIEqLPýIVT’S.;TALOG NUMBER r/ 4. TITLE (and wbiFflT, -L M4 1 , FEEDBACK SYSTEM THEORY ~r Inter in- 6. PERFORMING ORG. REPORT...ANNUAL REPORT FEEDBACK SYSTEM THEORY AFOSR GRANT NO. 76-2946B Air Force Office of Scientific Research for year ending October 31, 1978 79 02 08 L|I...re less stringent than in other synthesis techniques which cannot handle significant parameter uncertainty. _I FEEDBACK SYSTEM THEORY 1. Introduction

  20. Ambulatory Feedback System

    Science.gov (United States)

    Finger, Herbert; Weeks, Bill

    1985-01-01

    This presentation discusses instrumentation that will be used for a specific event, which we hope will carry on to future events within the Space Shuttle program. The experiment is the Autogenic Feedback Training Experiment (AFTE) scheduled for Spacelab 3, currently scheduled to be launched in November, 1984. The objectives of the AFTE are to determine the effectiveness of autogenic feedback in preventing or reducing space adaptation syndrome (SAS), to monitor and record in-flight data from the crew, to determine if prediction criteria for SAS can be established, and, finally, to develop an ambulatory instrument package to mount the crew throughout the mission. The purpose of the Ambulatory Feedback System (AFS) is to record the responses of the subject during a provocative event in space and provide a real-time feedback display to reinforce the training.

  1. Computational aspects of feedback in neural circuits.

    Directory of Open Access Journals (Sweden)

    Wolfgang Maass

    2007-01-01

    Full Text Available It has previously been shown that generic cortical microcircuit models can perform complex real-time computations on continuous input streams, provided that these computations can be carried out with a rapidly fading memory. We investigate the computational capability of such circuits in the more realistic case where not only readout neurons, but in addition a few neurons within the circuit, have been trained for specific tasks. This is essentially equivalent to the case where the output of trained readout neurons is fed back into the circuit. We show that this new model overcomes the limitation of a rapidly fading memory. In fact, we prove that in the idealized case without noise it can carry out any conceivable digital or analog computation on time-varying inputs. But even with noise, the resulting computational model can perform a large class of biologically relevant real-time computations that require a nonfading memory. We demonstrate these computational implications of feedback both theoretically, and through computer simulations of detailed cortical microcircuit models that are subject to noise and have complex inherent dynamics. We show that the application of simple learning procedures (such as linear regression or perceptron learning to a few neurons enables such circuits to represent time over behaviorally relevant long time spans, to integrate evidence from incoming spike trains over longer periods of time, and to process new information contained in such spike trains in diverse ways according to the current internal state of the circuit. In particular we show that such generic cortical microcircuits with feedback provide a new model for working memory that is consistent with a large set of biological constraints. Although this article examines primarily the computational role of feedback in circuits of neurons, the mathematical principles on which its analysis is based apply to a variety of dynamical systems. Hence they may also

  2. Accelerator and feedback control simulation using neural networks

    International Nuclear Information System (INIS)

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

    1991-05-01

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

  3. Neural correlates of feedback processing in toddlers

    NARCIS (Netherlands)

    Meyer, M.; Bekkering, H.; Janssen, D.J.C.; Bruijn, E.R.A. de; Hunnius, S.

    2014-01-01

    External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated

  4. KEKB bunch feedback systems

    Energy Technology Data Exchange (ETDEWEB)

    Tobiyama, M; Kikutani, E [National Lab. for High Energy Physics, Tsukuba, Ibaraki (Japan)

    1996-08-01

    Design and the present status of the bunch by bunch feedback systems for KEKB rings are shown. The detection of the bunch oscillation are made with the phase detection for longitudinal plane, the AM/PM method for transverse plane. Two GHz component of the bunch signal which is extracted with an analog FIR filter is used for the detection. Hardware two-tap FIR filter systems to shift the phase of the oscillation by 90deg will be used for the longitudinal signal processing. The same system will be used with no filtering but with only digital delay for transverse system. The candidate for the kicker and the required maximum power are also estimated. (author)

  5. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  6. Bunch by bunch feedback systems

    International Nuclear Information System (INIS)

    Tobiyama, Makoto

    2006-01-01

    Outlines of bunch-by-bunch feedback systems for suppressing multibunch instabilities in electron/positron storage rings are presented. The design principles and functions of the feedback components are reviewed. Recent topics of applying very fast and dense FPGA as feedback signal processor are also shown. (author)

  7. Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

    Science.gov (United States)

    Pan, Yongping; Yu, Haoyong

    2017-06-01

    This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

  8. TFTR plasma feedback systems

    International Nuclear Information System (INIS)

    Efthimion, P.; Hawryluk, R.J.; Hojsak, W.; Marsala, R.J.; Mueller, D.; Rauch, W.; Tait, G.D.; Taylor, G.; Thompson, M.

    1985-01-01

    The Tokamak Fusion Test Reactor employs feedback control systems for four plasma parameters, i.e. for plasma current, for plasma major radius, for plasma vertical position, and for plasma density. The plasma current is controlled by adjusting the rate of change of current in the Ohmic Heating (OH) coil system. Plasma current is continuously sensed by a Rogowski coil and its associated electronics; the error between it and a preprogrammed reference plasma current history is operated upon by a ''proportional-plusintegral-plus-derivative'' (PID) control algorithm and combined with various feedforward terms, to generate compensating commands to the phase-controlled thyristor rectifiers which drive current through the OH coils. The plasma position is controlled by adjusting the currents in Equilibrium Field and Horizontal Field coil systems, which respectively determine the vertical and radial external magnetic fields producing J X B forces on the plasma current. The plasma major radius position and vertical position, sensed by ''B /sub theta/ '' and ''B /sub rho/ '' magnetic flux pickup coils with their associated electronics, are controlled toward preprogrammed reference histories by allowing PID and feedforward control algorithms to generate commands to the EF and HF coil power supplies. Plasma density is controlled by adjusting the amount of gas injected into the vacuum vessel. Time-varying gains are used to combine lineaveraged plasma density measurements from a microwave interferometer plasma diagnostic system with vacuum vessel pressure measurements from ion gauges, with various other measurements, and with preprogrammed reference histories, to determine commands to piezoelectric gas injection valves

  9. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  10. Multi-bunch Feedback Systems

    OpenAIRE

    Lonza, M.; Schmickler, H.

    2016-01-01

    Coupled-bunch instabilities excited by the interaction of the particle beam with its surroundings can seriously limit the performance of circular particle accelerators. These instabilities can be cured by the use of active feedback systems based on sensors capable of detecting the unwanted beam motion and actuators that apply the feedback correction to the beam. Advances in electronic technology now allow the implementation of feedback loops using programmable digital systems. Besides importa...

  11. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  12. Feedback Systems for Linear Colliders

    International Nuclear Information System (INIS)

    1999-01-01

    Feedback systems are essential for stable operation of a linear collider, providing a cost-effective method for relaxing tight tolerances. In the Stanford Linear Collider (SLC), feedback controls beam parameters such as trajectory, energy, and intensity throughout the accelerator. A novel dithering optimization system which adjusts final focus parameters to maximize luminosity contributed to achieving record performance in the 1997-98 run. Performance limitations of the steering feedback have been investigated, and improvements have been made. For the Next Linear Collider (NLC), extensive feedback systems are planned as an integral part of the design. Feedback requirements for JLC (the Japanese Linear Collider) are essentially identical to NLC; some of the TESLA requirements are similar but there are significant differences. For NLC, algorithms which incorporate improvements upon the SLC implementation are being prototyped. Specialized systems for the damping rings, rf and interaction point will operate at high bandwidth and fast response. To correct for the motion of individual bunches within a train, both feedforward and feedback systems are planned. SLC experience has shown that feedback systems are an invaluable operational tool for decoupling systems, allowing precision tuning, and providing pulse-to-pulse diagnostics. Feedback systems for the NLC will incorporate the key SLC features and the benefits of advancing technologies

  13. Multi-bunch Feedback Systems

    CERN Document Server

    Lonza, M.

    2014-12-19

    Coupled-bunch instabilities excited by the interaction of the particle beam with its surroundings can seriously limit the performance of circular particle accelerators. These instabilities can be cured by the use of active feedback systems based on sensors capable of detecting the unwanted beam motion and actuators that apply the feedback correction to the beam. Advances in electronic technology now allow the implementation of feedback loops using programmable digital systems. Besides important advantages in terms of flexibility and reproducibility, digital systems open the way to the use of novel diagnostic tools and additional features. We first introduce coupled-bunch instabilities, analysing the equation of motion of charged particles and the different modes of oscillation of a multi-bunch beam, showing how they can be observed and measured. Different types of feedback systems will then be presented as examples of real implementations that belong to the history of multi-bunch feedback systems. The main co...

  14. Multi-bunch Feedback Systems

    International Nuclear Information System (INIS)

    Lonza, M; Schmickler, H

    2014-01-01

    Coupled-bunch instabilities excited by the interaction of the particle beam with its surroundings can seriously limit the performance of circular particle accelerators. These instabilities can be cured by the use of active feedback systems based on sensors capable of detecting the unwanted beam motion and actuators that apply the feedback correction to the beam. Advances in electronic technology now allow the implementation of feedback loops using programmable digital systems. Besides important advantages in terms of flexibility and reproducibility, digital systems open the way to the use of novel diagnostic tools and additional features. We first introduce coupled-bunch instabilities, analysing the equation of motion of charged particles and the different modes of oscillation of a multi-bunch beam, showing how they can be observed and measured. Different types of feedback systems will then be presented as examples of real implementations that belong to the history of multi-bunch feedback systems. The main components of a feedback system and the related issues will also be analysed. Finally, we shall focus on digital feedback systems, their characteristics, and features, as well as on how they can be concretely exploited for both the optimization of feedback performance and for beam dynamics studies

  15. Multi-bunch feedback systems

    CERN Document Server

    Lonza, M

    2008-01-01

    Coupled-bunch instabilities excited by the interaction of the particle beam with its surroundings can seriously limit the performance of circular particle accelerators. These instabilities can be cured by the use of active feedback systems based on sensors capable of detecting the unwanted beam motion and actuators that apply the feedback correction to the beam. The advances in electronic technology now allow the implementation of feedback loops using programmable digital systems. Besides important advantages in terms of flexibility and reproducibility, digital systems open the way to the use of novel diagnostic tools and additional features. The lecture will first introduce coupled-bunch instabilities analysing the equation of motion of charged particles and the different modes of oscillation of a multi-bunch beam, showing how they can be observed and measured. Different types of feedbacks systems will then be presented as examples of real implementations that belong to the history of multi-bunch feedback sy...

  16. Feedback systems for linear colliders

    CERN Document Server

    Hendrickson, L; Himel, Thomas M; Minty, Michiko G; Phinney, N; Raimondi, Pantaleo; Raubenheimer, T O; Shoaee, H; Tenenbaum, P G

    1999-01-01

    Feedback systems are essential for stable operation of a linear collider, providing a cost-effective method for relaxing tight tolerances. In the Stanford Linear Collider (SLC), feedback controls beam parameters such as trajectory, energy, and intensity throughout the accelerator. A novel dithering optimization system which adjusts final focus parameters to maximize luminosity contributed to achieving record performance in the 1997-98 run. Performance limitations of the steering feedback have been investigated, and improvements have been made. For the Next Linear Collider (NLC), extensive feedback systems are planned as an intregal part of the design. Feedback requiremetns for JLC (the Japanese Linear Collider) are essentially identical to NLC; some of the TESLA requirements are similar but there are significant differences. For NLC, algorithms which incorporate improvements upon the SLC implementation are being prototyped. Specialized systems for the damping rings, rf and interaction point will operate at hi...

  17. A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

    Directory of Open Access Journals (Sweden)

    Christopher L Buckley

    2018-01-01

    Full Text Available During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results

  18. A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

    Science.gov (United States)

    Buckley, Christopher L; Toyoizumi, Taro

    2018-01-01

    During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence

  19. Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

    Directory of Open Access Journals (Sweden)

    Rong Mei

    2017-01-01

    Full Text Available This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.

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

    Science.gov (United States)

    Wan, Ying; Cao, Jinde; Wen, Guanghui

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

  1. Identification of neural structures involved in stuttering using vibrotactile feedback.

    Science.gov (United States)

    Cheadle, Oliver; Sorger, Clarissa; Howell, Peter

    Feedback delivered over auditory and vibratory afferent pathways has different effects on the fluency of people who stutter (PWS). These features were exploited to investigate the neural structures involved in stuttering. The speech signal vibrated locations on the body (vibrotactile feedback, VTF). Eleven PWS read passages under VTF and control (no-VTF) conditions. All combinations of vibration amplitude, synchronous or delayed VTF and vibrator position (hand, sternum or forehead) were presented. Control conditions were performed at the beginning, middle and end of test sessions. Stuttering rate, but not speaking rate, differed between the control and VTF conditions. Notably, speaking rate did not change between when VTF was delayed versus when it was synchronous in contrast with what happens with auditory feedback. This showed that cerebellar mechanisms, which are affected when auditory feedback is delayed, were not implicated in the fluency-enhancing effects of VTF, suggesting that there is a second fluency-enhancing mechanism. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Two-Layer Feedback Neural Networks with Associative Memories

    International Nuclear Information System (INIS)

    Gui-Kun, Wu; Hong, Zhao

    2008-01-01

    We construct a two-layer feedback neural network by a Monte Carlo based algorithm to store memories as fixed-point attractors or as limit-cycle attractors. Special attention is focused on comparing the dynamics of the network with limit-cycle attractors and with fixed-point attractors. It is found that the former has better retrieval property than the latter. Particularly, spurious memories may be suppressed completely when the memories are stored as a long-limit cycle. Potential application of limit-cycle-attractor networks is discussed briefly. (general)

  3. Recognition of boundary feedback systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1989-01-01

    A system that has been the object of intense research is outlined. In view of that and recent progress of the theory of pseudodifferential boundary operator calculus, the author describes some features that could prove to be interesting in connection with the problems of boundary feedback stabili...... stabilizability. It is shown that it is possible to use the calculus to consider more general feedback systems in a variational setup.......A system that has been the object of intense research is outlined. In view of that and recent progress of the theory of pseudodifferential boundary operator calculus, the author describes some features that could prove to be interesting in connection with the problems of boundary feedback...

  4. RF and feedback systems

    International Nuclear Information System (INIS)

    Boussard, D.

    1994-01-01

    The radiofrequency system of the Tau Charm Factory accelerating 10 11 particles per bunch and a circulating current of 0.5 A is presented. In order to produce the very short bunches required, the RF system of TCF must provide a large RF voltage (8 MV) at a frequency in the neighbourhood of 400-500 MHz. It appears very attractive to produce the high voltage required with superconducting cavities, for which wall losses are negligible. A comparison between the sc RF system proposed and a possible copper system run at an average 1 MV/m, shows the clear advantage of sc cavities for TCF. (R.P.). 2 figs,. 1 tab

  5. Longitudinal feedback system for PEP

    International Nuclear Information System (INIS)

    Allen, M.A.; Cornacchia, M.; Millich, A.

    1979-02-01

    Whether the wide bandwidth longitudinal feedback system described in this paper is made to act on the individual modes in frequency domain or on the individual bunches in time domain, it represents a clean and efficient way of damping the longitudinal oscillations without influencing other beam parameters such as bunch shape or synchrotron frequency distribution. The frequency domain feedback presents the advantage of providing information on which modes are unstable and on their risetimes, which may be helpful in locating dangerous resonators in the ring

  6. Feedback coupling in dynamical systems

    Science.gov (United States)

    Trimper, Steffen; Zabrocki, Knud

    2003-05-01

    Different evolution models are considered with feedback-couplings. In particular, we study the Lotka-Volterra system under the influence of a cumulative term, the Ginzburg-Landau model with a convolution memory term and chemical rate equations with time delay. The memory leads to a modified dynamical behavior. In case of a positive coupling the generalized Lotka-Volterra system exhibits a maximum gain achieved after a finite time, but the population will die out in the long time limit. In the opposite case, the time evolution is terminated in a crash. Due to the nonlinear feedback coupling the two branches of a bistable model are controlled by the the strength and the sign of the memory. For a negative coupling the system is able to switch over between both branches of the stationary solution. The dynamics of the system is further controlled by the initial condition. The diffusion-limited reaction is likewise studied in case the reacting entities are not available simultaneously. Whereas for an external feedback the dynamics is altered, but the stationary solution remain unchanged, a self-organized internal feedback leads to a time persistent solution.

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

    Science.gov (United States)

    Dierks, Travis; Jagannathan, Sarangapani

    2010-01-01

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

  8. Pilot acute study of feedback-controlled retrograde peristalsis invoked by neural gastric electrical stimulation

    International Nuclear Information System (INIS)

    Aelen, P; Jurkov, A; Aulanier, A; Mintchev, M P

    2009-01-01

    Neural gastric electrical stimulation (NGES) is a new method for invoking gastric contractions under microprocessor control. However, optimization of this technique using feedback mechanisms to minimize power consumption and maximize effectiveness has been lacking. The present pilot study proposes a prototype feedback-controlled neural gastric electric stimulator for the treatment of obesity. Both force-based and inter-electrode impedance-based feedback neurostimulators were implemented and tested. Four mongrel dogs (2 M, 2 F, weight 14.9 ± 2.3 kg) underwent subserosal implantation of two-channel, 1 cm, bipolar electrode leads and two force transducers in the distal antrum. Two of the dogs were stimulated with a force feedback system utilizing the force transducers, and the other two animals were stimulated utilizing an inter-electrode impedance-based feedback system utilizing the proximal electrode leads. Both feedback systems were able to recognize erythromycin-driven contractions of the stomach and were capable of overriding them with NGES-invoked retrograde contractions which exceeded the magnitudes of the erythromycin-driven contractions by an average of 100.6 ± 33.5% in all animals. The NGES-invoked contractions blocked the erythromycin-driven contractions past the proximal electrode pair and induced temporary gastroparesis in the vicinity of the distal force transducer despite the continuing erythromycin infusion. The amplitudes of the erythromycin-invoked contractions in the vicinity of the proximal force transducer decreased abruptly by an average of 47.9 ± 6.3% in all four dogs after triggering-invoked retrograde contractions, regardless of the specific feedback-controlled mechanism. The proposed technique could be helpful for retaining food longer in the stomach, thus inducing early satiety and diminishing food intake

  9. Daresbury SRS Positional Feedback Systems

    CERN Document Server

    Smith, S L

    2000-01-01

    The Daresbury SRS is a second generation synchrotron radiation source which ramps from its injection energy of 600 MeV to 2.0 GeV. Beam orbit feedback systems have been in routine operation on the SRS since 1994 and are now an essential element in delivering stable photon beams to experimental stations. The most recent enhancements to these systems have included the introduction of a ramp servo system to provide the orbit control demanded by the installation of two new narrow gap insertion device and development of the vertical orbit feedback system to cope with an increasing number of photon beamlines. This paper summaries the current status of these systems and briefly discusses proposed developments.

  10. Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

    Science.gov (United States)

    Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

    2010-09-01

    This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

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

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  12. Neural Feedback Scheduling of Real-Time Control Tasks

    OpenAIRE

    Xia, Feng; Tian, Yu-Chu; Sun, Youxian; Dong, Jinxiang

    2008-01-01

    Many embedded real-time control systems suffer from resource constraints and dynamic workload variations. Although optimal feedback scheduling schemes are in principle capable of maximizing the overall control performance of multitasking control systems, most of them induce excessively large computational overheads associated with the mathematical optimization routines involved and hence are not directly applicable to practical systems. To optimize the overall control performance while minimi...

  13. Theory of multi-bunch feedback systems

    International Nuclear Information System (INIS)

    Kohaupt, R.D.

    1991-06-01

    In this article the theory of multibunch feedback systems is developed in a rigorous way including the fact that the elements of feedback systems are localized in the ring. The results of the theory which can be used for any strength of the systems are the base for the multibunch feedback systems for PETRA and HERA, already tested successfully in PETRA. (orig.)

  14. Wideband feedback system prototype validation

    CERN Document Server

    Li, K; Bjorsvik, E; Fox, J; Hofle, W; Kotzian, G; Rivetta, C; Salvant, B; Turgut, O

    2017-01-01

    A wideband feedback demonstrator system has been de-veloped in collaboration with US-LARP under the joint lead-ership of CERN and SLAC. The system includes widebandkicker structures and amplifiers along with a fast digital re-configurable system up to 4 GS/s for single bunch and multibunch control. Most of the components have been installedin recent years and have been put into operation to test bothintra-bunch damping and individual bunch control in a multibunch train. In this note we report on the MD program,procedure and key findings that were made with this systemin the past year.

  15. Design, implementation and testing of an implantable impedance-based feedback-controlled neural gastric stimulator

    International Nuclear Information System (INIS)

    Arriagada, A J; Jurkov, A S; Mintchev, M P; Neshev, E; Andrews, C N; Muench, G

    2011-01-01

    Functional neural gastrointestinal electrical stimulation (NGES) is a methodology of gastric electrical stimulation that can be applied as a possible treatment for disorders such as obesity and gastroparesis. NGES is capable of generating strong lumen-occluding local contractions that can produce retrograde or antegrade movement of gastric content. A feedback-controlled implantable NGES system has been designed, implemented and tested both in laboratory conditions and in an acute animal setting. The feedback system, based on gastric tissue impedance change, is aimed at reducing battery energy requirements and managing the phenomenon of gastric tissue accommodation. Acute animal testing was undertaken in four mongrel dogs (2 M, 2 F, weight 25.53 ± 7.3 kg) that underwent subserosal two-channel electrode implantation. Three force transducers sutured serosally along the gastric axis and a wireless signal acquisition system were utilized to record stimulation-generated contractions and tissue impedance variations respectively. Mechanically induced contractions in the stomach were utilized to indirectly generate a tissue impedance change that was detected by the feedback system. Results showed that increasing or decreasing impedance changes were detected by the implantable stimulator and that therapy can be triggered as a result. The implantable feedback system brings NGES one step closer to long term treatment of burdening gastric motility disorders in humans

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

    Science.gov (United States)

    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.

  17. Neural correlates of anticipation and processing of performance feedback in social anxiety.

    Science.gov (United States)

    Heitmann, Carina Y; Peterburs, Jutta; Mothes-Lasch, Martin; Hallfarth, Marlit C; Böhme, Stephanie; Miltner, Wolfgang H R; Straube, Thomas

    2014-12-01

    Fear of negative evaluation, such as negative social performance feedback, is the core symptom of social anxiety. The present study investigated the neural correlates of anticipation and perception of social performance feedback in social anxiety. High (HSA) and low (LSA) socially anxious individuals were asked to give a speech on a personally relevant topic and received standardized but appropriate expert performance feedback in a succeeding experimental session in which neural activity was measured during anticipation and presentation of negative and positive performance feedback concerning the speech performance, or a neutral feedback-unrelated control condition. HSA compared to LSA subjects reported greater anxiety during anticipation of negative feedback. Functional magnetic resonance imaging results showed deactivation of medial prefrontal brain areas during anticipation of negative feedback relative to the control and the positive condition, and medial prefrontal and insular hyperactivation during presentation of negative as well as positive feedback in HSA compared to LSA subjects. The results indicate distinct processes underlying feedback processing during anticipation and presentation of feedback in HSA as compared to LSA individuals. In line with the role of the medial prefrontal cortex in self-referential information processing and the insula in interoception, social anxiety seems to be associated with lower self-monitoring during feedback anticipation, and an increased self-focus and interoception during feedback presentation, regardless of feedback valence. © 2014 Wiley Periodicals, Inc.

  18. Adaptive feedback synchronization of Lue system

    International Nuclear Information System (INIS)

    Han, X.; Lu, J.-A.; Wu, X.

    2004-01-01

    This letter further improves and extends the works of Chen and Lue [Chaos, Solitons and Fractals 14 (2002) 643] and Wang et al. [Phys. Lett. A 312 (2003) 34]. In detail, the linear feedback synchronization and adaptive feedback synchronization for Lue system are discussed. And the lower bound of the feedback gain in linear feedback synchronization is presented. The adaptive feedback synchronization with only one controller is designed, which improves the proof in the work by Wang et al. The adaptive synchronization with two controllers for completely uncertain Lue system is also discussed, which extends the work of Chen and Lue. Also, numerical simulations show the effectiveness of these methods

  19. Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

    Science.gov (United States)

    Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut

    2016-01-01

    Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

  20. Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

    Directory of Open Access Journals (Sweden)

    Waddah Waheeb

    Full Text Available Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN and the Dynamic Ridge Polynomial Neural Network (DRPNN. Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

  1. Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

    Science.gov (United States)

    Daniel, Reka; Pollmann, Stefan

    2010-01-06

    The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

  2. Neural control of magnetic suspension systems

    Science.gov (United States)

    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.

  3. Real-time system for studies of the effects of acoustic feedback on animal vocalizations.

    Directory of Open Access Journals (Sweden)

    Mike eSkocik

    2013-01-01

    Full Text Available Studies of behavioral and neural responses to distorted auditory feedback can help shed light on the neural mechanisms of animal vocalizations. We describe an apparatus for generating real-time acoustic feedback. The system can very rapidly detect acoustic features in a song and output acoustic signals if the detected features match the desired acoustic template. The system uses spectrogram-based detection of acoustic elements. It is low-cost and can be programmed for a variety of behavioral experiments requiring acoustic feedback or neural stimulation. We use the system to study the effects of acoustic feedback on birds' vocalizations and demonstrate that such an acoustic feedback can cause both immediate and long-term changes to birds’ songs.

  4. Feedback systems in the SLC

    International Nuclear Information System (INIS)

    Thompson, K.A.; Jobe, R.K.; Johnson, R.; Phinney, N.

    1987-02-01

    Two classes of computer-controlled feedback have been implemented to stabilize parameters in subsystems of the SLC: (1) ''slow'' (time scales ∼ minutes) feedback, and (2) ''fast'', i.e., pulse-to-pulse, feedback. The slow loops run in a single FEEDBACK process in the SLC host VAX, which acquires signals and sets control parameters via communication with the database and the network of normal SLC microprocessors. Slow loops exist to stabilize beam energy and energy spread, beam position and angle, and timing of kicker magnets, and to compensate for changes in the phase length of the rf drive line. The fast loops run in dedicated microprocessors, and may sample and/or feedback on particular parameters as often as every pulse of the SLC beam. The first implementations of fast feedback are to control transverse beam blow-up and to stabilize the energy and energy spread of bunches going into the SLC arcs. The overall architecture of the feedback software and the operator interface for controlling loops are discussed

  5. Evaluating the negative or valuing the positive? Neural mechanisms supporting feedback-based learning across development.

    Science.gov (United States)

    van Duijvenvoorde, Anna C K; Zanolie, Kiki; Rombouts, Serge A R B; Raijmakers, Maartje E J; Crone, Eveline A

    2008-09-17

    How children learn from positive and negative performance feedback lies at the foundation of successful learning and is therefore of great importance for educational practice. In this study, we used functional magnetic resonance imaging (fMRI) to examine the neural developmental changes related to feedback-based learning when performing a rule search and application task. Behavioral results from three age groups (8-9, 11-13, and 18-25 years of age) demonstrated that, compared with adults, 8- to 9-year-old children performed disproportionally more inaccurately after receiving negative feedback relative to positive feedback. Additionally, imaging data pointed toward a qualitative difference in how children and adults use performance feedback. That is, dorsolateral prefrontal cortex and superior parietal cortex were more active after negative feedback for adults, but after positive feedback for children (8-9 years of age). For 11- to 13-year-olds, these regions did not show differential feedback sensitivity, suggesting that the transition occurs around this age. Pre-supplementary motor area/anterior cingulate cortex, in contrast, was more active after negative feedback in both 11- to 13-year-olds and adults, but not 8- to 9-year-olds. Together, the current data show that cognitive control areas are differentially engaged during feedback-based learning across development. Adults engage these regions after signals of response adjustment (i.e., negative feedback). Young children engage these regions after signals of response continuation (i.e., positive feedback). The neural activation patterns found in 11- to 13-year-olds indicate a transition around this age toward an increased influence of negative feedback on performance adjustment. This is the first developmental fMRI study to compare qualitative changes in brain activation during feedback learning across distinct stages of development.

  6. Neural Correlates of Feedback Processing in Decision Making under Risk

    Directory of Open Access Journals (Sweden)

    Beate eSchuermann

    2012-07-01

    Full Text Available Introduction. Event-related brain potentials (ERP provide important information about the sensitivity of the brain to process varying risks. The aim of the present study was to determine how different risk levels are reflected in decision-related ERPs, namely the feedback-related negativity (FRN and the P300. Material and Methods. 20 participants conducted a probabilistic two-choice gambling task while an electroencephalogram was recorded. Choices were provided between a low-risk option yielding low rewards and low losses and a high-risk option yielding high rewards and high losses. While options differed in expected risks, they were equal in expected values and in feedback probabilities. Results. At the behavioral level, participants were generally risk-averse but modulated their risk-taking behavior according to reward history. An early positivity (P200 was enhanced on negative feedbacks in high-risk compared to low-risk options. With regard to the FRN, there were significant amplitude differences between positive and negative feedbacks in high-risk options, but not in low-risk options. While the FRN on negative feedbacks did not vary with decision riskiness, reduced amplitudes were found for positive feedbacks in high-risk relative to low-risk choices. P300 amplitudes were larger in high-risk decisions, and in an additive way, after negative compared to positive feedback. Discussion. The present study revealed significant influences of risk and valence processing on ERPs. FRN findings suggest that the reward prediction error signal is increased after high-risk decisions. The increased P200 on negative feedback in risky decisions suggests that large negative prediction errors are processed as early as in the P200 time range. The later P300 amplitude is sensitive to feedback valence as well as to the risk of a decision. Thus, the P300 carries additional information for reward processing, mainly the enhanced motivational significance of risky

  7. Generalized fast feedback system in the SLC

    International Nuclear Information System (INIS)

    Hendrickson, L.; Allison, S.; Gromme, T.; Himel, T.; Krauter, K.; Rouse, F.; Sass, R.; Shoaee, H.

    1992-01-01

    A generalized fast feedback system has been developed to stabilize beams at various locations in the SLC. The system is designed to perform measurements and change actuator settings to control beam states such as position, angle and energy on a pulse to pulse basis. The software design is based on the state space formalism of digital control theory. The system is database-driven, facilitating the addition of new loops without requiring additional software. A communications system, KISNet, provides fast communications links between microprocessors for feedback loops which involve multiple micros. Feedback loops have been installed in seventeen locations throughout the SLC and have proven to be invaluable in stabilizing the machine. (author)

  8. Generalized fast feedback system in the SLC

    International Nuclear Information System (INIS)

    Hendrickson, L.; Allison, S.; Gromme, T.; Himel, T.; Krauter, K.; Rouse, F.; Sass, R.; Shoaee, H.

    1991-11-01

    A generalized fast feedback system has been developed to stabilize beams at various locations in the SLC. The system is designed to perform measurements and change actuator settings to control beam states such as position, angle and energy on a pulse to pulse basis. The software design is based on the state space formalism of digital control theory. The system is database-driven, facilitating the addition of new loops without requiring additional software. A communications system, KISNet, provides fast communications links between microprocessors for feedback loops which involve multiple micros. Feedback loops have been installed in seventeen locations throughout the SLC and have proven to be invaluable in stabilizing the machine

  9. Neural activations associated with feedback and retrieval success

    Science.gov (United States)

    Wiklund-Hörnqvist, Carola; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

    2017-11-01

    There is substantial behavioral evidence for a phenomenon commonly called "the testing effect", i.e. superior memory performance after repeated testing compared to re-study of to-be-learned materials. However, considerably less is known about the underlying neuro-cognitive processes that are involved in the initial testing phase, and thus underlies the actual testing effect. Here, we investigated functional brain activity related to test-enhanced learning with feedback. Subjects learned foreign vocabulary across three consecutive tests with correct-answer feedback. Functional brain-activity responses were analyzed in relation to retrieval and feedback events, respectively. Results revealed up-regulated activity in fronto-striatal regions during the first successful retrieval, followed by a marked reduction in activity as a function of improved learning. Whereas feedback improved behavioral performance across consecutive tests, feedback had a negligable role after the first successful retrieval for functional brain-activity modulations. It is suggested that the beneficial effects of test-enhanced learning is regulated by feedback-induced updating of memory representations, mediated via the striatum, that might underlie the stabilization of memory commonly seen in behavioral studies of the testing effect.

  10. Global Control of the Furuta Pendulum Using Artificial Neural Networks and Feedback of State Variables

    Directory of Open Access Journals (Sweden)

    Luisa F. Escobar-Dávila

    2013-06-01

    Full Text Available This paper presents the mathematical modeling of the Furuta Pendu-lum by power functions, taking into account the non linear own dynamics of the physical systems and considering the existing couplings between the electric and mechanic devices. A control process based on feedback of state variables (FSV for the equilibrium point is developed and two topics for the non linear zone are addressed. First of all, functions are implemented to represent the energetic states of the plant in a global way and the operation regions are established (“Swing up” zone, and later Artificial Neural Networks (ANN are employed to simulate the behavior of the energy functions. Finally, it is presented the combination between the control techniques, considering the own constrains of the actuators and sensors used, besides of this, a study is done in a simulated environment of the physical phenomena that may disturb system behavior, and the capacity, sensitivity and robustness of the controller is verified.

  11. Operation of PEP longitudinal feedback system

    International Nuclear Information System (INIS)

    Allen, M.A.; Karvonen, L.G.; McConnell, R.A.; Schwarz, H.

    1981-03-01

    In order to suppress longitudinal coupled-bunch oscillations which might limit the capabilities of PEP, the 18 GeV e + e - storage ring at SLAC, a longitudinal feedback system is utilized. A frequency domain feedback system was chosen with the frequency spectrum of the stored beam being sampled close to a symmetry point in the ring where the feedback cavity itself is also located. The symmetry point chosen is symmetry point 5 which lies half-way between interaction regions 4 and 6. The system has been installed in PEP and is now operational. However, at stored currents up to the maximum stored in PEP to date at 14.5 GeV (approximately 40 mA in 6 bunches), the ring has been stable to all modes of longitudinal coupled-bunch oscillations both barycentric and the other fundamental modes. By deliberately detuning the main accelerating cavities, small multibunch oscillations can be introduced which, in turn, can be damped by the feedback system. Under optimized beam conditions the feedback system could be adjusted to positive feedback and excite oscillations with relatively small power to the feedback cavity. This will be described along with other details of the system

  12. RHIC 10 Hz global orbit feedback system

    International Nuclear Information System (INIS)

    Michnoff, R.; Arnold, L.; Carboni, L.; Cerniglia, P.; Curcio, A.; DeSanto, L.; Folz, C.; Ho, C.; Hoff, L.; Hulsart, R.; Karl, R.; Luo, Y.; Liu, C.; MacKay, W.; Mahler, G.; Meng, W.; Mernick, K.; Minty, M.; Montag, C.; Olsen, R.; Piacentino, J.; Popken, P.; Przybylinski, R.; Ptitsyn, V.; Ritter, J.; Schoenfeld, R.; Thieberger, P.; Tuozzolo, J.; Weston, A.; White, J.; Ziminski, P.; Zimmerman, P.

    2011-01-01

    Vibrations of the cryogenic triplet magnets at the Relativistic Heavy Ion Collider (RHIC) are suspected to be causing the horizontal beam perturbations observed at frequencies around 10 Hz. Several solutions to counteract the effect have been considered in the past, including a local beam feedback system at each of the two experimental areas, reinforcing the magnet base support assembly, and a mechanical servo feedback system. However, the local feedback system was insufficient because perturbation amplitudes outside the experimental areas were still problematic, and the mechanical solutions are very expensive. A global 10 Hz orbit feedback system consisting of 36 beam position monitors (BPMs) and 12 small dedicated dipole corrector magnets in each of the two 3.8 km circumference counter-rotating rings has been developed and commissioned in February 2011. A description of the system architecture and results with beam will be discussed.

  13. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  14. Augmenting Environmental Interaction in Audio Feedback Systems

    Directory of Open Access Journals (Sweden)

    Seunghun Kim

    2016-04-01

    Full Text Available Audio feedback is defined as a positive feedback of acoustic signals where an audio input and output form a loop, and may be utilized artistically. This article presents new context-based controls over audio feedback, leading to the generation of desired sonic behaviors by enriching the influence of existing acoustic information such as room response and ambient noise. This ecological approach to audio feedback emphasizes mutual sonic interaction between signal processing and the acoustic environment. Mappings from analyses of the received signal to signal-processing parameters are designed to emphasize this specificity as an aesthetic goal. Our feedback system presents four types of mappings: approximate analyses of room reverberation to tempo-scale characteristics, ambient noise to amplitude and two different approximations of resonances to timbre. These mappings are validated computationally and evaluated experimentally in different acoustic conditions.

  15. Synchronization of cellular neural networks of neutral type via dynamic feedback controller

    International Nuclear Information System (INIS)

    Park, Ju H.

    2009-01-01

    In this paper, we aim to study global synchronization for neural networks with neutral delay. A dynamic feedback control scheme is proposed to achieve the synchronization between drive network and response network. By utilizing the Lyapunov function and linear matrix inequalities (LMIs), we derive simple and efficient criterion in terms of LMIs for synchronization. The feedback controllers can be easily obtained by solving the derived LMIs.

  16. Ideomotor feedback control in a recurrent neural network.

    Science.gov (United States)

    Galtier, Mathieu

    2015-06-01

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

  17. Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control

    International Nuclear Information System (INIS)

    Cui Baotong; Lou Xuyang

    2009-01-01

    In this paper, a new method to synchronize two identical chaotic recurrent neural networks is proposed. Using the drive-response concept, a nonlinear feedback control law is derived to achieve the state synchronization of the two identical chaotic neural networks. Furthermore, based on the Lyapunov method, a delay independent sufficient synchronization condition in terms of linear matrix inequality (LMI) is obtained. A numerical example with graphical illustrations is given to illuminate the presented synchronization scheme

  18. Non-linear feedback neural networks VLSI implementations and applications

    CERN Document Server

    Ansari, Mohd Samar

    2014-01-01

    This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

  19. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  20. Feedbacks in human-landscape systems

    Science.gov (United States)

    Chin, Anne

    2015-04-01

    As human interactions with Earth systems intensify in the "Anthropocene", understanding the complex relationships among human activity, landscape change, and societal responses to those changes is increasingly important. Interdisciplinary research centered on the theme of "feedbacks" in human-landscape systems serves as a promising focus for unraveling these interactions. Deciphering interacting human-landscape feedbacks extends our traditional approach of considering humans as unidirectional drivers of change. Enormous challenges exist, however, in quantifying impact-feedback loops in landscapes with significant human alterations. This paper illustrates an example of human-landscape interactions following a wildfire in Colorado (USA) that elicited feedback responses. After the 2012 Waldo Canyon Fire, concerns for heightened flood potential and debris flows associated with post-fire hydrologic changes prompted local landowners to construct tall fences at the base of a burned watershed. These actions changed the sediment transport regime and promoted further landscape change and human responses in a positive feedback cycle. The interactions ultimately increase flood and sediment hazards, rather than dampening the effects of fire. A simple agent-based model, capable of integrating social and hydro-geomorphological data, demonstrates how such interacting impacts and feedbacks could be simulated. Challenges for fully capturing human-landscape feedback interactions include the identification of diffuse and subtle feedbacks at a range of scales, the availability of data linking impact with response, the identification of multiple thresholds that trigger feedback mechanisms, and the varied metrics and data needed to represent both the physical and human systems. By collaborating with social scientists with expertise in the human causes of landscape change, as well as the human responses to those changes, geoscientists could more fully recognize and anticipate the coupled

  1. Novel Reduced-Feedback Wireless Communication Systems

    KAUST Repository

    Shaqfeh, Mohammad Obaidah; Alnuweiri, Hussein; Alouini, Mohamed-Slim

    2011-01-01

    We have recently contributed to this field and published several journal and conference papers. We are the pioneers to propose a novel reduced-feedback opportunistic scheduling scheme that combines many desired features including fairness in resources distribution across the active terminals and distributed processing at the MAC layer level. In addition our scheme operates close to the upper capacity limits of achievable transmission rates over wireless links. We have also proposed another hybrid scheme that enables adjusting the feedback load flexibly based on rates requirements. We are currently investigating other novel ideas to design reduced-feedback communication systems.

  2. Hybrid feedback feedforward: An efficient design of adaptive neural network control.

    Science.gov (United States)

    Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong

    2016-04-01

    This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. The importance of cutaneous feedback on neural activation during maximal voluntary contraction

    NARCIS (Netherlands)

    Cruz-Montecinos, Carlos; Maas, Huub; Pellegrin-Friedmann, Carla; Tapia, Claudio

    2017-01-01

    Purpose: The purpose of this study was to investigate the importance of cutaneous feedback on neural activation during maximal voluntary contraction (MVC) of the ankle plantar flexors. Methods: The effects of cutaneous plantar anaesthesia were assessed in 15 subjects and compared to 15 controls,

  4. Strategies influence neural activity for feedback learning across child and adolescent development.

    Science.gov (United States)

    Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

    2014-09-01

    Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Developing 360 degree feedback system for KINS

    International Nuclear Information System (INIS)

    Han, In Soo; Cheon, B. M.; Kim, T. H.; Ryu, J. H.

    2003-12-01

    This project aims to investigate the feasibility of a 360 degree feedback systems for KINS and to design guiding rules and structures in implementing that systems. Literature survey, environmental analysis and questionnaire survey were made to ensure that 360 degree feedback is the right tool to improve performance in KINS. That review leads to conclusion that more readiness and careful feasibility review are needed before implementation of 360 degree feedback in KINS. Further the project suggests some guiding rules that can be helpful for successful implementation of that system in KINS. Those include : start with development, experiment with one department, tie it to a clear organization's goal, train everyone involve, make sure to try that system in an atmosphere of trust

  6. Developing 360 degree feedback system for KINS

    Energy Technology Data Exchange (ETDEWEB)

    Han, In Soo; Cheon, B. M.; Kim, T. H.; Ryu, J. H. [Chungman National Univ., Daejeon (Korea, Republic of)

    2003-12-15

    This project aims to investigate the feasibility of a 360 degree feedback systems for KINS and to design guiding rules and structures in implementing that systems. Literature survey, environmental analysis and questionnaire survey were made to ensure that 360 degree feedback is the right tool to improve performance in KINS. That review leads to conclusion that more readiness and careful feasibility review are needed before implementation of 360 degree feedback in KINS. Further the project suggests some guiding rules that can be helpful for successful implementation of that system in KINS. Those include : start with development, experiment with one department, tie it to a clear organization's goal, train everyone involve, make sure to try that system in an atmosphere of trust.

  7. PEP-II RF feedback system simulation

    Energy Technology Data Exchange (ETDEWEB)

    Tighe, R [Stanford Linear Accelerator Center, Menlo Park, CA (United States)

    1996-08-01

    A model containing the fundamental impedance of the PEP-II cavity along with the longitudinal beam dynamics and RF feedback system components is in use. It is prepared in a format allowing time-domain as well as frequency-domain analysis and full graphics capability. Matlab and Simulink are control system design and analysis programs (widely available) with many built-in tools. The model allows the use of compiled C-code modules for compute intensive portions. We desire to represent as nearly as possible the components of the feedback system including all delays, sample rates and applicable nonlinearities. (author)

  8. The fast correction coil feedback control system

    International Nuclear Information System (INIS)

    Coffield, F.; Caporaso, G.; Zentler, J.M.

    1989-01-01

    A model-based feedback control system has been developed to correct beam displacement errors in the Advanced Test Accelerator (ATA) electron beam accelerator. The feedback control system drives an X/Y dipole steering system that has a 40-MHz bandwidth and can produce ±300-Gauss-cm dipole fields. A simulator was used to develop the control algorithm and to quantify the expected performance in the presence of beam position measurement noise and accelerator timing jitter. The major problem to date has been protecting the amplifiers from the voltage that is inductively coupled to the steering bars by the beam. 3 refs., 8 figs

  9. Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Miriam eZacksenhouse

    2015-05-01

    Full Text Available Recent experiments with brain-machine-interfaces (BMIs indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

  10. Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces.

    Science.gov (United States)

    Benyamini, Miri; Zacksenhouse, Miriam

    2015-01-01

    Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

  11. Controlling chaotic systems via nonlinear feedback control

    International Nuclear Information System (INIS)

    Park, Ju H.

    2005-01-01

    In this article, a new method to control chaotic systems is proposed. Using Lyapunov method, we design a nonlinear feedback controller to make the controlled system be stabilized. A numerical example is given to illuminate the design procedure and advantage of the result derived

  12. Diversity in School Performance Feedback Systems

    Science.gov (United States)

    Verhaeghe, Goedele; Schildkamp, Kim; Luyten, Hans; Valcke, Martin

    2015-01-01

    As data-based decision making is receiving increased attention in education, more and more school performance feedback systems (SPFSs) are being developed and used worldwide. These systems provide schools with data on their functioning. However, little research is available on the characteristics of the different SPFSs. Therefore, this study…

  13. Feedback control strategies for the Liu chaotic system

    International Nuclear Information System (INIS)

    Zhu Congxu; Chen Zhigang

    2008-01-01

    This Letter proposed three strategies of the dislocated feedback control, enhancing feedback control and speed feedback control of the Liu chaotic system to its unstable equilibrium points. It is found that the coefficients of enhancing feedback control and speed feedback control are smaller than those of ordinary feedback control, so, the complexity and cost of the system control are reduced. Theoretical analysis and numerical simulation are given, revealing the effectiveness of these strategies

  14. Novel Reduced-Feedback Wireless Communication Systems

    KAUST Repository

    Shaqfeh, Mohammad Obaidah

    2011-11-20

    Modern communication systems apply channel-aware adaptive transmission techniques and dynamic resource allocation in order to exploit the peak conditions of the fading wireless links and to enable significant performance gains. However, conveying the channel state information among the users’ mobile terminals into the access points of the network consumes a significant portion of the scarce air-link resources and depletes the battery resources of the mobile terminals rapidly. Despite its evident drawbacks, the channel information feedback cannot be eliminated in modern wireless networks because blind communication technologies cannot support the ever-increasing transmission rates and high quality of experience demands of current ubiquitous services. Developing new transmission technologies with reduced-feedback requirements is sought. Network operators will benefit from releasing the bandwidth resources reserved for the feedback communications and the clients will enjoy the extended battery life of their mobile devices. The main technical challenge is to preserve the prospected transmission rates over the network despite decreasing the channel information feedback significantly. This is a noteworthy research theme especially that there is no mature theory for feedback communication in the existing literature despite the growing number of publications about the topic in the last few years. More research efforts are needed to characterize the trade-off between the achievable rate and the required channel information and to design new reduced-feedback schemes that can be flexibly controlled based on the operator preferences. Such schemes can be then introduced into the standardization bodies for consideration in next generation broadband systems. We have recently contributed to this field and published several journal and conference papers. We are the pioneers to propose a novel reduced-feedback opportunistic scheduling scheme that combines many desired features

  15. Intelligent neural network diagnostic system

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2010-01-01

    Recently, artificial neural network (ANN) has made a significant mark in the domain of diagnostic applications. Neural networks are used to implement complex non-linear mappings (functions) using simple elementary units interrelated through connections with adaptive weights. The performance of the ANN is mainly depending on their topology structure and weights. Some systems have been developed using genetic algorithm (GA) to optimize the topology of the ANN. But, they suffer from some limitations. They are : (1) The computation time requires for training the ANN several time reaching for the average weight required, (2) Slowness of GA for optimization process and (3) Fitness noise appeared in the optimization of ANN. This research suggests new issues to overcome these limitations for finding optimal neural network architectures to learn particular problems. This proposed methodology is used to develop a diagnostic neural network system. It has been applied for a 600 MW turbo-generator as a case of real complex systems. The proposed system has proved its significant performance compared to two common methods used in the diagnostic applications.

  16. PLS beam position measurement and feedback system

    International Nuclear Information System (INIS)

    Huang, J.Y.; Lee, J.; Park, M.K.; Kim, J.H.; Won, S.C.

    1992-01-01

    A real-time orbit correction system is proposed for the stabilization of beam orbit and photon beam positions in Pohang Light Source. PLS beam position monitoring system is designed to be VMEbus compatible to fit the real-time digital orbit feedback system. A VMEbus based subsystem control computer, Mil-1553B communication network and 12 BPM/PS machine interface units constitute digital part of the feedback system. With the super-stable PLS correction magnet power supply, power line frequency noise is almost filtered out and the dominant spectra of beam obtit fluctuations are expected to appear below 15 Hz. Using DSP board in SCC for the computation and using an appropriate compensation circuit for the phase delay by the vacuum chamber, PLS real-time orbit correction system is realizable without changing the basic structure of PLS computer control system. (author)

  17. Mining Feedback in Ranking and Recommendation Systems

    Science.gov (United States)

    Zhuang, Ziming

    2009-01-01

    The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

  18. Synchronization of coupled nonidentical multidelay feedback systems

    International Nuclear Information System (INIS)

    Hoang, Thang Manh; Nakagawa, Masahiro

    2007-01-01

    We present the lag synchronization of coupled nonidentical multidelay feedback systems, in which the synchronization signal is the sum of nonlinearly transformed components of delayed state variable. The sufficient condition for synchronization is considered by the Krasovskii-Lyapunov theory. The specific examples will demonstrate and verify the effectiveness of the proposed model

  19. Robust synchronization of chaotic systems via feedback

    Energy Technology Data Exchange (ETDEWEB)

    Femat, Ricardo [IPICYT, San Luis Potosi (Mexico). Dept. de Matematicas Aplicadas; Solis-Perales, Gualberto [Universidad de Guadalajara, Centro Univ. de Ciencias Exactas e Ingenierias (Mexico). Div. de Electronica y Computacion

    2008-07-01

    This volume includes the results derived during last ten years about both suppression and synchronization of chaotic -continuous time- systems. Along this time, the concept was to study how the intrinsic properties of dynamical systems can be exploited to suppress and to synchronize the chaotic behaviour and what synchronization phenomena can be found under feedback interconnection. A compilation of these findings is described in this book. This book shows a perspective on synchronization of chaotic systems. (orig.)

  20. An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks

    International Nuclear Information System (INIS)

    Cao Jinde

    2004-01-01

    In this Letter, the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are estimated by means of matrix measure and comparison principle. A new estimation is given for the domain of attraction of memory patterns and exponential convergence rate. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks

  1. Stereotype threat engenders neural attentional bias toward negative feedback to undermine performance.

    Science.gov (United States)

    Forbes, Chad E; Leitner, Jordan B

    2014-10-01

    Stereotype threat, a situational pressure individuals experience when they fear confirming a negative group stereotype, engenders a cascade of physiological stress responses, negative appraisals, and performance monitoring processes that tax working memory resources necessary for optimal performance. Less is known, however, about how stereotype threat biases attentional processing in response to performance feedback, and how such attentional biases may undermine performance. Women received feedback on math problems in stereotype threatening compared to stereotype-neutral contexts while continuous EEG activity was recorded. Findings revealed that stereotype threatened women elicited larger midline P100 ERPs, increased phase locking between anterior cingulate cortex and dorsolateral prefrontal cortex (two regions integral for attentional processes), and increased power in left fusiform gyrus in response to negative feedback compared to positive feedback and women in stereotype-neutral contexts. Increased power in left fusiform gyrus in response to negative feedback predicted underperformance on the math task among stereotype threatened women only. Women in stereotype-neutral contexts exhibited the opposite trend. Findings suggest that in stereotype threatening contexts, neural networks integral for attention and working memory are biased toward negative, stereotype confirming feedback at very early speeds of information processing. This bias, in turn, plays a role in undermining performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

    Science.gov (United States)

    Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

    2016-11-14

    In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

  3. Trait self-esteem and neural activities related to self-evaluation and social feedback

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-01-01

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one’s own personality traits and of others’ opinion about one’s own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one’s own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback. PMID:26842975

  4. Trait self-esteem and neural activities related to self-evaluation and social feedback.

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-02-04

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one's own personality traits and of others' opinion about one's own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one's own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback.

  5. Mobile robot nonlinear feedback control based on Elman neural network observer

    Directory of Open Access Journals (Sweden)

    Khaled Al-Mutib

    2015-12-01

    Full Text Available This article presents a new approach to control a wheeled mobile robot without velocity measurement. The controller developed is based on kinematic model as well as dynamics model to take into account parameters of dynamics. These parameters related to dynamic equations are identified using a proposed methodology. Input–output feedback linearization is considered with a slight modification in the mathematical expressions to implement the dynamic controller and analyze the nonlinear internal behavior. The developed controllers require sensors to obtain the states needed for the closed-loop system. However, some states may not be available due to the absence of the sensors because of the cost, the weight limitation, reliability, induction of errors, failure, and so on. Particularly, for the velocity measurements, the required accuracy may not be achieved in practical applications due to the existence of significant errors induced by stochastic or cyclical noise. In this article, Elman neural network is proposed to work as an observer to estimate the velocity needed to complete the full state required for the closed-loop control and account for all the disturbances and model parameter uncertainties. Different simulations are carried out to demonstrate the feasibility of the approach in tracking different reference trajectories in comparison with other paradigms.

  6. Snap-drift neural computing for intelligent diagnostic feedback

    OpenAIRE

    Habte, Samson

    2017-01-01

    Information and communication technologies have been playing a crucial role in improving the efficiency and effectiveness of learning and teaching in higher education. Two decades ago, research studies were focused on how to use artificial intelligence techniques to imitate teachers or tutors in delivering learning sessions. Machine learning techniques have been applied in several research studies to construct a student model in the context of intelligent tutoring systems. However, the usage ...

  7. The Technology of Measurement Feedback Systems.

    Science.gov (United States)

    Bickman, Leonard; Kelley, Susan Douglas; Athay, Michele

    2012-12-01

    Usual care in the community is far from optimal. Sufficient evidence exists that dropout rates are significant, treatment is effective for only a small proportion of clients, and that the translation of evidence-based treatments to the real world is problematic. Technology has been shown to be helpful in health care in improving the effectiveness of treatment. A relatively new technology being used in mental health is measurement feedback systems (MFSs). MFSs are particularly applicable to couple and family psychology (CFP) because of its ability to provide information on the multiple perspectives involved in treatment. The Contextualized Feedback Systems tm (CFS®), developed at Vanderbilt University is used as an example of what can be accomplished with an MFS. The advantages and limitations of this technology are described as well as the anticipated reimbursement requirements that mental health services will need.

  8. A method for calculating active feedback system to provide vertical

    Indian Academy of Sciences (India)

    The active feedback system is applied to control slow motions of plasma. The objective of the ... The other problem is connected with the control of plasma vertical position with active feedback system. Calculation of ... Current Issue Volume 90 ...

  9. Lectures in feedback design for multivariable systems

    CERN Document Server

    Isidori, Alberto

    2017-01-01

    This book focuses on methods that relate, in one form or another, to the “small-gain theorem”. It is aimed at readers who are interested in learning methods for the design of feedback laws for linear and nonlinear multivariable systems in the presence of model uncertainties. With worked examples throughout, it includes both introductory material and more advanced topics. Divided into two parts, the first covers relevant aspects of linear-systems theory, the second, nonlinear theory. In order to deepen readers’ understanding, simpler single-input–single-output systems generally precede treatment of more complex multi-input–multi-output (MIMO) systems and linear systems precede nonlinear systems. This approach is used throughout, including in the final chapters, which explain the latest advanced ideas governing the stabilization, regulation, and tracking of nonlinear MIMO systems. Two major design problems are considered, both in the presence of model uncertainties: asymptotic stabilization with a “...

  10. The LILARTI neural network system

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J.D. Jr.; Schell, F.M.; Dodd, C.V.

    1992-10-01

    The material of this Technical Memorandum is intended to provide the reader with conceptual and technical background information on the LILARTI neural network system of detail sufficient to confer an understanding of the LILARTI method as it is presently allied and to facilitate application of the method to problems beyond the scope of this document. Of particular importance in this regard are the descriptive sections and the Appendices which include operating instructions, partial listings of program output and data files, and network construction information.

  11. Neural dynamics of feedforward and feedback processing in figure-ground segregation.

    Science.gov (United States)

    Layton, Oliver W; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  12. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    Directory of Open Access Journals (Sweden)

    Oliver W. Layton

    2014-09-01

    Full Text Available Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure’s interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells, and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells. Neurons (convex cells that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  13. Neural dynamics of feedforward and feedback processing in figure-ground segregation

    Science.gov (United States)

    Layton, Oliver W.; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation. PMID:25346703

  14. Neural Adaptive Sliding-Mode Control of a Vehicle Platoon Using Output Feedback

    Directory of Open Access Journals (Sweden)

    Maode Yan

    2017-11-01

    Full Text Available This paper investigates the output feedback control problem of a vehicle platoon with a constant time headway (CTH policy, where each vehicle can communicate with its consecutive vehicles. Firstly, based on the integrated-sliding-mode (ISM technique, a neural adaptive sliding-mode control algorithm is developed to ensure that the vehicle platoon is moving with the CTH policy and full state measurement. Then, to further decrease the measurement complexity and reduce the communication load, an output feedback control protocol is proposed with only position information, in which a higher order sliding-mode observer is designed to estimate the other required information (velocities and accelerations. In order to avoid collisions among the vehicles, the string stability of the whole vehicle platoon is proven through the stability theorem. Finally, numerical simulation results are provided to verify its effectiveness and advantages over the traditional sliding-mode control method in vehicle platoons.

  15. A simulation study of the global orbit feedback system for Pohang light source

    International Nuclear Information System (INIS)

    Kim, Kukhee; Shim, Kyuyeol; Cho, Moohyun; Namkung, Won; Ko, In Soo; Choi, Jinhyuk

    2000-01-01

    This paper describes the simulation of the global orbit feedback system using the singular value decomposition (SVD) method, the error minimization method, and the neural network method. Instead of facing unacceptable correction result raised occasionally in the SVD method, we choose the error minimization method for the global orbit feedback. This method provides minimum orbit errors while avoiding unacceptable corrections, and keeps the orbit within the dynamic aperture of the storage ring. We simulate the Pohang Light Source (PLS) storage ring using the Methodical Accelerator Design (MAD) code that generates the orbit distortions for the error minimization method and the learning data set for neural network method. In order to compare the effectiveness of the neural network method with others, a neural network is trained by the learning algorithm using the learning data set. The global response matrix with a minimum error and the trained neural network are used to the global orbit feedback system. The simulation shows that a selection of beam position monitors (BPMs) is very sensitive in the reduction of rms orbit distortions, and the random choice gives better results than any other cases. (author)

  16. Partial state feedback control of chaotic neural network and its application

    International Nuclear Information System (INIS)

    He Guoguang; Shrimali, Manish Dev; Aihara, Kazuyuki

    2007-01-01

    The chaos control in the chaotic neural network is studied using the partial state feedback with a control signal from a few control neurons. The controlled CNN converges to one of the stored patterns with a period which depends on the initial conditions, i.e., the set of control neurons and other control parameters. We show that the controlled CNN can distinguish between two initial patterns even if they have a small difference. This implies that such a controlled CNN can be feasibly applied to information processing such as pattern recognition

  17. ASSESSMENT OF LIBRARY USERS’ FEEDBACK USING MODIFIED MULTILAYER PERCEPTRON NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    K G Nandha Kumar

    2017-07-01

    Full Text Available An attempt has been made to evaluate the feedbacks of library users of four different libraries by using neural network based data mining techniques. This paper presents the results of a survey of users’ satisfactory level on four different libraries. The survey has been conducted among the users of four libraries of educational institutions of Kovai Medical Center Research and Educational Trust. Data were collected through questionnaires. Artificial neural network based data mining techniques are proposed and applied to assess the libraries in terms of level of satisfaction of users. In order to assess the users’ satisfaction level, two neural network techniques: Modified Multilayer Perceptron Network-Supervised and Modified Multilayer Perceptron Network-Unsupervised are proposed. The proposed techniques are compared with the conventional classification algorithm Multilayer Perceptron Neural Network and found better in overall performance. It is found that the quality of service provided by the libraries is highly good and users are highly satisfied with various aspects of library service. The Arts and Science College Library secured the maximum percent in terms of user satisfaction. This shows that the users’ satisfaction of ASCL is better than the other libraries. This study provides an insight into the actual quality and satisfactory level of users of libraries after proper assessment. It is strongly expected that the results will help library authorities to enhance services and quality in the near future.

  18. System analysis of force feedback microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Rodrigues, Mario S. [CFMC/Dep. de Física, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa (Portugal); Costa, Luca [European Synchrotron Radiation Facility, 6 rue Jules Horowitz BP 220, 38043 Grenoble Cedex (France); Université Joseph Fourier BP 53, 38041 Grenoble Cedex 9 (France); Chevrier, Joël [European Synchrotron Radiation Facility, 6 rue Jules Horowitz BP 220, 38043 Grenoble Cedex (France); Université Grenoble Alpes, Inst NEEL, F-38042 Grenoble (France); CNRS, Inst NEEL, F-38042 Grenoble (France); Comin, Fabio [European Synchrotron Radiation Facility, 6 rue Jules Horowitz BP 220, 38043 Grenoble Cedex (France)

    2014-02-07

    It was shown recently that the Force Feedback Microscope (FFM) can avoid the jump-to-contact in Atomic force Microscopy even when the cantilevers used are very soft, thus increasing force resolution. In this letter, we explore theoretical aspects of the associated real time control of the tip position. We take into account lever parameters such as the lever characteristics in its environment, spring constant, mass, dissipation coefficient, and the operating conditions such as controller gains and interaction force. We show how the controller parameters are determined so that the FFM functions at its best and estimate the bandwidth of the system under these conditions.

  19. Extended Cognition: Feedback Loops and Coupled Systems

    Directory of Open Access Journals (Sweden)

    Olga Markic

    2017-12-01

    Full Text Available The article explores two waves of active externalism. I first introduce the distinction between passive and active externalism and analyse a proposal of active externalism based on the principle of parity proposed by Clark and Chalmers. There are two main obstacles, causal-constitution fallacy and cognitive bloat, that threaten the extended cognition hypothesis. The second wave of discussions based on the complementarity principle deals with cognitive systems with feedback loops between internal and external elements and is a more radical departure from functionalism and traditional thinking about cognition. I conclude with some remarks on potential ethical considerations of extended cognition.

  20. System analysis of force feedback microscopy

    International Nuclear Information System (INIS)

    Rodrigues, Mario S.; Costa, Luca; Chevrier, Joël; Comin, Fabio

    2014-01-01

    It was shown recently that the Force Feedback Microscope (FFM) can avoid the jump-to-contact in Atomic force Microscopy even when the cantilevers used are very soft, thus increasing force resolution. In this letter, we explore theoretical aspects of the associated real time control of the tip position. We take into account lever parameters such as the lever characteristics in its environment, spring constant, mass, dissipation coefficient, and the operating conditions such as controller gains and interaction force. We show how the controller parameters are determined so that the FFM functions at its best and estimate the bandwidth of the system under these conditions

  1. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  2. Parameter estimation in space systems using recurrent neural networks

    Science.gov (United States)

    Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

    1991-01-01

    The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

  3. An overview of neural function and feedback control in human communication.

    Science.gov (United States)

    Hood, L J

    1998-01-01

    The speech and hearing mechanisms depend on accurate sensory information and intact feedback mechanisms to facilitate communication. This article provides a brief overview of some components of the nervous system important for human communication and some electrophysiological methods used to measure cortical function in humans. An overview of automatic control and feedback mechanisms in general and as they pertain to the speech motor system and control of the hearing periphery is also presented, along with a discussion of how the speech and auditory systems interact.

  4. Neural Control of the Immune System

    Science.gov (United States)

    Sundman, Eva; Olofsson, Peder S.

    2014-01-01

    Neural reflexes support homeostasis by modulating the function of organ systems. Recent advances in neuroscience and immunology have revealed that neural reflexes also regulate the immune system. Activation of the vagus nerve modulates leukocyte cytokine production and alleviates experimental shock and autoimmune disease, and recent data have…

  5. Temporal neural networks and transient analysis of complex engineering systems

    Science.gov (United States)

    Uluyol, Onder

    A theory is introduced for a multi-layered Local Output Gamma Feedback (LOGF) neural network within the paradigm of Locally-Recurrent Globally-Feedforward neural networks. It is developed for the identification, prediction, and control tasks of spatio-temporal systems and allows for the presentation of different time scales through incorporation of a gamma memory. It is initially applied to the tasks of sunspot and Mackey-Glass series prediction as benchmarks, then it is extended to the task of power level control of a nuclear reactor at different fuel cycle conditions. The developed LOGF neuron model can also be viewed as a Transformed Input and State (TIS) Gamma memory for neural network architectures for temporal processing. The novel LOGF neuron model extends the static neuron model by incorporating into it a short-term memory structure in the form of a digital gamma filter. A feedforward neural network made up of LOGF neurons can thus be used to model dynamic systems. A learning algorithm based upon the Backpropagation-Through-Time (BTT) approach is derived. It is applicable for training a general L-layer LOGF neural network. The spatial and temporal weights and parameters of the network are iteratively optimized for a given problem using the derived learning algorithm.

  6. Operation of the transverse feedback system at the CERN SPS

    International Nuclear Information System (INIS)

    Bossart, R.; Louwerse, R.; Mourier, J.; Vos, L.

    1987-01-01

    To prevent transverse instabilities at high beam intensity in the SPS, the transverse feedback system for damping the betatron oscillations has been upgraded for larger damping decrements and for increased system's bandwidth. The feedback loop now contains a digital delay line cancellor, so that the damper works with a velocity feedback Δx/Δt, unaffected by the closed orbit position x at the pick-up station. The digital processing of the feedback signal facilitates nonlinear feedback techniques such as antidamping and ''band-bang'' feedback. The ''bang-bang'' feedback provides the maximum possible damping rate of the injection oscillations in the SPS-collider, in order to minimize the emittance increase caused by filamentation. The antidamping nonlinearity provides small continuous beam oscillations of 50 μm amplitude for tracking the machine tune Q with a phase locked loop

  7. Educators' Perceptions of Automated Feedback Systems

    Science.gov (United States)

    Debuse, Justin C. W.; Lawley, Meredith; Shibl, Rania

    2008-01-01

    Assessment of student learning is a core function of educators. Ideally students should be provided with timely, constructive feedback to facilitate learning. However, provision of high quality feedback becomes more complex as class sizes increase, modes of study expand and academic workloads increase. ICT solutions are being developed to…

  8. Development of a longitudinal feedback cavity for the beam feedback system

    International Nuclear Information System (INIS)

    Huang Gang; Chen Huaibi; Huang Wenhui; Tong Dechun; Lin Yuzheng; Zhao Zhentang

    2003-01-01

    Longitudinal beam feedback system is widely used to damp coupling bunch instability. Kicker is one of the key components of the longitudinal feedback system. A prototype cavity of longitudinal feedback kicker is developed according to the parameter of BEPC II. The usage of nose cone in the kicker design increased the shunt impedance. In order to avoid the extra tapper in the storage ring, the racetrack shape beam pipe is applied in the kicker. The impedance and the bandwidth of the kicker is measured by the coaxial line impedance measurement platform and the result achieved the design goals

  9. Neural neworks in a management information systems

    Directory of Open Access Journals (Sweden)

    Jana Weinlichová

    2009-01-01

    Full Text Available For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of manager issues. Those products are given as primary support for manager issues solving. We were tried to find reciprocally between products using Neural Networks and between Management Information Systems for finding a real possibility of applying Neural Networks as a direct part of Management Information Systems (MIS. In the article are presented possibilities to apply Neural Networks on different types of tasks in MIS.

  10. Effect of intermittent feedback control on robustness of human-like postural control system

    Science.gov (United States)

    Tanabe, Hiroko; Fujii, Keisuke; Suzuki, Yasuyuki; Kouzaki, Motoki

    2016-03-01

    Humans have to acquire postural robustness to maintain stability against internal and external perturbations. Human standing has been recently modelled using an intermittent feedback control. However, the causality inside of the closed-loop postural control system associated with the neural control strategy is still unknown. Here, we examined the effect of intermittent feedback control on postural robustness and of changes in active/passive components on joint coordinative structure. We implemented computer simulation of a quadruple inverted pendulum that is mechanically close to human tiptoe standing. We simulated three pairs of joint viscoelasticity and three choices of neural control strategies for each joint: intermittent, continuous, or passive control. We examined postural robustness for each parameter set by analysing the region of active feedback gain. We found intermittent control at the hip joint was necessary for model stabilisation and model parameters affected the robustness of the pendulum. Joint sways of the pendulum model were partially smaller than or similar to those of experimental data. In conclusion, intermittent feedback control was necessary for the stabilisation of the quadruple inverted pendulum. Also, postural robustness of human-like multi-link standing would be achieved by both passive joint viscoelasticity and neural joint control strategies.

  11. Echoes in correlated neural systems

    International Nuclear Information System (INIS)

    Helias, M; Tetzlaff, T; Diesmann, M

    2013-01-01

    Correlations are employed in modern physics to explain microscopic and macroscopic phenomena, like the fractional quantum Hall effect and the Mott insulator state in high temperature superconductors and ultracold atoms. Simultaneously probed neurons in the intact brain reveal correlations between their activity, an important measure to study information processing in the brain that also influences the macroscopic signals of neural activity, like the electroencephalogram (EEG). Networks of spiking neurons differ from most physical systems: the interaction between elements is directed, time delayed, mediated by short pulses and each neuron receives events from thousands of neurons. Even the stationary state of the network cannot be described by equilibrium statistical mechanics. Here we develop a quantitative theory of pairwise correlations in finite-sized random networks of spiking neurons. We derive explicit analytic expressions for the population-averaged cross correlation functions. Our theory explains why the intuitive mean field description fails, how the echo of single action potentials causes an apparent lag of inhibition with respect to excitation and how the size of the network can be scaled while maintaining its dynamical state. Finally, we derive a new criterion for the emergence of collective oscillations from the spectrum of the time-evolution propagator. (paper)

  12. Neural activation during imitation with or without performance feedback: An fMRI study.

    Science.gov (United States)

    Zhang, Kaihua; Wang, Hui; Dong, Guangheng; Wang, Mengxing; Zhang, Jilei; Zhang, Hui; Meng, Weixia; Du, Xiaoxia

    2016-08-26

    In our daily lives, we often receive performance feedback (PF) during imitative learning, and we adjust our behaviors accordingly to improve performance. However, little is known regarding the neural mechanisms underlying this learning process. We hypothesized that appropriate PF would enhance neural activation or recruit additional brain areas during subsequent action imitation. Pictures of 20 different finger gestures without any social meaning were shown to participants from the first-person perspective. Imitation with or without PF was investigated by functional magnetic resonance imaging in 30 healthy subjects. The PF was given by a real person or by a computer. PF from a real person induced hyperactivation of the parietal lobe (precuneus and cuneus), cingulate cortex (posterior and anterior), temporal lobe (superior and transverse temporal gyri), and cerebellum (posterior and anterior lobes) during subsequent imitation. The positive PF and negative PF from a real person, induced the activation of more brain areas during the following imitation. The hyperactivation of the cerebellum, posterior cingulate cortex, precuneus, and cuneus suggests that the subjects exhibited enhanced motor control and visual attention during imitation after PF. Additionally, random PF from a computer had a small effect on the next imitation. We suggest that positive and accurate PF may be helpful for imitation learning. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Neural systems for tactual memories.

    Science.gov (United States)

    Bonda, E; Petrides, M; Evans, A

    1996-04-01

    1. The aim of this study was to investigate the neural systems involved in the memory processing of experiences through touch. 2. Regional cerebral blood flow was measured with positron emission tomography by means of the water bolus H2(15)O methodology in human subjects as they performed tasks involving different levels of tactual memory. In one of the experimental tasks, the subjects had to palpate nonsense shapes to match each one to a previously learned set, thus requiring constant reference to long-term memory. The other experimental task involved judgements of the recent recurrence of shapes during the scanning period. A set of three control tasks was used to control for the type of exploratory movements and sensory processing inherent in the two experimental tasks. 3. Comparisons of the distribution of activity between the experimental and the control tasks were carried out by means of the subtraction method. In relation to the control conditions, the two experimental tasks requiring memory resulted in significant changes within the posteroventral insula and the central opercular region. In addition, the task requiring recall from long-term memory yielded changes in the perirhinal cortex. 4. The above findings demonstrated that a ventrally directed parietoinsular pathway, leading to the posteroventral insula and the perirhinal cortex, constitutes a system by which long-lasting representations of tactual experiences are formed. It is proposed that the posteroventral insula is involved in tactual feature analysis, by analogy with the similar role of the inferotemporal cortex in vision, whereas the perirhinal cortex is further involved in the integration of these features into long-lasting representations of somatosensory experiences.

  14. Proposed Reactor Operating Experience Feedback System Development

    International Nuclear Information System (INIS)

    Ahn, Seung Hoon; Kim, Min Chul; Huh, Chang Wook; Lee, Durk Hun; Bae, Koo Hyun

    2006-01-01

    Most events occurring in nuclear power plants are not individually significant, and prevented from progressing to accident conditions by a series of barriers against core damage and radioactive releases. Significant events, if occur, are almost always a breach of these multiple barriers. As illustrated in the 'Swiss cheese' model, the individual layers of defense or 'cheese slices' have weakness or 'holes.' These weaknesses are inconstant, i.e., the holes are open or close at random. When by chance all the holes are aligned, a hazard causes the significant event of concern. Elements of low significant events, inattention to detail, time or economic pressure, uncorrected poor practices/habits, marginal maintenance and equipment care, etc., make holes in the layers of defense; some elements may make more holes in different layers, incurring more chances to be aligned. An effective reduction of the holes, therefore, is gained through better knowledge or awareness of increasing trends of the event elements, followed by appropriate actions. According to the Swiss cheese metaphor, attention to the Operating Experience (OE) feedback system, as opposed to the individual and to randomness, is drawn from a viewpoint of reactor safety

  15. Design of output feedback controller for a unified chaotic system

    International Nuclear Information System (INIS)

    Li Wenlin; Chen Xiuqin; Shen Zhiping

    2008-01-01

    In this paper, the synchronization of a unified chaotic system is investigated by the use of output feedback controllers; a two-input single-output feedback controller and single-input single-output feedback controller are presented to synchronize the unified chaotic system when the states are not all measurable. Compared with the existing results, the controllers designed in this paper have some advantages such as small feedback gain, simple structure and less conservation. Finally, numerical simulations results are provided to demonstrate the validity and effectiveness of the proposed method

  16. Operational status of the transverse multibunch feedback system at Diamond

    International Nuclear Information System (INIS)

    Uzun, I.; Abbott, M.; Heron, M.T.; Morgan, A.F.D.; Rehm, G.

    2012-01-01

    A transverse multibunch feedback (TMBF) system is in operation at Diamond Light Source to damp coupled-bunch instabilities up to 250 MHz in both the vertical and horizontal planes. It comprises an in-house designed and built analogue front end combined with a Libera Bunch-by-Bunch feedback processor and output stripline kickers. FPGA-based feedback electronics is used to implement several diagnostic features in addition to the basic feedback functionality. This paper reports on the current operational status of the TMBF system along with its characteristics. Also discussed are operational diagnostic functionalities including continuous measurement of the betatron tune and chromaticity. (authors)

  17. The efficacy of an automated feedback system for general practitioners

    NARCIS (Netherlands)

    Bindels, Rianne; Hasman, Arie; Kester, Arnold D.; Talmon, Jan L.; de Clercq, Paul A.; Winkens, Ron A. G.

    2003-01-01

    OBJECTIVE: An automated feedback system that produces comments about the non-adherence of general practitioners (GPs) to accepted practice guidelines for ordering diagnostic tests was developed. Before implementing the automated feedback system in daily practice, we assessed the potential effect of

  18. Quasi-period oscillations of relay feedback systems

    International Nuclear Information System (INIS)

    Wen Guilin; Wang Qingguo; Lee, T.H.

    2007-01-01

    This paper presents an analytical method for investigation of the existence and stability of quasi-period oscillations (torus solutions) for a class of relay feedback systems. The idea is to analyze Poincare map from one switching surface to the next based on the Hopf bifurcation theory of maps. It is shown that there exist quasi-period oscillations in certain relay feedback systems

  19. Designing new feedback mangement system Långvik

    OpenAIRE

    Dang, Hien

    2014-01-01

    This thesis is a design project on the field of feedback management, conducted for Långvik hotel. The purpose of this thesis is to recommend a new feedback management system for the hotel that can effectively recognize original reasons for customers’ returning decision. The new approach to feedback management is expected to generate a higher number of re- turned customers subsequent to the summer business peak. The literature review focuses on the connection between customer experience and...

  20. Combined feedforward and feedback control of end milling system

    OpenAIRE

    Čuš, Franc; Župerl, Uroš; Balič, Jože

    2012-01-01

    Purpose: Purpose of this paper. An intelligent control system is presented that uses a combination of feedforward and feedback for cutting force control in end milling.Design/methodology/approach: The network is trained by the feedback output that is minimized during training and most control action for disturbance rejection is finally performed by the rapid feedforward action of the network.Findings: The feedback controller corrects for errors caused by external disturbances. The feedforward...

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

    DEFF Research Database (Denmark)

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

    2001-01-01

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

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

    DEFF Research Database (Denmark)

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

    2001-01-01

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

  3. Ideal and conventional feedback systems for RWM suppression

    International Nuclear Information System (INIS)

    Pustovitov, V.D.

    2002-01-01

    Feedback suppression of resistive wall modes (RWM) is studied analytically using a model based on a standard cylindrical approximation. Two feedback systems are compared: 'ideal', creating only the field necessary for RMW suppression, and 'conventional', like that used in the DIII-D tokamak and considered as a candidate for ITER. The widespread opinion that the feedback with poloidal sensors is better than that with radial sensors is discussed. It is shown that the 'conventional' feedback with radial sensors can be effective only in a limited range, while using the input signal from internal poloidal sensors allows easy fulfilment of the stability criterion. This is a property of the 'conventional' feedback, but the 'ideal' feedback would stabilise RWM in both cases. (author)

  4. Ideal and conventional feedback systems for RWM suppression

    Energy Technology Data Exchange (ETDEWEB)

    Pustovitov, V.D.

    2002-01-01

    Feedback suppression of resistive wall modes (RWM) is studied analytically using a model based on a standard cylindrical approximation. Two feedback systems are compared: 'ideal', creating only the field necessary for RMW suppression, and 'conventional', like that used in the DIII-D tokamak and considered as a candidate for ITER. The widespread opinion that the feedback with poloidal sensors is better than that with radial sensors is discussed. It is shown that the 'conventional' feedback with radial sensors can be effective only in a limited range, while using the input signal from internal poloidal sensors allows easy fulfilment of the stability criterion. This is a property of the 'conventional' feedback, but the 'ideal' feedback would stabilise RWM in both cases. (author)

  5. Minimal-Inversion Feedforward-And-Feedback Control System

    Science.gov (United States)

    Seraji, Homayoun

    1990-01-01

    Recent developments in theory of control systems support concept of minimal-inversion feedforward-and feedback control system consisting of three independently designable control subsystems. Applicable to the control of linear, time-invariant plant.

  6. Feedback authoring possibilities in web-based learning systems

    NARCIS (Netherlands)

    Vasilyeva, E.; De Bra, P.M.E.; Pechenizkiy, M.; Bonk, C.J.; et al., xx

    2008-01-01

    This paper surveys and analyses the feedback authoring possibilities in online assessment modules of the most popular Learning Management Systems (LMS) including Moodle, Sakai, and Blackboard. We consider the problem of authoring and support of tailored and personalized feedback and demonstrate how

  7. Neural neworks in a management information systems

    OpenAIRE

    Jana Weinlichová; Michael Štencl

    2009-01-01

    For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of ma...

  8. Using sampled-data feedback control and linear feedback synchronization in a new hyperchaotic system

    International Nuclear Information System (INIS)

    Zhao Junchan; Lu Junan

    2008-01-01

    This paper investigates control and synchronization of a new hyperchaotic system which was proposed by [Chen A, Lu J-A, Lue J, Yu S. Generating hyperchaotic Lue attractor via state feedback control. Physica A 2006;364:103-10]. Firstly, we give different sampled-data feedback control schemes with the variation of system parameter d. Specifically, we only use one controller to drive the system to the origin when d element of (-0.35, 0), and use two controllers if d element of [0, 1.3]. Next, we combine PC method with linear feedback approach to realize synchronization, and derive similar conclusions with varying d. Numerical simulations are also given to validate the proposed approaches

  9. Truncated predictor feedback for time-delay systems

    CERN Document Server

    Zhou, Bin

    2014-01-01

    This book provides a systematic approach to the design of predictor based controllers for (time-varying) linear systems with either (time-varying) input or state delays. Differently from those traditional predictor based controllers, which are infinite-dimensional static feedback laws and may cause difficulties in their practical implementation, this book develops a truncated predictor feedback (TPF) which involves only finite dimensional static state feedback. Features and topics: A novel approach referred to as truncated predictor feedback for the stabilization of (time-varying) time-delay systems in both the continuous-time setting and the discrete-time setting is built systematically Semi-global and global stabilization problems of linear time-delay systems subject to either magnitude saturation or energy constraints are solved in a systematic manner Both stabilization of a single system and consensus of a group of systems (multi-agent systems) are treated in a unified manner by applying the truncated pre...

  10. Normal form and synchronization of strict-feedback chaotic systems

    International Nuclear Information System (INIS)

    Wang, Feng; Chen, Shihua; Yu Minghai; Wang Changping

    2004-01-01

    This study concerns the normal form and synchronization of strict-feedback chaotic systems. We prove that, any strict-feedback chaotic system can be rendered into a normal form with a invertible transform and then a design procedure to synchronize the normal form of a non-autonomous strict-feedback chaotic system is presented. This approach needs only a scalar driving signal to realize synchronization no matter how many dimensions the chaotic system contains. Furthermore, the Roessler chaotic system is taken as a concrete example to illustrate the procedure of designing without transforming a strict-feedback chaotic system into its normal form. Numerical simulations are also provided to show the effectiveness and feasibility of the developed methods

  11. Modeling and simulation of Indus-2 RF feedback control system

    International Nuclear Information System (INIS)

    Sharma, D.; Bagduwal, P.S.; Tiwari, N.; Lad, M.; Hannurkar, P.R.

    2012-01-01

    Indus-2 synchrotron radiation source has four RF stations along with their feedback control systems. For higher beam energy and current operation amplitude and phase feedback control systems of Indus-2 are being upgraded. To understand the behaviour of amplitude and phase control loop under different operating conditions, modelling and simulation of RF feedback control system is done. RF cavity baseband I/Q model has been created due to its close correspondence with actual implementation and better computational efficiency which makes the simulation faster. Correspondence between cavity baseband and RF model is confirmed by comparing their simulation results. Low Level RF (LLRF) feedback control system simulation is done using the same cavity baseband I/Q model. Error signals are intentionally generated and response of the closed loop system is observed. Simulation will help us in optimizing parameters of upgraded LLRF system for higher beam energy and current operation. (author)

  12. Direct output feedback control of discrete-time systems

    International Nuclear Information System (INIS)

    Lin, C.C.; Chung, L.L.; Lu, K.H.

    1993-01-01

    An optimal direct output feedback control algorithm is developed for discrete-time systems with the consideration of time delay in control force action. Optimal constant output feedback gains are obtained through variational process such that certain prescribed quadratic performance index is minimized. Discrete-time control forces are then calculated from the multiplication of output measurements by these pre-calculated feedback gains. According to the proposed algorithm, structural system is assured to remain stable even in the presence of time delay. The number of sensors and controllers may be very small as compared with the dimension of states. Numerical results show that direct velocity feedback control is more sensitive to time delay than state feedback but, is still quite effective in reducing the dynamic responses under earthquake excitation. (author)

  13. Corresponding Angle Feedback in an innovative weighted transportation system

    International Nuclear Information System (INIS)

    Dong Chuanfei; Ma Xu

    2010-01-01

    The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this Letter, we study dynamics of traffic flow with real-time information. The influence of a feedback strategy named Corresponding Angle Feedback Strategy (CAFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  14. Feedback from visual cortical area 7 to areas 17 and 18 in cats: How neural web is woven during feedback.

    Science.gov (United States)

    Yang, X; Ding, H; Lu, J

    2016-01-15

    To investigate the feedback effect from area 7 to areas 17 and 18, intrinsic signal optical imaging combined with pharmacological, morphological methods and functional magnetic resonance imaging (fMRI) was employed. A spatial frequency-dependent decrease in response amplitude of orientation maps was observed in areas 17 and 18 when area 7 was inactivated by a local injection of GABA, or by a lesion induced by liquid nitrogen freezing. The pattern of orientation maps of areas 17 and 18 after the inactivation of area 7, if they were not totally blurred, paralleled the normal one. In morphological experiments, after one point at the shallow layers within the center of the cat's orientation column of area 17 was injected electrophoretically with HRP (horseradish peroxidase), three sequential patches in layers 1, 2 and 3 of area 7 were observed. Employing fMRI it was found that area 7 feedbacks mainly to areas 17 and 18 on ipsilateral hemisphere. Therefore, our conclusions are: (1) feedback from area 7 to areas 17 and 18 is spatial frequency modulated; (2) feedback from area 7 to areas 17 and 18 occurs mainly ipsilaterally; (3) histological feedback pattern from area 7 to area 17 is weblike. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  15. Optimal control of nonlinear continuous-time systems in strict-feedback form.

    Science.gov (United States)

    Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

    2015-10-01

    This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

  16. Feedback-linearization and feedback-feedforward decentralized control for multimachine power system

    Energy Technology Data Exchange (ETDEWEB)

    De Tuglie, Enrico [Dipartimento di Ingegneria dell' Ambiente, e per lo Sviluppo Sostenibile - DIASS, Politecnico di Bari, Viale del Turismo 8, 74100 Taranto (Italy); Iannone, Silvio Marcello; Torelli, Francesco [Dipartimento di Elettrotecnica, ed Elettronica - DEE, Politecnico di Bari, Via Re David 200, 70125 Bari (Italy)

    2008-03-15

    In this paper a decentralized nonlinear controller for large-scale power systems is investigated. The proposed controller design is based on the input-output feedback linearization methodology. In order to overcome computational difficulties in adopting such methodology, the overall interconnected nonlinear system, given as n-order, is analyzed as a cascade connection of an n{sub 1}-order nonlinear subsystem and an n{sub 2}-order linear subsystem. The controller design is obtained by applying input-output feedback linearization to the nonlinear subsystem and adopting a tracking control scheme, based on feedback-feedforward technique, for the linear subsystem. In the assumed system model, which is characterised by an interconnected structure between generating units, a decentralised adaptive controller is implemented by decentralizing these constraints. The use of a totally decentralised controller implies a system performance decay with respect to performance when the system is equipped with a centralised controller. Fortunately, the robustness of the proposed controller, based on input-output feedback procedure, guarantees good performance in terms of disturbance even when disturbances are caused by decentralization of interconnection constraints. Test results, provided on the IEEE 30 bus test system, demonstrate the effectiveness and practical applicability of proposed methodology. (author)

  17. Application of neural networks in CRM systems

    Directory of Open Access Journals (Sweden)

    Bojanowska Agnieszka

    2017-01-01

    Full Text Available The central aim of this study is to investigate how to apply artificial neural networks in Customer Relationship Management (CRM. The paper presents several business applications of neural networks in software systems designed to aid CRM, e.g. in deciding on the profitability of building a relationship with a given customer. Furthermore, a framework for a neural-network based CRM software tool is developed. Building beneficial relationships with customers is generating considerable interest among various businesses, and is often mentioned as one of the crucial objectives of enterprises, next to their key aim: to bring satisfactory profit. There is a growing tendency among businesses to invest in CRM systems, which together with an organisational culture of a company aid managing customer relationships. It is the sheer amount of gathered data as well as the need for constant updating and analysis of this breadth of information that may imply the suitability of neural networks for the application in question. Neural networks exhibit considerably higher computational capabilities than sequential calculations because the solution to a problem is obtained without the need for developing a special algorithm. In the majority of presented CRM applications neural networks constitute and are presented as a managerial decision-taking optimisation tool.

  18. Systematic Self-Regulation of the Neural System Essential for Peak Performance and Wellbeing.

    Science.gov (United States)

    Cassel, Russell N.

    1985-01-01

    Balance and harmony within one's neural system is dynamic and changing, and restoring that balance is essential for peak performance. With a minimum amount of training individuals are able to restore this delicate balance and thereby enhance their own wellbeing. Autogenic feedback training has been demonstrated to be an effective means for…

  19. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Z.; Rizy, D.T.

    1996-02-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks an d one nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  20. Weighted congestion coefficient feedback in intelligent transportation systems

    International Nuclear Information System (INIS)

    Dong Chuanfei; Ma Xu; Wang Binghong

    2010-01-01

    In traffic systems, a reasonable information feedback can improve road capacity. In this Letter, we study dynamics of traffic flow with real-time information. And the influence of a feedback strategy named Weighted Congestion Coefficient Feedback Strategy (WCCFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  1. Instabilities simulations with wideband feedback systems: CMAD, HEADTAIL, WARP

    CERN Document Server

    Li, Kevin; Fox, J D; Pivi, M; Rivetta, C; Rumolo, G

    2013-01-01

    Transverse mode coupling (TMCI) and electron cloud instabilities (ECI) pose fundamental limitations on the acceptable beam intensities in the SPS at CERN. This in turn limits the ultimate achievable luminosity in the LHC. Therefore, future luminosity upgrades foresee methods for evading TMCI as well as ECI. Proposed approaches within the LHC Injector Upgrade (LIU) project include new optics with reduced transition energy as well as vacuum chamber coating techniques. As a complementary option, high bandwidth feedback systems may provide instability mitigation by actively damping the intra-bunch motion of unstable modes. In an effort to evaluate the potentials and limitations of such feedback systems and to characterise some of the specifications, a numerical model of a realistic feedback system has been developed and integrated into available instabilities simulation codes. Together with the implementation of this new feedback system model, CMAD and HEADTAIL have been used to investigate the impact of differen...

  2. An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2014-02-01

    Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

  3. Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

    Science.gov (United States)

    Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

    2001-01-01

    A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

  4. Instabilities simulations with wideband feedback systems: CMAD, HEADTAIL, WARP

    International Nuclear Information System (INIS)

    Li, Kevin; Cesaratto, J; Fox, J D; Pivi, M; Rivetta, C; Rumolo, G

    2013-01-01

    Transverse mode coupling (TMCI) and electron cloud instabilities (ECI) pose fundamental limitations on the acceptable beam intensities in the SPS at CERN. This in turn limits the ultimate achievable luminosity in the LHC. Therefore, future luminosity upgrades foresee methods for evading TMCI as well as ECI. Proposed approaches within the LHC Injector Upgrade (LIU) project include new optics with reduced transition energy as well as vacuum chamber coating techniques. As a complementary option, high bandwidth feedback systems may provide instability mitigation by actively damping the intra-bunch motion of unstable modes. In an effort to evaluate the potentials and limitations of such feedback systems and to characterise some of the specifications, a numerical model of a realistic feedback system has been developed and integrated into available instabilities simulation codes. Together with the implementation of this new feedback system model, CMAD and HEADTAIL have been used to investigate the impact of different wideband feedback systems on ECI in the SPS. In this paper, we present some details on the numerical model of the realistic feedback system and its implementation as well as the results obtained from the simulation study using this model together with the instability codes. (author)

  5. Synchronizing strict-feedback and general strict-feedback chaotic systems via a single controller

    International Nuclear Information System (INIS)

    Chen Shihua; Wang Feng; Wang Changping

    2004-01-01

    We present a systematic design procedure to synchronize a class of chaotic systems in a so-called strict-feedback form based on back-stepping procedure. This approach needs only a single controller to realize synchronization no matter how many dimensions the chaotic system contains. Furthermore, we point out that the method does not work for general strict-feedback chaotic systems, for instance, Lorenz system. Therefore, we propose three kinds of synchronization schemes for Lorenz system using the Lyapunov function method. All the three schemes avoid including divergence factor as in Ref. [Chaos, Solitons and Fractals 16 (2003) 37]. Especially in the last two schemes, we need only one state variable in controller, which has important significance in chaos synchronization used for communication purposes. Finally numerical simulations are provided to show the effectiveness and feasibility of the developed methods

  6. Spiking neural P systems with multiple channels.

    Science.gov (United States)

    Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

    2017-11-01

    Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Predictor feedback for delay systems implementations and approximations

    CERN Document Server

    Karafyllis, Iasson

    2017-01-01

    This monograph bridges the gap between the nonlinear predictor as a concept and as a practical tool, presenting a complete theory of the application of predictor feedback to time-invariant, uncertain systems with constant input delays and/or measurement delays. It supplies several methods for generating the necessary real-time solutions to the systems’ nonlinear differential equations, which the authors refer to as approximate predictors. Predictor feedback for linear time-invariant (LTI) systems is presented in Part I to provide a solid foundation on the necessary concepts, as LTI systems pose fewer technical difficulties than nonlinear systems. Part II extends all of the concepts to nonlinear time-invariant systems. Finally, Part III explores extensions of predictor feedback to systems described by integral delay equations and to discrete-time systems. The book’s core is the design of control and observer algorithms with which global stabilization, guaranteed in the previous literature with idealized (b...

  8. Evaluating neural networks and artificial intelligence systems

    Science.gov (United States)

    Alberts, David S.

    1994-02-01

    Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

  9. Comparison of Power Generating Systems Using Feedback Effect Modeling

    International Nuclear Information System (INIS)

    Kim, Seong Ho; Kim, Kil Yoo; Kim, Tae Woon

    2005-01-01

    Comparative assessment of various power systems can be treated as a multicriteria decision-making (MCDM) problem. In reality, there is interdependence among decision elements (e.g., decision goal, decision criteria, and decision alternatives). In our previous work, using an analytic hierarchy process (AHP) technique, a comprehensive assessment framework for national power systems has been developed. It was assumed in the AHP modeling that there is no interdependence among decision elements. In the present work, one of interdependence phenomena, feedback effect, is investigated in the context of network structures instead of one-way directional tree structures. Moreover, attitudes of decision-makers can be incorporated into the feedback effect modeling. The main objectives of this work are to develop a feedback effect modeling using an analytic network process (ANP) technique and to demonstrate the feedback effect using a numerical example in comparison to the hierarchy model

  10. Impact of biogenic emissions on feedbacks in the climate system

    Science.gov (United States)

    Krüger, Olaf

    2017-04-01

    Impact of biogenic emissions on feedbacks in the climate system Bio-geophysical feedback between marine or continental ecosystems and the atmosphere potentially can alter climate change. A prominent feedback loop which is under discussion since 1983 bases on the emission of biologically produced gases - molecular oxygen, sulphur containing compounds and possibly isoprene, supersaturated in oceanic waters - into the marine troposphere. These by-products of phytoplankton metabolism lead to aerosol production and procure sustained influence on climate via modulation of cloud optical properties. In this contribution some findings related to the above mentioned climate processes are presented with special emphasis on marine ecosystems. A comparison of marine and continental ecosystems is made and different processes with major impact on feedbacks in the climate system are discussed.

  11. Integrated Neural Flight and Propulsion Control System

    Science.gov (United States)

    Kaneshige, John; Gundy-Burlet, Karen; Norvig, Peter (Technical Monitor)

    2001-01-01

    This paper describes an integrated neural flight and propulsion control system. which uses a neural network based approach for applying alternate sources of control power in the presence of damage or failures. Under normal operating conditions, the system utilizes conventional flight control surfaces. Neural networks are used to provide consistent handling qualities across flight conditions and for different aircraft configurations. Under damage or failure conditions, the system may utilize unconventional flight control surface allocations, along with integrated propulsion control, when additional control power is necessary for achieving desired flight control performance. In this case, neural networks are used to adapt to changes in aircraft dynamics and control allocation schemes. Of significant importance here is the fact that this system can operate without emergency or backup flight control mode operations. An additional advantage is that this system can utilize, but does not require, fault detection and isolation information or explicit parameter identification. Piloted simulation studies were performed on a commercial transport aircraft simulator. Subjects included both NASA test pilots and commercial airline crews. Results demonstrate the potential for improving handing qualities and significantly increasing survivability rates under various simulated failure conditions.

  12. Coherent versus Measurement Feedback: Linear Systems Theory for Quantum Information

    Directory of Open Access Journals (Sweden)

    Naoki Yamamoto

    2014-11-01

    Full Text Available To control a quantum system via feedback, we generally have two options in choosing a control scheme. One is the coherent feedback, which feeds the output field of the system, through a fully quantum device, back to manipulate the system without involving any measurement process. The other one is measurement-based feedback, which measures the output field and performs a real-time manipulation on the system based on the measurement results. Both schemes have advantages and disadvantages, depending on the system and the control goal; hence, their comparison in several situations is important. This paper considers a general open linear quantum system with the following specific control goals: backaction evasion, generation of a quantum nondemolished variable, and generation of a decoherence-free subsystem, all of which have important roles in quantum information science. Some no-go theorems are proven, clarifying that those goals cannot be achieved by any measurement-based feedback control. On the other hand, it is shown that, for each control goal there exists a coherent feedback controller accomplishing the task. The key idea to obtain all the results is system theoretic characterizations of the above three notions in terms of controllability and observability properties or transfer functions of linear systems, which are consistent with their standard definitions.

  13. Swing Damping for Helicopter Slung Load Systems using Delayed Feedback

    OpenAIRE

    Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

    2009-01-01

    This paper presents the design and verification of a swing reducing controller for helicopter slung load systems usingintentional delayed feedback. It is intended for augmenting a trajectory tracking helicopter controller and thereby improving the slung load handing capabilities for autonomous helicopters. The delayed feedback controller is added to actively reduce oscillations of the slung load by improving the damping of the slung load pendulum modes. Furthermore, it is intended for integra...

  14. Feedback control of nonlinear quantum systems: a rule of thumb.

    Science.gov (United States)

    Jacobs, Kurt; Lund, Austin P

    2007-07-13

    We show that in the regime in which feedback control is most effective - when measurements are relatively efficient, and feedback is relatively strong - then, in the absence of any sharp inhomogeneity in the noise, it is always best to measure in a basis that does not commute with the system density matrix than one that does. That is, it is optimal to make measurements that disturb the state one is attempting to stabilize.

  15. Feedback Control of a Class of Nonholonomic Hamiltonian Systems

    DEFF Research Database (Denmark)

    Sørensen, Mathias Jesper

    Feedback control of nonholonomic systems has always been problematic due to the nonholonomic constraints that limit the space of possible system velocities. This property is very basic, and Brockett proved that a nonholonomic system cannot be asymptotically stabilized by a time-invariant smooth...... turns out to be useful when stabilizing the nonholonomic system. If the system is properly actuated it is possible to asymptotically stabilize the primary part of the configuration coordinates via a passive energy shaping and damping injecting feedback. The feedback is smooth and time......-invariant, but since it does not asymptotically stabilize the secondary part of the configuration coordinates, it does not violate Brockett’s obstruction. The results fromthe general class of nonholonomicHamiltonian systems with kinematic inputs are applied to a real implementation of a four wheel steered, four wheel...

  16. Feedback Design Patterns for Math Online Learning Systems

    Science.gov (United States)

    Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

    2017-01-01

    Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

  17. Asymptotic stabilization of nonlinear systems using state feedback

    International Nuclear Information System (INIS)

    D'Attellis, Carlos

    1990-01-01

    This paper studies the design of state-feedback controllers for the stabilization of single-input single-output nonlinear systems x = f(x) + g(x)u, y = h(x). Two approaches for the stabilization problem are given; the asymptotic stability is achieved by means of: a) nonlinear state feedback: two nonlinear feedbacks are used; the first separates the system in a controllable linear part and in the zeros-dynamic part. The second feedback generates an asymptotically stable equilibrium on the manifold where this dynamics evolves; b) nonlinear dynamic feedback: conditions are established under which the system can follow the output of a completely controllable bilinear system which uses bounded controls. This fact enables the system to reach, using bounded controls too, a desired output value in finite time. As this value corresponds to a state that lays in the attraction basin of a stable equilibrium with the same output, the system evolves to that point. The two methods are illustrated by examples. (Author) [es

  18. Beam position feedback system for the advanced photon source

    International Nuclear Information System (INIS)

    Chung, Y.

    1994-01-01

    The Advanced Photon Source (APS) will implement both global and local beam position feedback systems to stabilize the particle and x-ray beams for the storage ring. The systems consist of 20 VME crates distributed around the ring, each running multiple digital signal processors (DSP) running at 4 kHz sampling rate with a proportional, integral, and derivative (PID) control algorithm. The particle and x-ray beam position data is shared by the distributed processors through networked reflective memory. A theory of closed orbit correction using the technique of singular value decomposition (SVD) of the response matrix and simulation of its application to the APS storage ring will be discussed. This technique combines the global and local feedback systems and resolves the conflict among multiple local feedback systems due to local bump closure error. Maximum correction efficiency is achieved by feeding back to the global orbit data to the local feedback systems. The effect of the eddy current induced in the relatively thick (1/2 in.) vacuum chamber by the ac corrector magnet field for local feedback systems is compensated by digital filters. Results of experiments conducted on the x-ray ring of the National Synchrotron Light Source and the SPEAR at Stanford Synchrotron Radiation Laboratory will also be presented

  19. Beam position feedback system for the advanced photon source

    International Nuclear Information System (INIS)

    Chung, Y.

    1994-01-01

    The Advanced Photon Source (APS) will implement both global and local beam position feedback systems to stabilize the particle and X-ray beams for the storage ring. The systems consist of 20 VME crates distributed around the ring, each running multiple digital signal processors (DSP) running at 4 kHz sampling rate with a proportional, integral, and derivative (PID) control algorithm. The particle and X-ray beam position data is shared by the distributed processors through networked reflective memory. A theory of closed orbit correction using the technique of singular value decomposition (SVD) of the response matrix and simulation of its application to the APS storage ring will be discussed. This technique combines the global and local feedback systems and resolves the conflict among multiple local feedback systems due to local bump closure error. Maximum correction efficiency is achieved by feeding back the global orbit data to the local feedback systems. The effect of the vacuum chamber eddy current induced by the AC corrector magnet field for local feedback systems is compensated by digital filters. Results of experiments conducted on the X-ray ring of the National Synchrotron Light Source and the SPEAR at Stanford Synchrotron Radiation Laboratory will be presented. copyright 1994 American Institute of Physics

  20. Beam position feedback system for the Advanced Photon Source

    International Nuclear Information System (INIS)

    Chung, Y.

    1993-01-01

    The Advanced Photon Source (APS) will implement both global and local beam position feedback systems to stabilize the particle and X-ray beams for the storage ring. The systems consist of 20 VME crates distributed around the ring, each running multiple digital signal processors (DSP) running at 4kHz sampling rate with a proportional, integral, and derivative (PID) control algorithm. The particle and X-ray beam position data is shared by the distributed processors through networked reflective memory. A theory of closed orbit correction using the technique of singular value decomposition (SVD) of the response matrix and simulation of its application to the APS storage ring will be discussed. This technique combines the global and local feedback systems and resolves the conflict among multiple local feedback systems due to local bump closure error. Maximum correction efficiency is achieved by feeding back the global orbit data to the local feedback systems. The effect of the vacuum chamber eddy current induced by the AC corrector magnet field for local feedback systems is compensated by digital filters. Results of experiments conducted on the X-ray ring of the National Synchrotron Light Source and the SPEAR at Stanford Synchrotron Radiation Laboratory will be presented

  1. Beam position feedback system for the Advanced Photon Source

    International Nuclear Information System (INIS)

    Chung, Y.

    1993-01-01

    The Advanced Photon Source (APS) will implement both global and local beam position feedback systems to stabilize the particle and X-ray beams for the storage ring. The systems consist of 20 VME crates distributed around the ring, each running multiple digital signal processors (DSP) running at 4kHz sampling rate with a proportional, integral, and derivative (PID) control algorithm. The particle and X-ray beam position data is shared by the distributed processors through networked reflective memory. A theory of closed orbit correction using the technique of singular value decomposition (SVD) of the response matrix and simulation of its application to the APS storage ring will be discussed. This technique combines the global and local feedback systems and resolves the conflict among multiple local feedback systems due to local bump closure error. Maximum correction efficiency is achieved by feeding back the global orbit data to the local feedback systems. The effect of the eddy current induced in the relatively thick (1/2 inch) vacuum chamber by the AC corrector magnet field for local feedback systems is compensated by digital filters. Results of experiments conducted on the X-ray ring of the National Synchrotron Light Source and the SPEAR at Stanford Synchrotron Radiation Laboratory will also be presented

  2. System and method for determining stability of a neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2011-01-01

    Disclosed are methods, systems, and computer-readable media for determining stability of a neural system. The method includes tracking a function world line of an N element neural system within at least one behavioral space, determining whether the tracking function world line is approaching a psychological stability surface, and implementing a quantitative solution that corrects instability if the tracked function world line is approaching the psychological stability surface.

  3. H∞ synchronization of chaotic systems via dynamic feedback approach

    International Nuclear Information System (INIS)

    Lee, S.M.; Ji, D.H.; Park, Ju H.; Won, S.C.

    2008-01-01

    This Letter considers H ∞ synchronization of a general class of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance to an H ∞ norm constraint. A dynamic feedback control scheme is proposed for H ∞ synchronization in chaotic systems for the first time. Then, a criterion for existence of the controller is given in terms of LMIs. Finally, a numerical simulation is presented to show the effectiveness of the proposed chaos synchronization scheme

  4. Decoupling control of vehicle chassis system based on neural network inverse system

    Science.gov (United States)

    Wang, Chunyan; Zhao, Wanzhong; Luan, Zhongkai; Gao, Qi; Deng, Ke

    2018-06-01

    Steering and suspension are two important subsystems affecting the handling stability and riding comfort of the chassis system. In order to avoid the interference and coupling of the control channels between active front steering (AFS) and active suspension subsystems (ASS), this paper presents a composite decoupling control method, which consists of a neural network inverse system and a robust controller. The neural network inverse system is composed of a static neural network with several integrators and state feedback of the original chassis system to approach the inverse system of the nonlinear systems. The existence of the inverse system for the chassis system is proved by the reversibility derivation of Interactor algorithm. The robust controller is based on the internal model control (IMC), which is designed to improve the robustness and anti-interference of the decoupled system by adding a pre-compensation controller to the pseudo linear system. The results of the simulation and vehicle test show that the proposed decoupling controller has excellent decoupling performance, which can transform the multivariable system into a number of single input and single output systems, and eliminate the mutual influence and interference. Furthermore, it has satisfactory tracking capability and robust performance, which can improve the comprehensive performance of the chassis system.

  5. Automatic Thermal Control System with Temperature Difference or Derivation Feedback

    Directory of Open Access Journals (Sweden)

    Darina Matiskova

    2016-02-01

    Full Text Available Automatic thermal control systems seem to be non-linear systems with thermal inertias and time delay. A controller is also non-linear because its information and power signals are limited. The application of methods that are available to on-linear systems together with computer simulation and mathematical modelling creates a possibility to acquire important information about the researched system. This paper provides a new look at the heated system model and also designs the structure of the thermal system with temperature derivation feedback. The designed system was simulated by using a special software in Turbo Pascal. Time responses of this system are compared to responses of a conventional thermal system. The thermal system with temperature derivation feedback provides better transients, better quality of regulation and better dynamical properties.

  6. Analysis of complex systems using neural networks

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  7. Collaborative Recurrent Neural Networks forDynamic Recommender Systems

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population

  8. Theoretical treatment of transverse feedback systems with memory

    International Nuclear Information System (INIS)

    Cornacchia, M.; Wang, J.M.

    1981-01-01

    The differential equation of the dipole moment of coherent oscillations in the presence of a feedback system is derived. The analysis, which starts in the time domain, is extended to the frequency domain; this allows a straightforward derivation of the damping rate for both coasting and bunched beams. The damping rate is expressed in terms of the transfer function of the feedback system and in a general form which takes into account the β-function and betatron phase modulation along the beam trajectory, the effect of memory arising from the finiteness of the system bandwidth, the effect of the time delay and of the betatron phase advance between detector and kicker. Some examples of the dependence of the damping rate on the feedback parameters are given

  9. Introducing a feedback training system for guided home rehabilitation

    Directory of Open Access Journals (Sweden)

    Disselhorst-Klug Catherine

    2010-01-01

    Full Text Available Abstract As the number of people requiring orthopaedic intervention is growing, individualized physiotherapeutic rehabilitation and adequate postoperative care becomes increasingly relevant. The chances of improvement in the patients condition is directly related to the performance and consistency of the physiotherapeutic exercises. In this paper a smart, cost-effective and easy to use Feedback Training System for home rehabilitation based on standard resistive elements is introduced. This ensures high accuracy of the exercises performed and offers guidance and control to the patient by offering direct feedback about the performance of the movements. 46 patients were recruited and performed standard physiotherapeutic training to evaluate the system. The results show a significant increase in the patient's ability to reproduce even simple physiotherapeutic exercises when being supported by the Feedback Training System. Thus physiotherapeutic training can be extended into the home environment whilst ensuring a high quality of training.

  10. Introducing a feedback training system for guided home rehabilitation.

    Science.gov (United States)

    Kohler, Fabian; Schmitz-Rode, Thomas; Disselhorst-Klug, Catherine

    2010-01-15

    As the number of people requiring orthopaedic intervention is growing, individualized physiotherapeutic rehabilitation and adequate postoperative care becomes increasingly relevant. The chances of improvement in the patients condition is directly related to the performance and consistency of the physiotherapeutic exercises.In this paper a smart, cost-effective and easy to use Feedback Training System for home rehabilitation based on standard resistive elements is introduced. This ensures high accuracy of the exercises performed and offers guidance and control to the patient by offering direct feedback about the performance of the movements.46 patients were recruited and performed standard physiotherapeutic training to evaluate the system. The results show a significant increase in the patient's ability to reproduce even simple physiotherapeutic exercises when being supported by the Feedback Training System. Thus physiotherapeutic training can be extended into the home environment whilst ensuring a high quality of training.

  11. Persistent disturbance rejection via state feedback for networked control systems

    Energy Technology Data Exchange (ETDEWEB)

    Yue Dong [Institute of Information and Control Engineering Technology, Nanjing Normal University, 78 Bancang Street, Nanjing, Jiangsu 210042 (China)], E-mail: medongy@njnu.edu.cn; Lam, James [Department of Mechanical Engineering, University of Hong Kong, Pokfulam Road (Hong Kong); Wang Zidong [Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH (United Kingdom)], E-mail: Zidong.Wang@brunel.ac.uk

    2009-04-15

    The problem of persistent disturbance rejection via state feedback for networked control systems is concerned based on the Lyapunov function method. The effect of the network conditions, such as network-induced delay and data dropout, is considered in the modeling of the system. It is assumed that the state and the control signals are individually quantized by quantizers on the sensor side and the controller side. The feedback gain and the quantizer parameters that guarantee the internal stability and the disturbance rejection performance of the closed-loop system are obtained by solving some linear matrix inequalities. To illustrate the effectiveness of the proposed method, a numerical example is provided for the design of the feedback gain and the quantizer parameters.

  12. A multipoint feedback control system for scanned focussed ultrasound hyperthermia

    International Nuclear Information System (INIS)

    Johnson, C.; Kress, R.; Roemer, R.; Hynynen, K.

    1987-01-01

    A multipoint feedback control system has been developed and tested for use with a scanned focussed ultrasound hyperthermia system. Extensive in-vivo tests (using a perfused organ model) have been made to evaluate the basic performance characteristics of the feedback control scheme for control of temperature in perfused media. The results of these tests are presented and compared with the predictions of a simulation routine. The control scheme was also tested in vivo using dogs' thighs and kidneys. Thigh experiments show the control scheme responds well to the affects of vasodilation and is able to maintain the targeted temperatures. In kidney experiments, where the rate of perfusion was controllable, the power adjusting algorithm successfully maintained uniform temperature distributions across regions of varying rates of perfusion. As a conclusion, the results show that this multipoint feedback controller scheme induces uniform temperature distributions when used with scanned focussed ultrasound systems

  13. Survey of Digital Feedback Systems in High Current Storage Rings

    International Nuclear Information System (INIS)

    Teytelman, Dmitry

    2003-01-01

    In the last decade demand for brightness in synchrotron light sources and luminosity in circular colliders led to construction of multiple high current storage rings. Many of these new machines require feedback systems to achieve design stored beam currents. In the same time frame the rapid advances in the technology of digital signal processing allowed the implementation of these complex feedback systems. In this paper I concentrate on three applications of feedback to storage rings: orbit control in light sources, coupled-bunch instability control, and low-level RF control. Each of these applications is challenging in areas of processing bandwidth, algorithm complexity, and control of time-varying beam and system dynamics. I will review existing implementations as well as comment on promising future directions

  14. Persistent disturbance rejection via state feedback for networked control systems

    International Nuclear Information System (INIS)

    Yue Dong; Lam, James; Wang Zidong

    2009-01-01

    The problem of persistent disturbance rejection via state feedback for networked control systems is concerned based on the Lyapunov function method. The effect of the network conditions, such as network-induced delay and data dropout, is considered in the modeling of the system. It is assumed that the state and the control signals are individually quantized by quantizers on the sensor side and the controller side. The feedback gain and the quantizer parameters that guarantee the internal stability and the disturbance rejection performance of the closed-loop system are obtained by solving some linear matrix inequalities. To illustrate the effectiveness of the proposed method, a numerical example is provided for the design of the feedback gain and the quantizer parameters.

  15. Design of a Haptic Feedback System for Flight Envelope Protection

    NARCIS (Netherlands)

    Van Baelen, D.; Ellerbroek, J.; van Paassen, M.M.; Mulder, M.

    2018-01-01

    Current Airbus aircraft use a fly-by-wire control device: a passive spring-damper system which generates, without any force feedback, an electrical signal to the flight control computer. Additionally, a hard flight envelope protection system is used which can limit the inputs of the pilot when

  16. A method for calculating active feedback system to provide vertical ...

    Indian Academy of Sciences (India)

    Slow instabilities, development time of which is proportional to the .... where (w, I) denotes the scalar (inner or dot) product of vectors w and I. Solutions ... which the system of passive conductors must satisfy. ..... In this research, the active feedback system consisting of two coils with coordi- .... a new mode becomes dominant.

  17. Haptic feedback designs in teleoperation systems for minimal invasive surgery

    NARCIS (Netherlands)

    Font, I.; Weiland, S.; Franken, M.; Steinbuch, M.; Rovers, A.F.

    2004-01-01

    One of the major shortcomings of state-of-the-art robotic systems for minimal invasive surgery is the lack of haptic feedback for the surgeon. In order to provide haptic information, sensors and actuators have to be added to the master and slave device. A control system should process the data and

  18. Synchronization of spatiotemporal chaotic systems by feedback control

    International Nuclear Information System (INIS)

    Lai, Y.; Grebogi, C.

    1994-01-01

    We demonstrate that two identical spatiotemporal chaotic systems can be synchronized by (1) linking one or a few of their dynamical variables, and (2) applying a small feedback control to one of the systems. Numerical examples using the diffusively coupled logistic map lattice are given. The effect of noise and the limitation of the technique are discussed

  19. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

    Science.gov (United States)

    Fei, Juntao; Lu, Cheng

    2018-04-01

    In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

  20. Stability of digital feedback control systems

    Directory of Open Access Journals (Sweden)

    Larkin Eugene

    2018-01-01

    Lag time characteristics are used for investigation of stability of linear systems. Digital PID controller is divided onto linear part, which is realized with a soft and pure lag unit, which is realized with both hardware and software. With use notions amplitude and phase margins, condition for stability of system functioning are obtained. Theoretical results are confirm with computer experiment carried out on the third-order system.

  1. Event-triggered output feedback control for distributed networked systems.

    Science.gov (United States)

    Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

    2016-01-01

    This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  2. IMPLEMENTATION OF NEURAL - CRYPTOGRAPHIC SYSTEM USING FPGA

    Directory of Open Access Journals (Sweden)

    KARAM M. Z. OTHMAN

    2011-08-01

    Full Text Available Modern cryptography techniques are virtually unbreakable. As the Internet and other forms of electronic communication become more prevalent, electronic security is becoming increasingly important. Cryptography is used to protect e-mail messages, credit card information, and corporate data. The design of the cryptography system is a conventional cryptography that uses one key for encryption and decryption process. The chosen cryptography algorithm is stream cipher algorithm that encrypt one bit at a time. The central problem in the stream-cipher cryptography is the difficulty of generating a long unpredictable sequence of binary signals from short and random key. Pseudo random number generators (PRNG have been widely used to construct this key sequence. The pseudo random number generator was designed using the Artificial Neural Networks (ANN. The Artificial Neural Networks (ANN providing the required nonlinearity properties that increases the randomness statistical properties of the pseudo random generator. The learning algorithm of this neural network is backpropagation learning algorithm. The learning process was done by software program in Matlab (software implementation to get the efficient weights. Then, the learned neural network was implemented using field programmable gate array (FPGA.

  3. Simulating neural systems with Xyce.

    Energy Technology Data Exchange (ETDEWEB)

    Schiek, Richard Louis; Thornquist, Heidi K.; Mei, Ting; Warrender, Christina E.; Aimone, James Bradley; Teeter, Corinne; Duda, Alex M.

    2012-12-01

    Sandias parallel circuit simulator, Xyce, can address large scale neuron simulations in a new way extending the range within which one can perform high-fidelity, multi-compartment neuron simulations. This report documents the implementation of neuron devices in Xyce, their use in simulation and analysis of neuron systems.

  4. Diamond Light Source Booster fast orbit feedback system

    International Nuclear Information System (INIS)

    Gayadeen, S.; Duncan, S.R.; Christou, C.; Heron, M.T.; Rowland, J.

    2012-01-01

    The Fast Orbit Feedback system that has been installed on the Diamond Light Source Storage ring has been replicated on the Booster synchrotron in order to provide a test bed for the development of the Storage Ring controller design. To realise this the Booster is operated in DC mode. The electron beam is regulated in two planes using the Fast Orbit Feedback system, which takes the beam position from 22 beam position monitors for each plane, and calculates offsets to 44 corrector power supplies at a sample rate of 10 kHz. This paper describes the design and realization of the controller for the Booster Fast Orbit Feedback, presents results from the implementation and considers future development

  5. Swing Damping for Helicopter Slung Load Systems using Delayed Feedback

    DEFF Research Database (Denmark)

    Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

    2009-01-01

    of swing. The design of the delayed feedback controller is presented as an optimization problem which gives the possibility of an automated design process. Simulations and flight test verifications of the control system on two different autonomous helicopters are presented and it is shown how a significant......This paper presents the design and verification of a swing reducing controller for helicopter slung load systems using intentional delayed feedback. It is intended for augmenting a trajectory tracking helicopter controller and thereby improving the slung load handing capabilities for autonomous...... helicopters. The delayed feedback controller is added to actively reduce oscillations of the slung load by improving the damping of the slung load pendulum modes. Furthermore, it is intended for integration with a feedforward control scheme based on input shaping for concurrent avoidance and dampening...

  6. Cultural shaping of neural responses: Feedback-related potentials vary with self-construal and face priming.

    Science.gov (United States)

    Hitokoto, Hidefumi; Glazer, James; Kitayama, Shinobu

    2016-01-01

    Previous work shows that when an image of a face is presented immediately prior to each trial of a speeded cognitive task (face-priming), the error-related negativity (ERN) is upregulated for Asians, but it is downregulated for Caucasians. These findings are consistent with the hypothesis that images of "generalized other" vary cross-culturally such that they evoke anxiety for Asians, whereas they serve as safety cues for Caucasians. Here, we tested whether the cross-cultural variation in the face-priming effect would be observed in a gambling paradigm. Caucasian Americans, Asian Americans, and Asian sojourners were exposed to a brief flash of a schematic face during a gamble. For Asian Americans, face-priming resulted in significant increases of both negative-going deflection of ERP upon negative feedback (feedback-related negativity [FRN]) and positive-going deflection of ERP upon positive feedback (feedback-related positivity [FRP]). For Caucasian Americans, face-priming showed a significant reversal, decreasing both FRN and FRP. The cultural difference in the face-priming effect in FRN and FRP was partially mediated by interdependent self-construal. Curiously, Asian sojourners showed a pattern similar to the one for Caucasian Americans. Our findings suggest that culture shapes neural pathways in both systematic and highly dynamic fashion. © 2015 Society for Psychophysiological Research.

  7. Operating experience feedback report - Air systems problems

    International Nuclear Information System (INIS)

    Ornstein, H.L.

    1987-12-01

    This report highlights significant operating events involving observed or potential failures of safety-related systems in U.S. plants that resulted from degraded or malfunctioning non-safety grade air systems. Based upon the evaluation of these events, the Office for Analysis and Evaluation of Operational Data (AEOD) concludes that the issue of air systems problems is an important one which requires additional NRC and industry attention. This report also provides AEOD's recommendations for corrective actions to deal with the issue. (author)

  8. Dynamics of nonlinear feedback control

    NARCIS (Netherlands)

    Snippe, H.P.; Hateren, J.H. van

    Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain

  9. Chaos synchronization in autonomous chaotic system via hybrid feedback control

    International Nuclear Information System (INIS)

    Yang Lixin; Chu Yandong; Zhang Jiangang; Li Xianfeng; Chang Yingxiang

    2009-01-01

    This paper presents the synchronization of chaos by designing united controller. First, this method is implemented in synchronization of a simple system, then we realize the synchronization of Lue hyperchaotic system, we also take tracking control to realize the synchronization of Lue hyperchaotic system. Comparing with results, we can find that hybrid feedback control approach is more effective than tracking control for hyperchaotic system. Numerical simulations show the united synchronization method works well.

  10. Reduced risk avoidance and altered neural correlates of feedback processing in patients with borderline personality disorder.

    Science.gov (United States)

    Endrass, Tanja; Schuermann, Beate; Roepke, Stefan; Kessler-Scheil, Sonia; Kathmann, Norbert

    2016-09-30

    Patients with borderline personality disorder (BPD) show deficits in reward-guided decision making and learning. The present study examined risk-taking behavior in combination with feedback processing. Eighteen BPD patients and 18 healthy controls performed a probabilistic two-choice gambling task, while an electroencephalogram was recorded. Options differed in risk, but were identical in expected value and outcome probability. The feedback-related negativity (FRN) and the feedback-related P300 were analyzed. Healthy controls preferred low-risk over high-risk options, whereas BPD patients chose both option with equal probability. FRN amplitudes were reduced in BPD, but effects of feedback valence and risk did not differ between groups. This suggests attenuated outcome processing in the anterior cingulate cortex, but intact reward prediction error signaling. Furthermore, the modulation of the feedback-related P300 with feedback valence and risk was smaller in BPD patients, and decreased P300 amplitudes were associated with increased behavioral risk-taking behavior. These findings could relate to the reduced ability of BPD patients to learn and adequately adjust their behavior based on feedback information, possibly due to reduced significance of negative feedback. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. [Real-time feedback systems for improvement of resuscitation quality].

    Science.gov (United States)

    Lukas, R P; Van Aken, H; Engel, P; Bohn, A

    2011-07-01

    The quality of chest compression is a determinant of survival after cardiac arrest. Therefore, the European Resuscitation Council (ERC) 2010 guidelines on resuscitation strongly focus on compression quality. Despite its impact on survival, observational studies have shown that chest compression quality is not reached by professional rescue teams. Real-time feedback devices for resuscitation are able to measure chest compression during an ongoing resuscitation attempt through a sternal sensor equipped with a motion and pressure detection system. In addition to the electrocardiograph (ECG) ventilation can be detected by transthoracic impedance monitoring. In cases of quality deviation, such as shallow chest compression depth or hyperventilation, feedback systems produce visual or acoustic alarms. Rescuers can thereby be supported and guided to the requested quality in chest compression and ventilation. Feedback technology is currently available both as a so-called stand-alone device and as an integrated feature in a monitor/defibrillator unit. Multiple studies have demonstrated sustainable enhancement in the education of resuscitation due to the use of real-time feedback technology. There is evidence that real-time feedback for resuscitation combined with training and debriefing strategies can improve both resuscitation quality and patient survival. Chest compression quality is an independent predictor for survival in resuscitation and should therefore be measured and documented in further clinical multicenter trials.

  12. Delayed feedback control of fractional-order chaotic systems

    International Nuclear Information System (INIS)

    Gjurchinovski, A; Urumov, V; Sandev, T

    2010-01-01

    We study the possibility to stabilize unstable steady states and unstable periodic orbits in chaotic fractional-order dynamical systems by the time-delayed feedback method. By performing a linear stability analysis, we establish the parameter ranges for successful stabilization of unstable equilibria in the plane parameterized by the feedback gain and the time delay. An insight into the control mechanism is gained by analyzing the characteristic equation of the controlled system, showing that the control scheme fails to control unstable equilibria having an odd number of positive real eigenvalues. We demonstrate that the method can also stabilize unstable periodic orbits for a suitable choice of the feedback gain, providing that the time delay is chosen to coincide with the period of the target orbit. In addition, it is shown numerically that delayed feedback control with a sinusoidally modulated time delay significantly enlarges the stability region of steady states in comparison to the classical time-delayed feedback scheme with a constant delay.

  13. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    Science.gov (United States)

    1996-01-01

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

  14. TFTR power conversion and plasma feedback systems

    International Nuclear Information System (INIS)

    Neumeyer, C.

    1985-01-01

    Major components of the Tokamak Fusion Test Reactor (TFTR) power conversion system include 39 thyristor rectifier power supplies, 12 energy storage capacitor banks, and 6 ohmic heating interrupters. These components are connected in various series/parallel configurations to provide controlled pulses of current to the Toroidal Field (TF), Ohmic Heating (OH), Equilibrium (vertical) Field (EF), and Horizontal Field (HF) magnet coil systems. Real-time control of the power conversion system is accomplished by a centralized dedicated computer; local control is minimal. Power supply firing angles, capacitor bank charge and discharge commands, interrupter commands, etc., are all determined and issued by the central computer. Plasma Position and Current Control (PPCC) reference signals to power conversion (OH, EF, HF) are determined by separate analog electronics but invoked through the power conversion computer. Real-time fault sensing of plasma parameters, gas injection, neutral beams, etc., are monitored by a separate Discharge Fault System (DFS) but routed through the power conversion computer for pre-programmed shutdown response

  15. Boundary feedback stabilization of distributed parameter systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1988-01-01

    The author introduces the method of pseudo-differential stabilization. He notes that the theory of pseudo-differential boundary operators is a fruitful approach to problems arising in control and stabilization theory of distributed-parameter systems. The basic pseudo-differential calculus can...

  16. Beam excitation and damping with the transverse feedback system

    International Nuclear Information System (INIS)

    Pellegrin, J.L.; Rees, J.R.

    1979-08-01

    The questions often come up, ''What is the strength if the beam excitation system? How much damping can the transverse feedback provide?'' The design is now advanced enough to answer these questions; also, laboratory tests of some components have been conducted and we know what can be expected of the hardware. This paper discusses these questions

  17. Time-optimal feedback control for linear systems

    International Nuclear Information System (INIS)

    Mirica, S.

    1976-01-01

    The paper deals with the results of qualitative investigations of the time-optimal feedback control for linear systems with constant coefficients. In the first section, after some definitions and notations, two examples are given and it is shown that even the time-optimal control problem for linear systems with constant coefficients which looked like ''completely solved'' requires a further qualitative investigation of the stability to ''permanent perturbations'' of optimal feedback control. In the second section some basic results of the linear time-optimal control problem are reviewed. The third section deals with the definition of Boltyanskii's ''regular synthesis'' and its connection to Filippov's theory of right-hand side discontinuous differential equations. In the fourth section a theorem is proved concerning the stability to perturbations of time-optimal feedback control for linear systems with scalar control. In the last two sections it is proved that, if the matrix which defines the system has only real eigenvalues or is three-dimensional, the time-optimal feedback control defines a regular synthesis and therefore is stable to perturbations. (author)

  18. Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

    Science.gov (United States)

    Xia, Feng; Ma, Longhua; Peng, Chen; Sun, Youxian; Dong, Jinxiang

    2008-01-01

    There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN. PMID:27879934

  19. Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

    Directory of Open Access Journals (Sweden)

    Jinxiang Dong

    2008-07-01

    Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.

  20. Architecture of the APS real-time orbit feedback system

    International Nuclear Information System (INIS)

    Carwardine, J. A.; Lenkszus, F. R.

    1997-01-01

    The APS Real-Time Orbit Feedback System is designed to stabilize the orbit of the stored positron beam against low-frequency sources such as mechanical vibration and power supply ripple. A distributed array of digital signal processors is used to measure the orbit and compute corrections at a 1kHz rate. The system also provides extensive beam diagnostic tools. This paper describes the architectural aspects of the system and describes how the orbit correction algorithms are implemented

  1. Architecture of the APS real-time orbit feedback system.

    Energy Technology Data Exchange (ETDEWEB)

    Carwardine, J. A.; Lenkszus, F. R.

    1997-11-21

    The APS Real-Time Orbit Feedback System is designed to stabilize the orbit of the stored positron beam against low-frequency sources such as mechanical vibration and power supply ripple. A distributed array of digital signal processors is used to measure the orbit and compute corrections at a 1kHz rate. The system also provides extensive beam diagnostic tools. This paper describes the architectural aspects of the system and describes how the orbit correction algorithms are implemented.

  2. Feedback linearizing control of a MIMO power system

    Science.gov (United States)

    Ilyes, Laszlo

    Prior research has demonstrated that either the mechanical or electrical subsystem of a synchronous electric generator may be controlled using single-input single-output (SISO) nonlinear feedback linearization. This research suggests a new approach which applies nonlinear feedback linearization to a multi-input multi-output (MIMO) model of the synchronous electric generator connected to an infinite bus load model. In this way, the electrical and mechanical subsystems may be linearized and simultaneously decoupled through the introduction of a pair of auxiliary inputs. This allows well known, linear, SISO control methods to be effectively applied to the resulting systems. The derivation of the feedback linearizing control law is presented in detail, including a discussion on the use of symbolic math processing as a development tool. The linearizing and decoupling properties of the control law are validated through simulation. And finally, the robustness of the control law is demonstrated.

  3. Decoherence control in open quantum systems via classical feedback

    International Nuclear Information System (INIS)

    Ganesan, Narayan; Tarn, Tzyh-Jong

    2007-01-01

    In this work we propose a strategy using techniques from systems theory to completely eliminate decoherence and also provide conditions under which it can be done. A construction employing an auxiliary system, the bait, which is instrumental to decoupling the system from the environment is presented. Our approach to decoherence control in contrast to other approaches in the literature involves the bilinear input affine model of quantum control system which lends itself to various techniques from classical control theory, but with nontrivial modifications to the quantum regime. The elegance of this approach yields interesting results on open loop decouplability and decoherence free subspaces. Additionally, the feedback control of decoherence may be related to disturbance decoupling for classical input affine systems, which entails careful application of the methods by avoiding all the quantum mechanical pitfalls. In the process of calculating a suitable feedback the system must be restructured due to its tensorial nature of interaction with the environment, which is unique to quantum systems. In the subsequent section we discuss a general information extraction scheme to gain knowledge of the state and the amount of decoherence based on indirect continuous measurement. The analysis of continuous measurement on a decohering quantum system has not been extensively studied before. Finally, a methodology to synthesize feedback parameters itself is given, that technology permitting, could be implemented for practical 2-qubit systems to perform decoherence free quantum computing. The results obtained are qualitatively different and superior to the ones obtained via master equations

  4. Dynamics of nonlinear feedback control

    OpenAIRE

    Snippe, H.P.; Hateren, J.H. van

    2007-01-01

    Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input step...

  5. Dynamic artificial neural networks with affective systems.

    Directory of Open Access Journals (Sweden)

    Catherine D Schuman

    Full Text Available Artificial neural networks (ANNs are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP and long term depression (LTD, and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.

  6. Dynamical systems, attractors, and neural circuits.

    Science.gov (United States)

    Miller, Paul

    2016-01-01

    Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

  7. Feedbacks between conservation and social-ecological systems

    Science.gov (United States)

    Miller, Brian W.; Caplow, Susan C.; Leslie, Paul W.

    2012-01-01

    Robust ways to meet objectives of environmental conservation and social and economic development remain elusive. This struggle may in part be related to insufficient understanding of the feedbacks between conservation initiatives and social-ecological systems, specifically, the ways in which conservation initiatives result in social changes that have secondary effects on the environments targeted by conservation. To explore this idea we sampled peer-reviewed articles addressing the social and environmental dimensions of conservation and coded each paper according to its research focus and characterization of these feedbacks. The majority of articles in our sample focused either on the effect of conservation initiatives on people (e.g., relocation, employment) or the effect of people on the environment (e.g., fragmentation, conservation efficacy of traditional management systems). Few studies in our sample empirically addressed both the social dynamics resulting from conservation initiatives and subsequent environmental effects. In many cases, one was measured and the other was discussed anecdotally. Among the studies that describe feedbacks between social and environmental variables, there was more evidence of positive (amplifying) feedbacks between social and environmental outcomes (i.e., undesirable social outcomes yielded undesirable environmental effects, and desirable social outcomes yielded desirable environmental effects). The major themes within the sampled literature include conflict between humans and wild animals, social movements, adaptive comanagement, loss of traditional management systems, traditional ecological knowledge, human displacement and risks to livelihoods, and conservation and development. The narratives associated with each theme can serve as hypotheses for facilitating further discussion about conservation issues and for catalyzing future studies of the feedbacks between conservation and social-ecological systems. PMID:22443128

  8. Modeling mutual feedback between users and recommender systems

    Science.gov (United States)

    Zeng, An; Yeung, Chi Ho; Medo, Matúš; Zhang, Yi-Cheng

    2015-07-01

    Recommender systems daily influence our decisions on the Internet. While considerable attention has been given to issues such as recommendation accuracy and user privacy, the long-term mutual feedback between a recommender system and the decisions of its users has been neglected so far. We propose here a model of network evolution which allows us to study the complex dynamics induced by this feedback, including the hysteresis effect which is typical for systems with non-linear dynamics. Despite the popular belief that recommendation helps users to discover new things, we find that the long-term use of recommendation can contribute to the rise of extremely popular items and thus ultimately narrow the user choice. These results are supported by measurements of the time evolution of item popularity inequality in real systems. We show that this adverse effect of recommendation can be tamed by sacrificing part of short-term recommendation accuracy.

  9. Commissioning of the APS real-time orbit feedback system

    International Nuclear Information System (INIS)

    Carwardine, J.; Decker, G.; Evans, K. Jr.; Hillman, A.; Lenkszus, F.; Merl, R.; Pietryla, A.

    1997-01-01

    A unified global and local closed-orbit feedback system has been implemented at the Advanced Photon Source in order to stabilize both particle and photon beams. Beam stability requirements in the band up to 50 Hz are 17 microm in the horizontal plane and 4.4 microm vertically. Orbit feedback algorithms are implemented digitally using multiple digital signal processors, with computing power distributed in 20 VME crates around the storage ring. Each crate communicates with all others via a fast reflective memory network. The system has access to 320 rf beam position monitors together with x-ray beam position monitors in both insertion device and bending magnet beamlines. Up to 317 corrector magnets are available to the system. The global system reduces horizontal rms beam motion at the x-ray source points by more than a factor of two in the frequency band from 10 mHz to 50 Hz

  10. Neural System Prediction and Identification Challenge

    Directory of Open Access Journals (Sweden)

    Ioannis eVlachos

    2013-12-01

    Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  11. Neural system prediction and identification challenge.

    Science.gov (United States)

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  12. Autonomous learning by simple dynamical systems with delayed feedback.

    Science.gov (United States)

    Kaluza, Pablo; Mikhailov, Alexander S

    2014-09-01

    A general scheme for the construction of dynamical systems able to learn generation of the desired kinds of dynamics through adjustment of their internal structure is proposed. The scheme involves intrinsic time-delayed feedback to steer the dynamics towards the target performance. As an example, a system of coupled phase oscillators, which can, by changing the weights of connections between its elements, evolve to a dynamical state with the prescribed (low or high) synchronization level, is considered and investigated.

  13. The pointer basis and the feedback stabilization of quantum systems

    International Nuclear Information System (INIS)

    Li, L; Chia, A; Wiseman, H M

    2014-01-01

    The dynamics for an open quantum system can be ‘unravelled’ in infinitely many ways, depending on how the environment is monitored, yielding different sorts of conditioned states, evolving stochastically. In the case of ideal monitoring these states are pure, and the set of states for a given monitoring forms a basis (which is overcomplete in general) for the system. It has been argued elsewhere (Atkins et al 2005 Europhys. Lett. 69 163) that the ‘pointer basis’ as introduced by Zurek et al (1993 Phys. Rev. Lett. 70 1187), should be identified with the unravelling-induced basis which decoheres most slowly. Here we show the applicability of this concept of pointer basis to the problem of state stabilization for quantum systems. In particular we prove that for linear Gaussian quantum systems, if the feedback control is assumed to be strong compared to the decoherence of the pointer basis, then the system can be stabilized in one of the pointer basis states with a fidelity close to one (the infidelity varies inversely with the control strength). Moreover, if the aim of the feedback is to maximize the fidelity of the unconditioned system state with a pure state that is one of its conditioned states, then the optimal unravelling for stabilizing the system in this way is that which induces the pointer basis for the conditioned states. We illustrate these results with a model system: quantum Brownian motion. We show that even if the feedback control strength is comparable to the decoherence, the optimal unravelling still induces a basis very close to the pointer basis. However if the feedback control is weak compared to the decoherence, this is not the case. (paper)

  14. Linear feedback control, adaptive feedback control and their combination for chaos (lag) synchronization of LC chaotic systems

    International Nuclear Information System (INIS)

    Yan Zhenya; Yu Pei

    2007-01-01

    In this paper, we study chaos (lag) synchronization of a new LC chaotic system, which can exhibit not only a two-scroll attractor but also two double-scroll attractors for different parameter values, via three types of state feedback controls: (i) linear feedback control; (ii) adaptive feedback control; and (iii) a combination of linear feedback and adaptive feedback controls. As a consequence, ten families of new feedback control laws are designed to obtain global chaos lag synchronization for τ < 0 and global chaos synchronization for τ = 0 of the LC system. Numerical simulations are used to illustrate these theoretical results. Each family of these obtained feedback control laws, including two linear (adaptive) functions or one linear function and one adaptive function, is added to two equations of the LC system. This is simpler than the known synchronization controllers, which apply controllers to all equations of the LC system. Moreover, based on the obtained results of the LC system, we also derive the control laws for chaos (lag) synchronization of another new type of chaotic system

  15. Tutorial on beam-based feedback systems for linacs

    International Nuclear Information System (INIS)

    Hendrickson, L.; Allison, S.; Gromme, T.; Grossberg, P.; Himel, T.; Krauter, K.; MacKenzie, R.; Ross, M.; Sass, R.; Shoaee, H.

    1994-08-01

    A generalized fast feedback system stabilizes beams in the SLC. It performs measurements and modifies actuator settings to control beam states such as position, angle, energy and intensity on a pulse to pulse basis. An adaptive cascade feature allows communication between a series of linac loops, avoiding overcorrection problems. The system is based on the state space formalism of digital control theory. Due to the database-driven design, new loops are added without requiring software modifications. Recent enhancements support the monitoring and control of nonlinear states such as beam phase using excitation techniques. In over three years of operation, the feedback system has grown from its original eight loops to more than fifty loops, and it has been invaluable in stabilizing the machine

  16. Approximate solutions of dual fuzzy polynomials by feed-back neural networks

    Directory of Open Access Journals (Sweden)

    Ahmad Jafarian

    2012-11-01

    Full Text Available Recently, artificial neural networks (ANNs have been extensively studied and used in different areas such as pattern recognition, associative memory, combinatorial optimization, etc. In this paper, we investigate the ability of fuzzy neural networks to approximate solution of a dual fuzzy polynomial of the form $a_{1}x+ ...+a_{n}x^n =b_{1}x+ ...+b_{n}x^n+d,$ where $a_{j},b_{j},d epsilon E^1 (for j=1,...,n.$ Since the operation of fuzzy neural networks is based on Zadeh's extension principle. For this scope we train a fuzzified neural network by back-propagation-type learning algorithm which has five layer where connection weights are crisp numbers. This neural network can get a crisp input signal and then calculates its corresponding fuzzy output. Presented method can give a real approximate solution for given polynomial by using a cost function which is defined for the level sets of fuzzy output and target output. The simulation results are presented to demonstrate the efficiency and effectiveness of the proposed approach.

  17. Stability and Bifurcation in Magnetic Flux Feedback Maglev Control System

    Directory of Open Access Journals (Sweden)

    Wen-Qing Zhang

    2013-01-01

    Full Text Available Nonlinear properties of magnetic flux feedback control system have been investigated mainly in this paper. We analyzed the influence of magnetic flux feedback control system on control property by time delay and interfering signal of acceleration. First of all, we have established maglev nonlinear model based on magnetic flux feedback and then discussed hopf bifurcation’s condition caused by the acceleration’s time delay. The critical value of delayed time is obtained. It is proved that the period solution exists in maglev control system and the stable condition has been got. We obtained the characteristic values by employing center manifold reduction theory and normal form method, which represent separately the direction of hopf bifurcation, the stability of the period solution, and the period of the period motion. Subsequently, we discussed the influence maglev system on stability of by acceleration’s interfering signal and obtained the stable domain of interfering signal. Some experiments have been done on CMS04 maglev vehicle of National University of Defense Technology (NUDT in Tangshan city. The results of experiments demonstrate that viewpoints of this paper are correct and scientific. When time lag reaches the critical value, maglev system will produce a supercritical hopf bifurcation which may cause unstable period motion.

  18. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    Science.gov (United States)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  19. Alterations in Neural Control of Constant Isometric Contraction with the Size of Error Feedback.

    Directory of Open Access Journals (Sweden)

    Ing-Shiou Hwang

    Full Text Available Discharge patterns from a population of motor units (MUs were estimated with multi-channel surface electromyogram and signal processing techniques to investigate parametric differences in low-frequency force fluctuations, MU discharges, and force-discharge relation during static force-tracking with varying sizes of execution error presented via visual feedback. Fourteen healthy adults produced isometric force at 10% of maximal voluntary contraction through index abduction under three visual conditions that scaled execution errors with different amplification factors. Error-augmentation feedback that used a high amplification factor (HAF to potentiate visualized error size resulted in higher sample entropy, mean frequency, ratio of high-frequency components, and spectral dispersion of force fluctuations than those of error-reducing feedback using a low amplification factor (LAF. In the HAF condition, MUs with relatively high recruitment thresholds in the dorsal interosseous muscle exhibited a larger coefficient of variation for inter-spike intervals and a greater spectral peak of the pooled MU coherence at 13-35 Hz than did those in the LAF condition. Manipulation of the size of error feedback altered the force-discharge relation, which was characterized with non-linear approaches such as mutual information and cross sample entropy. The association of force fluctuations and global discharge trace decreased with increasing error amplification factor. Our findings provide direct neurophysiological evidence that favors motor training using error-augmentation feedback. Amplification of the visualized error size of visual feedback could enrich force gradation strategies during static force-tracking, pertaining to selective increases in the discharge variability of higher-threshold MUs that receive greater common oscillatory inputs in the β-band.

  20. Feedback-Equivalence of Nonlinear Systems with Applications to Power System Equations.

    Science.gov (United States)

    Marino, Riccardo

    The key concept of the dissertation is feedback equivalence among systems affine in control. Feedback equivalence to linear systems in Brunovsky canonical form and the construction of the corresponding feedback transformation are used to: (i) design a nonlinear regulator for a detailed nonlinear model of a synchronous generator connected to an infinite bus; (ii) establish which power system network structures enjoy the feedback linearizability property and design a stabilizing control law for these networks with a constraint on the control space which comes from the use of d.c. lines. It is also shown that the feedback linearizability property allows the use of state feedback to contruct a linear controllable system with a positive definite linear Hamiltonian structure for the uncontrolled part if the state space is even; a stabilizing control law is derived for such systems. Feedback linearizability property is characterized by the involutivity of certain nested distributions for strongly accessible analytic systems; if the system is defined on a manifold M diffeomorphic to the Euclidean space, it is established that the set where the property holds is a submanifold open and dense in M. If an analytic output map is defined, a set of nested involutive distributions can be always defined and that allows the introduction of an observability property which is the dual concept, in some sense, to feedback linearizability: the goal is to investigate when a nonlinear system affine in control with an analytic output map is feedback equivalent to a linear controllable and observable system. Finally a nested involutive structure of distributions is shown to guarantee the existence of a state feedback that takes a nonlinear system affine in control to a single input one, both feedback equivalent to linear controllable systems, preserving one controlled vector field.

  1. On Optimal Feedback Control for Stationary Linear Systems

    International Nuclear Information System (INIS)

    Russell, David L.

    2010-01-01

    We study linear-quadratic optimal control problems for finite dimensional stationary linear systems AX+BU=Z with output Y=CX+DU from the viewpoint of linear feedback solution. We interpret solutions in relation to system robustness with respect to disturbances Z and relate them to nonlinear matrix equations of Riccati type and eigenvalue-eigenvector problems for the corresponding Hamiltonian system. Examples are included along with an indication of extensions to continuous, i.e., infinite dimensional, systems, primarily of elliptic type.

  2. Cognitive Strategy Use as an Index of Developmental Differences in Neural Responses to Feedback

    DEFF Research Database (Denmark)

    Andersen, Lau M.; Visser, Ingmar; Crone, Eveline A.

    2014-01-01

    strategy groups except for the best performing one. Strategy use was a mediator and largely explained the relation between age and variance in activation patterns in the DLPFC and the SPC, but not in the ACC. These findings are interpreted vis-à-vis age versus performance predictors of brain development....... Keywords: feedback learning, functional brain activation, development, latent mixture models, strategy use...

  3. Control of a local neural network by feedforward and feedback inhibition

    NARCIS (Netherlands)

    Remme, M.W.H.; Wadman, W.J.

    2004-01-01

    The signal transfer of a neuronal network is shaped by the local interactions between the excitatory principal cells and the inhibitory interneurons. We investigated with a simple lumped model how feedforward and feedback inhibition in.uence the steady-state network signal transfer. We analyze how

  4. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

    Science.gov (United States)

    Orhan, A Emin; Ma, Wei Ji

    2017-07-26

    Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

  5. The neural coding of feedback learning across child and adolescent development

    NARCIS (Netherlands)

    Peters, S.; Braams, B.R.; Raijmakers, M.E.J.; Koolschijn, P.C.M.P.; Crone, E.A.

    2014-01-01

    The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain

  6. Optimal feedback control of the forced van der Pol system

    International Nuclear Information System (INIS)

    Chagas, T.P.; Toledo, B.A.; Rempel, E.L.; Chian, A.C.-L.; Valdivia, J.A.

    2012-01-01

    A simple feedback control strategy for chaotic systems is investigated using the forced van der Pol system as an example. The strategy regards chaos control as an optimization problem, where the maximum magnitude Floquet multiplier of a target unstable periodic orbit (UPO) is used as a cost function that needs to be minimized. Thus, the method obtains the optimal control gain in terms of the stability of the target UPO. This strategy was recently proposed for the proportional feedback control (PFC) method. Here, it is extended to the highly popular delayed feedback control (DFC) method. Since the DFC method treats the system as a delay-differential equation whose phase space is infinite-dimensional, the characteristic multipliers are found through a truncation in the number of delayed states. Control of a target UPO is achieved for several values of the forcing amplitude. We compare the DFC and PFC methods in terms of stability of the controlled orbit, steady state error and control effort.

  7. Neural systems for preparatory control of imitation.

    Science.gov (United States)

    Cross, Katy A; Iacoboni, Marco

    2014-01-01

    Humans have an automatic tendency to imitate others. Previous studies on how we control these tendencies have focused on reactive mechanisms, where inhibition of imitation is implemented after seeing an action. This work suggests that reactive control of imitation draws on at least partially specialized mechanisms. Here, we examine preparatory imitation control, where advance information allows control processes to be employed before an action is observed. Drawing on dual route models from the spatial compatibility literature, we compare control processes using biological and non-biological stimuli to determine whether preparatory imitation control recruits specialized neural systems that are similar to those observed in reactive imitation control. Results indicate that preparatory control involves anterior prefrontal, dorsolateral prefrontal, posterior parietal and early visual cortices regardless of whether automatic responses are evoked by biological (imitative) or non-biological stimuli. These results indicate both that preparatory control of imitation uses general mechanisms, and that preparatory control of imitation draws on different neural systems from reactive imitation control. Based on the regions involved, we hypothesize that preparatory control is implemented through top-down attentional biasing of visual processing.

  8. Design of the ALS transverse coupled-bunch feedback system

    International Nuclear Information System (INIS)

    Barry, W.; Byrd, J.M.; Corlett, J.N.; Hinkson, J.; Johnson, J.; Lambertson, G.R.; Fox, J.D.

    1993-05-01

    Calculations of transverse coupled bunch growth rates in the Advanced Light Source (ALS), a 1.5 GeV electron storage ring for producing synchrotron radiation, indicate the need for damping via a transverse feedback (TFB) system. We present the design of such a system. The maximum bunch frequency is 500 MHz, requiring that the FB system have a broadband response of at least 250 MHz. We described, in detail, the choice of broadband components such as kickers, pickups, power amplifiers, and electronics

  9. Digital filter algorithm study and simulation of SSRF feedback system

    International Nuclear Information System (INIS)

    Han Lifeng; Yuan Renxian; Ye Kairong

    2008-01-01

    Least Square Fitting was used to design a FIR filter of the transverse feedback system for the Shanghai Synchrotron Radiation Facility (SSRF). The algorithm helped us to set appropriate gain and phase at special frequency points. This reduced the power needed for damping the beam oscillations, which was proved by System View signal simulation. And with AT (Accelerator Tool) simulation, the Gain calculation and settings to the output signals from the FIR filter were deduced. The relationship between the Kicker power and the system damping time was also given. (authors)

  10. ETSON proposal on the European operational experience feedback system

    International Nuclear Information System (INIS)

    Maqua, Michael; Bertrand, Remy; Gelder, Pieter de

    2007-01-01

    The new IAEA Safety Fundamentals states regarding the operating experience feedback: The feedback of operating experience from facilities and activities - and, where relevant, from elsewhere - is a key means of enhancing safety. Processes must be put in place for the feedback and analysis of operating experience, including initiating events, accident precursors, near misses, accidents and unauthorized acts, so that lessons may be learned, shared and acted upon. This presentation deals with the proposal of the ETSON (European TSO Network) to optimize the European operating experiences feedback (OEF). It is generally recognized that the efficiency of nuclear safety supervision by public authorities is based on two key requirements: - the existence of a competent authority at national level, benefiting from an appropriate legislative and regulatory basis, from adequate (quantitatively and qualitatively) human resources, particularly for inspection purposes, - the availability of resources devoted to highly specialised independent technical expertise, in order to provide competent authorities with pertinent technical opinions on: -- the safety files provided by operators, for the purpose of licensing corresponding activities, -- the exploitation for regulatory purposes of the operating experience feed back from licensed nuclear installations. There are two worldwide systems intended to learn lessons from experience: the WANO (World Association of Nuclear Operators) system established by the licensees with access restricted to operating organizations and the IRS system jointly operated by IAEA and OECD/NEA accessible to regulators and to some other users nominated by the regulators in their countries. The IRS itself is dedicated to the analysis of safety significant operating events. NEA/CNRA runs a permanent working group on operating experience (WGOE). WGOE provides among other things also generic reports on safety concerns related to operating experiences and

  11. Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

    Science.gov (United States)

    Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

    2018-03-01

    Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.

  12. Fast feedback system for energy and beam stabilization

    International Nuclear Information System (INIS)

    R. Dickson; V. Lebedev

    1999-01-01

    The electron beams being delivered to targets of the Continuous Electron Beam Accelerator Facility (CEBAF) at Thomas Jefferson National Accelerator Facility (Jefferson Lab) are plagued with undesirable positional and energy fluctuations. These fluctuations primarily occur at harmonics of the power line frequency (60, 120, 180, etc. hertz), and their cause is rooted in electromagnetic fields generated by accelerator electronic equipment. It is possible to largely nullify these deviations by applying real time corrections to electromagnets and RF verniers along the beam line. This concept has been successfully applied at Jefferson Lab by extensively modifying the existing Beam Position Monitor (BPM) system with the integration of an algorithm that computes correction signals targeted at the power line harmonics. Many of the modifications required were due to the existing CEBAF BPM system not having the data acquisition bandwidth needed for this type of feedback system. This paper will describe the techniques required to transform the CEBAF standard BPM system into a high speed practical fast feedback system that coexists with the large scale control system--the Experimental Physics and Industrial Control System (EPICS)--that runs the CEBAF accelerator in daily operation

  13. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    OpenAIRE

    Oliver W. Layton; Ennio eMingolla; Arash eYazdanbakhsh

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedba...

  14. Survey on multisensory feedback virtual reality dental training systems.

    Science.gov (United States)

    Wang, D; Li, T; Zhang, Y; Hou, J

    2016-11-01

    Compared with traditional dental training methods, virtual reality training systems integrated with multisensory feedback possess potentials advantages. However, there exist many technical challenges in developing a satisfactory simulator. In this manuscript, we systematically survey several current dental training systems to identify the gaps between the capabilities of these systems and the clinical training requirements. After briefly summarising the components, functions and unique features of each system, we discuss the technical challenges behind these systems including the software, hardware and user evaluation methods. Finally, the clinical requirements of an ideal dental training system are proposed. Future research/development areas are identified based on an analysis of the gaps between current systems and clinical training requirements. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. Age differences in neural correlates of feedback processing after economic decisions under risk.

    Science.gov (United States)

    Fernandes, Carina; Pasion, Rita; Gonçalves, Ana R; Ferreira-Santos, Fernando; Barbosa, Fernando; Martins, Isabel P; Marques-Teixeira, João

    2018-05-01

    This study examines age-related differences in behavioral responses to risk and in the neurophysiological correlates of feedback processing. Our sample was composed of younger, middle-aged, and older adults, who were asked to decide between 2 risky options, in the gain and loss domains, during an EEG recording. Results evidenced group-related differences in early and later stages of feedback processing, indexed by differences in the feedback-related negativity (FRN) and P3 amplitudes. Specifically, in the loss domain, younger adults showed higher FRN amplitudes after non-losses than after losses, whereas middle-aged and older adults had similar FRN amplitudes after both. In the gain domain, younger and middle-aged adults had higher P3 amplitudes after gains than after non-gains, whereas older adults had similar P3 amplitudes after both. Behaviorally, older adults had higher rates of risky decisions than younger adults in the loss domain, a result that was correlated with poorer performance in memory and executive functions. Our results suggest age-related differences in the outcome-related expectations, as well as in the affective relevance attributed to the outcomes, which may underlie the group differences found in risk-aversion. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Distinct Feedforward and Feedback Effects of Microstimulation in Visual Cortex Reveal Neural Mechanisms of Texture Segregation.

    Science.gov (United States)

    Klink, P Christiaan; Dagnino, Bruno; Gariel-Mathis, Marie-Alice; Roelfsema, Pieter R

    2017-07-05

    The visual cortex is hierarchically organized, with low-level areas coding for simple features and higher areas for complex ones. Feedforward and feedback connections propagate information between areas in opposite directions, but their functional roles are only partially understood. We used electrical microstimulation to perturb the propagation of neuronal activity between areas V1 and V4 in monkeys performing a texture-segregation task. In both areas, microstimulation locally caused a brief phase of excitation, followed by inhibition. Both these effects propagated faithfully in the feedforward direction from V1 to V4. Stimulation of V4, however, caused little V1 excitation, but it did yield a delayed suppression during the late phase of visually driven activity. This suppression was pronounced for the V1 figure representation and weaker for background representations. Our results reveal functional differences between feedforward and feedback processing in texture segregation and suggest a specific modulating role for feedback connections in perceptual organization. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Development of bunch by bunch transverse feedback system at Hefei light source

    International Nuclear Information System (INIS)

    Wang Junhua; Zheng Kai; Li Weimin; Yang Yongliang; Huang Longjun; Chen Yuanbo; Zhou Zeran; Wang Lin; Liu Zeping; Sun Baogen; Ma Li; Cao Jianshe; Yue Junhui; Liu Dekang; Ye Kairong

    2008-01-01

    This paper has introduced the development of the transverse bunch-by-bunch measurement and feedback system, including the experiment of damping the coupled bunch instability. Some key technologies on the system have been introduced: the vector calculation module as a signal processing module used to adjust the phase of the feedback signals, the feedback kicker cavity and the notch filter used to filter the DC component and revolution frequencies component in a signal and save the feedback power. The result of the feedback experiment is mentioned: the instability oscillation was damped when the feedback system was on. (authors)

  18. Studies on leptin and its feedback system for weight regulation

    International Nuclear Information System (INIS)

    Lei Chengzhi

    2002-01-01

    Recently the hormone leptin has been regarded as hormonal signal linking adipose tissue status with a number of key central nervous system circuits. The role of leptin and its feedback system in man is partly revealed. Hypothalamic centers appear to control appetite, metabolic rate and activity level in a co-ordinate manner. Within the hypothalamus, known weight regulatory molecules include leptin, neuropeptide Y and POMC. The authors integrated new information into a revised model for understanding this important regulatory process. The model of energy homeostasis propose that the interaction of leptin with various neuroendocrine pathway in the brain and in the periphery to affect food-take

  19. Real-time control systems: feedback, scheduling and robustness

    Science.gov (United States)

    Simon, Daniel; Seuret, Alexandre; Sename, Olivier

    2017-08-01

    The efficient control of real-time distributed systems, where continuous components are governed through digital devices and communication networks, needs a careful examination of the constraints arising from the different involved domains inside co-design approaches. Thanks to the robustness of feedback control, both new control methodologies and slackened real-time scheduling schemes are proposed beyond the frontiers between these traditionally separated fields. A methodology to design robust aperiodic controllers is provided, where the sampling interval is considered as a control variable of the system. Promising experimental results are provided to show the feasibility and robustness of the approach.

  20. State-PID Feedback for Pole Placement of LTI Systems

    Directory of Open Access Journals (Sweden)

    Sarawut Sujitjorn

    2011-01-01

    Full Text Available Pole placement problems are especially important for disturbance rejection and stabilization of dynamical systems and regarded as algebraic inverse eigenvalue problems. In this paper, we propose gain formulae of state feedback through PID-elements to achieve desired pole placement for a delay-free LTI system with single input. Real and complex stable poles can be assigned with the proposed compact gain formulae. Numerical examples show that our proposed gain formulae can be used effectively resulting in very satisfactory responses.

  1. Theory of Neural Information Processing Systems

    International Nuclear Information System (INIS)

    Galla, Tobias

    2006-01-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 10 11 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kuehn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  2. Feedback Linearization Controller for a Wind Energy Power System

    Directory of Open Access Journals (Sweden)

    Muthana Alrifai

    2016-09-01

    Full Text Available This paper deals with the control of a doubly-fed induction generator (DFIG-based variable speed wind turbine power system. A system of eight ordinary differential equations is used to model the wind energy conversion system. The generator has a wound rotor type with back-to-back three-phase power converter bridges between its rotor and the grid; it is modeled using the direct-quadrature rotating reference frame with aligned stator flux. An input-state feedback linearization controller is proposed for the wind energy power system. The controller guarantees that the states of the system track the desired states. Simulation results are presented to validate the proposed control scheme. Moreover, further simulation results are shown to investigate the robustness of the proposed control scheme to changes in some of the parameters of the system.

  3. Practical Loop-Shaping Design of Feedback Control Systems

    Science.gov (United States)

    Kopasakis, George

    2010-01-01

    An improved methodology for designing feedback control systems has been developed based on systematically shaping the loop gain of the system to meet performance requirements such as stability margins, disturbance attenuation, and transient response, while taking into account the actuation system limitations such as actuation rates and range. Loop-shaping for controls design is not new, but past techniques do not directly address how to systematically design the controller to maximize its performance. As a result, classical feedback control systems are designed predominantly using ad hoc control design approaches such as proportional integral derivative (PID), normally satisfied when a workable solution is achieved, without a good understanding of how to maximize the effectiveness of the control design in terms of competing performance requirements, in relation to the limitations of the plant design. The conception of this improved methodology was motivated by challenges in designing control systems of the types needed for supersonic propulsion. But the methodology is generally applicable to any classical control-system design where the transfer function of the plant is known or can be evaluated. In the case of a supersonic aerospace vehicle, a major challenge is to design the system to attenuate anticipated external and internal disturbances, using such actuators as fuel injectors and valves, bypass doors, and ramps, all of which are subject to limitations in actuator response, rates, and ranges. Also, for supersonic vehicles, with long slim type of structures, coupling between the engine and the structural dynamics can produce undesirable effects that could adversely affect vehicle stability and ride quality. In order to design distributed controls that can suppress these potential adverse effects, within the full capabilities of the actuation system, it is important to employ a systematic control design methodology such as this that can maximize the

  4. Effect of vibrotactile feedback on an EMG-based proportional cursor control system.

    Science.gov (United States)

    Li, Shunchong; Chen, Xingyu; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

    2013-01-01

    Surface electromyography (sEMG) has been introduced into the bio-mechatronics systems, however, most of them are lack of the sensory feedback. In this paper, the effect of vibrotactile feedback for a myoelectric cursor control system is investigated quantitatively. Simultaneous and proportional control signals are extracted from EMG using a muscle synergy model. Different types of feedback including vibrotactile feedback and visual feedback are added, assessed and compared with each other. The results show that vibrotactile feedback is capable of improving the performance of EMG-based human machine interface.

  5. Neural Network for Optimization of Existing Control Systems

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1995-01-01

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

  6. Designing a stable feedback control system for blind image deconvolution.

    Science.gov (United States)

    Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan

    2018-05-01

    Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Passivation and control of partially known SISO nonlinear systems via dynamic neural networks

    Directory of Open Access Journals (Sweden)

    Reyes-Reyes J.

    2000-01-01

    Full Text Available In this paper, an adaptive technique is suggested to provide the passivity property for a class of partially known SISO nonlinear systems. A simple Dynamic Neural Network (DNN, containing only two neurons and without any hidden-layers, is used to identify the unknown nonlinear system. By means of a Lyapunov-like analysis the new learning law for this DNN, guarantying both successful identification and passivation effects, is derived. Based on this adaptive DNN model, an adaptive feedback controller, serving for wide class of nonlinear systems with an a priori incomplete model description, is designed. Two typical examples illustrate the effectiveness of the suggested approach.

  8. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

    Directory of Open Access Journals (Sweden)

    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

  9. Feedback error learning controller for functional electrical stimulation assistance in a hybrid robotic system for reaching rehabilitation

    Directory of Open Access Journals (Sweden)

    Francisco Resquín

    2016-07-01

    Full Text Available Hybrid robotic systems represent a novel research field, where functional electrical stimulation (FES is combined with a robotic device for rehabilitation of motor impairment. Under this approach, the design of robust FES controllers still remains an open challenge. In this work, we aimed at developing a learning FES controller to assist in the performance of reaching movements in a simple hybrid robotic system setting. We implemented a Feedback Error Learning (FEL control strategy consisting of a feedback PID controller and a feedforward controller based on a neural network. A passive exoskeleton complemented the FES controller by compensating the effects of gravity. We carried out experiments with healthy subjects to validate the performance of the system. Results show that the FEL control strategy is able to adjust the FES intensity to track the desired trajectory accurately without the need of a previous mathematical model.

  10. Feedback stabilization system for pulsed single longitudinal mode tunable lasers

    Science.gov (United States)

    Esherick, Peter; Raymond, Thomas D.

    1991-10-01

    A feedback stabilization system for pulse single longitudinal mode tunable lasers having an excited laser medium contained within an adjustable length cavity and producing a laser beam through the use of an internal dispersive element, including detection of angular deviation in the output laser beam resulting from detuning between the cavity mode frequency and the passband of the internal dispersive element, and generating an error signal based thereon. The error signal can be integrated and amplified and then applied as a correcting signal to a piezoelectric transducer mounted on a mirror of the laser cavity for controlling the cavity length.

  11. Laser experimental system as teaching aid for demonstrating basic phenomena of laser feedback

    International Nuclear Information System (INIS)

    Xu, Ling; Zhao, Shijie; Zhang, Shulian

    2015-01-01

    An experimental laser teaching system is developed to demonstrate laser feedback phenomena, which bring great harm to optical communication and benefits to precision measurement. The system consists of an orthogonally polarized He-Ne laser, a feedback mirror which reflects the laser output light into the laser cavity, and an optical attenuator which changes the intensity of the feedback light. As the feedback mirror is driven by a piezoelectric ceramic, the attenuator is adjusted and the feedback mirror is tilted, the system can demonstrate many basic laser feedback phenomena, including weak, moderate and strong optical feedback, multiple feedback and polarization flipping. Demonstrations of these phenomena can give students a better understanding about the intensity and polarization of lasers. The system is well designed and assembled, simple to operate, and provides a valuable teaching aid at an undergraduate level. (paper)

  12. Simulation of the ALS longitudinal multibunch feedback system

    International Nuclear Information System (INIS)

    Byrd, J.

    1993-05-01

    Longitudinal coupled bunch growth rates in the Advanced Light Source (ALS), a 1.5 GeV electron storage ring for producing synchrotron radiation, indicate the need for damping via a feedback (FB) system. The design of the system is based on the proposed PEP-II longitudinal FB system which uses a digital filter to provide the required phase and amplitude response. We report the results of a detailed computer simulation of the FB system including single particle longitudinal beam dynamics, measured RF cavity fundamental and higher order modes, and response of major FB components such as the power amplifier and kicker. The simulation addresses issues such as required FB power and gain, noise, digital filter effects, and varying initial bunch conditions

  13. State-feedback control of fuzzy discrete-event systems.

    Science.gov (United States)

    Lin, Feng; Ying, Hao

    2010-06-01

    In a 2002 paper, we combined fuzzy logic with discrete-event systems (DESs) and established an automaton model of fuzzy DESs (FDESs). The model can effectively represent deterministic uncertainties and vagueness, as well as human subjective observation and judgment inherent to many real-world problems, particularly those in biomedicine. We also investigated optimal control of FDESs and applied the results to optimize HIV/AIDS treatments for individual patients. Since then, other researchers have investigated supervisory control problems in FDESs, and several results have been obtained. These results are mostly derived by extending the traditional supervisory control of (crisp) DESs, which are string based. In this paper, we develop state-feedback control of FDESs that is different from the supervisory control extensions. We use state space to describe the system behaviors and use state feedback in control. Both disablement and enforcement are allowed. Furthermore, we study controllability based on the state space and prove that a controller exists if and only if the controlled system behavior is (state-based) controllable. We discuss various properties of the state-based controllability. Aside from novelty, the proposed new framework has the advantages of being able to address a wide range of practical problems that cannot be effectively dealt with by existing approaches. We use the diabetes treatment as an example to illustrate some key aspects of our theoretical results.

  14. NNETS - NEURAL NETWORK ENVIRONMENT ON A TRANSPUTER SYSTEM

    Science.gov (United States)

    Villarreal, J.

    1994-01-01

    The primary purpose of NNETS (Neural Network Environment on a Transputer System) is to provide users a high degree of flexibility in creating and manipulating a wide variety of neural network topologies at processing speeds not found in conventional computing environments. To accomplish this purpose, NNETS supports back propagation and back propagation related algorithms. The back propagation algorithm used is an implementation of Rumelhart's Generalized Delta Rule. NNETS was developed on the INMOS Transputer. NNETS predefines a Back Propagation Network, a Jordan Network, and a Reinforcement Network to assist users in learning and defining their own networks. The program also allows users to configure other neural network paradigms from the NNETS basic architecture. The Jordan network is basically a feed forward network that has the outputs connected to a pseudo input layer. The state of the network is dependent on the inputs from the environment plus the state of the network. The Reinforcement network learns via a scalar feedback signal called reinforcement. The network propagates forward randomly. The environment looks at the outputs of the network to produce a reinforcement signal that is fed back to the network. NNETS was written for the INMOS C compiler D711B version 1.3 or later (MS-DOS version). A small portion of the software was written in the OCCAM language to perform the communications routing between processors. NNETS is configured to operate on a 4 X 10 array of Transputers in sequence with a Transputer based graphics processor controlled by a master IBM PC 286 (or better) Transputer. A RGB monitor is required which must be capable of 512 X 512 resolution. It must be able to receive red, green, and blue signals via BNC connectors. NNETS is meant for experienced Transputer users only. The program is distributed on 5.25 inch 1.2Mb MS-DOS format diskettes. NNETS was developed in 1991. Transputer and OCCAM are registered trademarks of Inmos Corporation. MS

  15. Education for Managing Digital Transformation: A Feedback Systems Approach

    Directory of Open Access Journals (Sweden)

    Michael Von Kutzschenbach

    2017-04-01

    Full Text Available "Digital transformation" is becoming the newest mantra of business leaders. It is clear that there are tremendous business opportunities resulting from this revolution, but there is also a price to be paid. Most management literature focuses on the benefits of digitalization, reflecting the desire to increase performance and efficiency in selected business activities. However, digital transformations may lead to the disruption of established ways of doing the work of the firm, stakeholder power may be fundamentally changed, and there is the potential for redefining the nature of the firm itself. Consequently, the decision to "go digital" requires managers to develop perspectives that have the requisite variety to cope with these challenges. Feedback systems thinking is a powerful means for managers to develop and communicate business models that include those aspects of digitalization that affects their firm's theory of success. The Uber case illustrates the principles of applying feedback systems thinking to the radical changes that it has presented the public transportation sector. This paper analyzes Uber's platform business by presenting an endogenous explanation of the drivers and eventual constraints to growth of the theory of success upon which the firm is based. This type of analysis has implications for all firms considering implementing a significant digital transformation process.

  16. The ctenophore genome and the evolutionary origins of neural systems

    NARCIS (Netherlands)

    Moroz, Leonid L.; Kocot, Kevin M.; Citarella, Mathew R.; Dosung, Sohn; Norekian, Tigran P.; Povolotskaya, Inna S.; Grigorenko, Anastasia P.; Dailey, Christopher; Berezikov, Eugene; Buckley, Katherine M.; Ptitsyn, Andrey; Reshetov, Denis; Mukherjee, Krishanu; Moroz, Tatiana P.; Bobkova, Yelena; Yu, Fahong; Kapitonov, Vladimir V.; Jurka, Jerzy; Bobkov, Yuri V.; Swore, Joshua J.; Girardo, David O.; Fodor, Alexander; Gusev, Fedor; Sanford, Rachel; Bruders, Rebecca; Kittler, Ellen; Mills, Claudia E.; Rast, Jonathan P.; Derelle, Romain; Solovyev, Victor V.; Kondrashov, Fyodor A.; Swalla, Billie J.; Sweedler, Jonathan V.; Rogaev, Evgeny I.; Halanych, Kenneth M.; Kohn, Andrea B.

    2014-01-01

    The origins of neural systems remain unresolved. In contrast to other basal metazoans, ctenophores (comb jellies) have both complex nervous and mesoderm-derived muscular systems. These holoplanktonic predators also have sophisticated ciliated locomotion, behaviour and distinct development. Here we

  17. Optimization of workflow scheduling in Utility Management System with hierarchical neural network

    Directory of Open Access Journals (Sweden)

    Srdjan Vukmirovic

    2011-08-01

    Full Text Available Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very high resource requirements. This paper proposes architecture for a new scheduling mechanism that dynamically executes a scheduling algorithm using feedback about the current status Grid nodes. Two Artificial Neural Networks were created in order to solve the scheduling problem. A case study is created for the Meter Data Management system with measurements from the Smart Metering system for the city of Novi Sad, Serbia. Performance tests show that significant improvement of overall execution time can be achieved by Hierarchical Artificial Neural Networks.

  18. CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks

    DEFF Research Database (Denmark)

    Palm, Rasmus Berg; Winther, Ole; Laws, Florian

    2017-01-01

    We present CloudScan; an invoice analysis system that requires zero configuration or upfront annotation. In contrast to previous work, CloudScan does not rely on templates of invoice layout, instead it learns a single global model of invoices that naturally generalizes to unseen invoice layouts....... The model is trained using data automatically extracted from end-user provided feedback. This automatic training data extraction removes the requirement for users to annotate the data precisely. We describe a recurrent neural network model that can capture long range context and compare it to a baseline...... logistic regression model corresponding to the current CloudScan production system. We train and evaluate the system on 8 important fields using a dataset of 326,471 invoices. The recurrent neural network and baseline model achieve 0.891 and 0.887 average F1 scores respectively on seen invoice layouts...

  19. Spiking Neural P Systems with Communication on Request.

    Science.gov (United States)

    Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

    2017-12-01

    Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

  20. Improving the security of optoelectronic delayed feedback system by parameter modulation and system coupling

    Science.gov (United States)

    Liu, Lingfeng; Miao, Suoxia; Cheng, Mengfan; Gao, Xiaojing

    2016-02-01

    A coupled system with varying parameters is proposed to improve the security of optoelectronic delayed feedback system. This system is coupled by two parameter-varied optoelectronic delayed feedback systems with chaotic modulation. Dynamics performance results show that this system has a higher complexity compared to the original one. Furthermore, this system can conceal the time delay effectively against the autocorrelation function and delayed mutual information method and can increase the dimension space of secure parameters to resist brute-force attack by introducing the digital chaotic systems.

  1. Design of EAST LHCD high power supply feedback control system based on PLC

    International Nuclear Information System (INIS)

    Hu Huaichuan; Shan Jiafang

    2009-01-01

    Design of EAST LHCD -35kV/5.6MW high power supply feedback control system based on PLC is described. Industrial computer and PLC are used to control high power supply in the system. PID arithmetic is adopted to achieve the feedback control of voltage of high power supply. Operating system is base on real-time operating system of QNX. Good controlling properties and reliable protective properties of the feedback control system are proved by the experiment results. (authors)

  2. Dynamics and control of a financial system with time-delayed feedbacks

    International Nuclear Information System (INIS)

    Chen, W.-C.

    2008-01-01

    Complex behaviors in a financial system with time-delayed feedbacks are discussed in this study via numerical modeling. The system shows complex dynamics such as periodic, quasi-periodic, and chaotic behaviors. Both period doubling and inverse period doubling routes were found in this system. This paper also shows that the attractor merging crisis is a fundamental feature of nonlinear financial systems with time-delayed feedbacks. Control of the deterministic chaos in the financial system can be realized using Pyragas feedbacks

  3. Bifurcation and chaos in neural excitable system

    International Nuclear Information System (INIS)

    Jing Zhujun; Yang Jianping; Feng Wei

    2006-01-01

    In this paper, we investigate the dynamical behaviors of neural excitable system without periodic external current (proposed by Chialvo [Generic excitable dynamics on a two-dimensional map. Chaos, Solitons and Fractals 1995;5(3-4):461-79] and with periodic external current as system's parameters vary. The existence and stability of three fixed points, bifurcation of fixed points, the conditions of existences of fold bifurcation, flip bifurcation and Hopf bifurcation are derived by using bifurcation theory and center manifold theorem. The chaotic existence in the sense of Marotto's definition of chaos is proved. We then give the numerical simulated results (using bifurcation diagrams, computations of Maximum Lyapunov exponent and phase portraits), which not only show the consistence with the analytic results but also display new and interesting dynamical behaviors, including the complete period-doubling and inverse period-doubling bifurcation, symmetry period-doubling bifurcations of period-3 orbit, simultaneous occurrence of two different routes (invariant cycle and period-doubling bifurcations) to chaos for a given bifurcation parameter, sudden disappearance of chaos at one critical point, a great abundance of period windows (period 2 to 10, 12, 19, 20 orbits, and so on) in transient chaotic regions with interior crises, strange chaotic attractors and strange non-chaotic attractor. In particular, the parameter k plays a important role in the system, which can leave the chaotic behavior or the quasi-periodic behavior to period-1 orbit as k varies, and it can be considered as an control strategy of chaos by adjusting the parameter k. Combining the existing results in [Generic excitable dynamics on a two-dimensional map. Chaos, Solitons and Fractals 1995;5(3-4):461-79] with the new results reported in this paper, a more complete description of the system is now obtained

  4. Jump resonant frequency islands in nonlinear feedback control systems

    Science.gov (United States)

    Koenigsberg, W. D.; Dunn, J. C.

    1975-01-01

    A new type of jump resonance is predicted and observed in certain nonlinear feedback control systems. The new jump resonance characteristic is described as a 'frequency island' due to the fact that a portion of the input-output transfer characteristic is disjoint from the main body. The presence of such frequency islands was predicted by using a sinusoidal describing function characterization of the dynamics of an inertial gyro employing nonlinear ternary rebalance logic. While the general conditions under which such islands are possible has not been examined, a numerical approach is presented which can aid in establishing their presence. The existence of the frequency islands predicted for the ternary rebalanced gyro was confirmed by simulating the nonlinear system and measuring the transfer function.

  5. Dynamic Intelligent Feedback Scheduling in Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Hui-ying Chen

    2013-01-01

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

  6. Laser Soldering of Rat Skin Using a Controlled Feedback System

    Directory of Open Access Journals (Sweden)

    Mohammad Sadegh Nourbakhsh

    2009-03-01

    Full Text Available Introduction: Laser tissue soldering using albumin and indocyanine green dye (ICG is an effective technique utilized in various surgical procedures. The purpose of this study was to perform laser soldering of rat skin under a feedback control system and compare the results with those obtained using standard sutures. Material and Methods: Skin incisions were made over eight rats’ dorsa, which were subsequently closed using different wound closure interventions in two groups: (a using a temperature controlled infrared detector or (b by suture. Tensile strengths were measured at 2, 5, 7 and 10 days post-incision. Histological examination was performed at the time of sacrifice. Results: Tensile strength results showed that during the initial days following the incisions, the tensile strengths of the sutured samples were greater than the laser samples. However, 10 days after the incisions, the tensile strengths of the laser soldered incisions were higher than the sutured cuts. Histopathological examination showed a preferred wound healing response in the soldered skin compared with the control samples. The healing indices of the laser soldered repairs (426 were significantly better than the control samples (340.5. Conclusion: Tissue feedback control of temperature and optical changes in laser soldering of skin leads to a higher tensile strength and better histological results and hence this method may be considered as an alternative to standard suturing.

  7. Integration of a force feedback joystick with a VR system

    Energy Technology Data Exchange (ETDEWEB)

    Castro, A C [ENEA, Centro Ricerche Casaccia, S. Maria di Galeria, RM (Italy). Dipt. Innovazione

    1999-07-01

    The report shows the result carried out at the Robotics and Information Systems Division of ENEA (National Agency for New Technology, Energy and the Environment) in the Casaccia Centre (Rome). The study presents an approach to the problem of integrating force feedback with a complete real-time virtual environment system: in particular bulky computations for graphics or simulation require a decoupling of the haptic servo loop from the main application loop if high-quality forces are to be obtained. The control system has been developed for the force-feedback joystick Impulse 2000, from Immersion Co., and the integration of it to a virtual environment is presented here. Technical issues related to the development of control architectures for Internet-based exchange of haptic information, in a stable way are discussed. [Italian] Il presente rapporto descrive il lavoro eseguito nella divisione robotica e informatica del dipartimento innovazione dell'ENEA del centro ricerche della Casaccia (Roma): il sistema di controllo del dispositivo con ritorno di forza in un sistema RV (real-time virtual environment system) ed illustra l'approccio a questa problematica ed in particolare la lentezza di esecuzione del ciclo di calcoli per la resa delle immagini da parte del sistema grafico e del ciclio per la simulazione della dinamica di sistema. Viene descritto il sistema di controllo per il joystick con ritorno di forza Impulse 2000 (Immersion Co.) e la sua integrazione ad un ambiente virtuale. Sono inoltre discusse le problematiche connesse allo sviluppo di sistemi che consentano lo scambio dell'informazione tattile attraverso Internet.

  8. Integration of a force feedback joystick with a VR system

    Energy Technology Data Exchange (ETDEWEB)

    Castro, A.C. [ENEA, Centro Ricerche Casaccia, S. Maria di Galeria, RM (Italy). Dipt. Innovazione

    1999-07-01

    The report shows the result carried out at the Robotics and Information Systems Division of ENEA (National Agency for New Technology, Energy and the Environment) in the Casaccia Centre (Rome). The study presents an approach to the problem of integrating force feedback with a complete real-time virtual environment system: in particular bulky computations for graphics or simulation require a decoupling of the haptic servo loop from the main application loop if high-quality forces are to be obtained. The control system has been developed for the force-feedback joystick Impulse 2000, from Immersion Co., and the integration of it to a virtual environment is presented here. Technical issues related to the development of control architectures for Internet-based exchange of haptic information, in a stable way are discussed. [Italian] Il presente rapporto descrive il lavoro eseguito nella divisione robotica e informatica del dipartimento innovazione dell'ENEA del centro ricerche della Casaccia (Roma): il sistema di controllo del dispositivo con ritorno di forza in un sistema RV (real-time virtual environment system) ed illustra l'approccio a questa problematica ed in particolare la lentezza di esecuzione del ciclo di calcoli per la resa delle immagini da parte del sistema grafico e del ciclio per la simulazione della dinamica di sistema. Viene descritto il sistema di controllo per il joystick con ritorno di forza Impulse 2000 (Immersion Co.) e la sua integrazione ad un ambiente virtuale. Sono inoltre discusse le problematiche connesse allo sviluppo di sistemi che consentano lo scambio dell'informazione tattile attraverso Internet.

  9. Design and Implementation of Output Feedback Control for Piezo Actuated Structure Using Embedded System

    Directory of Open Access Journals (Sweden)

    R.Maheswari

    2008-06-01

    Full Text Available This paper presents the design of periodic output feedback control using state feedback gain to control the vibration of piezo actuated cantilever beam. The effectiveness of the controller is evaluated through simulation and experimentally by exciting the structure at resonance. Real time implementation of the controller is done using microcontroller. The closed loop eigen values of the system with periodic output feedback and state feedback are identical.

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

    Science.gov (United States)

    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.

  11. Short-term synaptic plasticity and heterogeneity in neural systems

    Science.gov (United States)

    Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

    2013-01-01

    We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

  12. Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

    Directory of Open Access Journals (Sweden)

    Wang Chao

    2016-03-01

    Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

  13. Neural correlates of experienced moral emotion: an fMRI investigation of emotion in response to prejudice feedback.

    Science.gov (United States)

    Fourie, Melike M; Thomas, Kevin G F; Amodio, David M; Warton, Christopher M R; Meintjes, Ernesta M

    2014-01-01

    Guilt, shame, and embarrassment are quintessential moral emotions with important regulatory functions for the individual and society. Moral emotions are, however, difficult to study with neuroimaging methods because their elicitation is more intricate than that of basic emotions. Here, using functional MRI (fMRI), we employed a novel social prejudice paradigm to examine specific brain regions associated with real-time moral emotion, focusing on guilt and related moral-negative emotions. The paradigm induced intense moral-negative emotion (primarily guilt) in 22 low-prejudice individuals through preprogrammed feedback indicating implicit prejudice against Black and disabled people. fMRI data indicated that this experience of moral-negative emotion was associated with increased activity in anterior paralimbic structures, including the anterior cingulate cortex (ACC) and anterior insula, in addition to areas associated with mentalizing, including the dorsomedial prefrontal cortex, posterior cingulate cortex, and precuneus. Of significance was prominent conflict-related activity in the supragenual ACC, which is consistent with theories proposing an association between acute guilt and behavioral inhibition. Finally, a significant negative association between self-reported guilt and neural activity in the pregenual ACC suggested a role of self-regulatory processes in response to moral-negative affect. These findings are consistent with the multifaceted self-regulatory functions of moral-negative emotions in social behavior.

  14. Construction of experience feedback system for equipment supervision in nuclear engineering

    International Nuclear Information System (INIS)

    Zou Pingguo; Zhang Liying; Zhang Wenzhong

    2009-01-01

    Based on the analysis of the experience sources on equipment supervision in nuclear engineering, the details of the organization principle, working flow, and report requirement for the experience feedback system are introduced. The function range and its roll in the experience feedback system of the nuclear authority, nuclear power plant owners and equipment supervision organizations are illustrated. The standardization working requirements in the information gathering, analyzing, feedback and tracking process, and the characteristics and form of the incident report and feedback report are proposed. It emphasizes that the method for combined analysis of one significant incident and the whole incidents shall be adopted in the information analysis, and the experience feedback shall be considered in the development of equipment supervision technique and the equipment manufacturing, thus to maximize the use of experience feedback information to improve the pertinency and effectiveness of the experience feedback system. (authors)

  15. Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia.

    Directory of Open Access Journals (Sweden)

    Atsuhito Toyomaki

    Full Text Available Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia.

  16. Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia.

    Science.gov (United States)

    Toyomaki, Atsuhito; Hashimoto, Naoki; Kako, Yuki; Murohashi, Harumitsu; Kusumi, Ichiro

    2017-01-01

    Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia.

  17. Attention to Color Sharpens Neural Population Tuning via Feedback Processing in the Human Visual Cortex Hierarchy.

    Science.gov (United States)

    Bartsch, Mandy V; Loewe, Kristian; Merkel, Christian; Heinze, Hans-Jochen; Schoenfeld, Mircea A; Tsotsos, John K; Hopf, Jens-Max

    2017-10-25

    Attention can facilitate the selection of elementary object features such as color, orientation, or motion. This is referred to as feature-based attention and it is commonly attributed to a modulation of the gain and tuning of feature-selective units in visual cortex. Although gain mechanisms are well characterized, little is known about the cortical processes underlying the sharpening of feature selectivity. Here, we show with high-resolution magnetoencephalography in human observers (men and women) that sharpened selectivity for a particular color arises from feedback processing in the human visual cortex hierarchy. To assess color selectivity, we analyze the response to a color probe that varies in color distance from an attended color target. We find that attention causes an initial gain enhancement in anterior ventral extrastriate cortex that is coarsely selective for the target color and transitions within ∼100 ms into a sharper tuned profile in more posterior ventral occipital cortex. We conclude that attention sharpens selectivity over time by attenuating the response at lower levels of the cortical hierarchy to color values neighboring the target in color space. These observations support computational models proposing that attention tunes feature selectivity in visual cortex through backward-propagating attenuation of units less tuned to the target. SIGNIFICANCE STATEMENT Whether searching for your car, a particular item of clothing, or just obeying traffic lights, in everyday life, we must select items based on color. But how does attention allow us to select a specific color? Here, we use high spatiotemporal resolution neuromagnetic recordings to examine how color selectivity emerges in the human brain. We find that color selectivity evolves as a coarse to fine process from higher to lower levels within the visual cortex hierarchy. Our observations support computational models proposing that feature selectivity increases over time by attenuating the

  18. PWR system simulation and parameter estimation with neural networks

    International Nuclear Information System (INIS)

    Akkurt, Hatice; Colak, Uener

    2002-01-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

  19. PWR system simulation and parameter estimation with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

    2002-11-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

  20. Afferent Neural Feedback Overrides the Modulating Effects of Arousal, Hypercapnia and Hypoxemia on Neonatal Cardio-respiratory Control.

    Science.gov (United States)

    Lumb, Kathleen J; Schneider, Jennifer M; Ibrahim, Thowfique; Rigaux, Anita; Hasan, Shabih U

    2018-04-20

    Evidence at whole animal, organ-system, and cellular and molecular levels suggests that afferent volume feedback is critical for establishment of adequate ventilation at birth. Due to the irreversible nature of vagal ablation studies to date, it was difficult to quantify the roles of afferent volume input, arousal and changes in blood gas tensions on neonatal respiratory control. During reversible perineural vagal block, profound apneas, and hypoxemia and hypercarbia were observed necessitating termination of perineural blockade. Respiratory depression and apneas were independent of the sleep states. We demonstrate that profound apneas and life-threatening respiratory failure in vagally denervated animals do not result from lack of arousal or hypoxemia. Change in sleep state and concomitant respiratory depression result from lack of afferent volume feedback, which appears to be critical for the maintenance of normal breathing patterns and adequate gas exchange during the early postnatal period. Afferent volume feedback plays a vital role in neonatal respiratory control. Mechanisms for the profound respiratory depression and life-threatening apneas observed in vagally denervated neonatal animals remain unclear. We investigated the roles of sleep states, hypoxic-hypercapnia and afferent volume feedback on respiratory depression using reversible perineural vagal block during early postnatal period. Seven lambs were instrumented during the first 48h of life to record/analyze sleep states, diaphragmatic electromyograph, arterial blood gas tensions, systemic arterial blood pressure and rectal temperature. Perineural cuffs were placed around the vagi to attain reversible blockade. Post-operatively, during the awake state, both vagi were blocked using 2% xylocaine for up to 30 minutes. Compared with baseline values, pHa, PaO 2 and SaO 2 decreased and PaCO 2 increased during perineural blockade (P Respiratory depression and apneas were independent of sleep states. This

  1. Iterative Feedback Tuning in district heating systems; Iterative Feedback Tuning i vaermeproduktionsanlaeggningar

    Energy Technology Data Exchange (ETDEWEB)

    Raaberg, Martin; Velut, Stephane; Bari, Siavosh Amanat

    2010-10-15

    The project goal is to evaluate and describe how Iterative Feedback Tuning (IFT) can be used to tune controllers in the typical control loops in heat- and power plants. There are only a few practical studies carried out for IFT and they are not really relevant for power and heat processes. It is the practical problems in implementing the IFT and the result of trimming that is the focus of this project. The project will start with theoretical studies of the IFT-method, then realization and simple simulations in scilab. The IFT equations are then implemented in Freelance 2000, an ABB control system, for practical tests on a SISO- and a MIMO-process. By performing reproducible experiments on the process and analyze the results IFT can adjust the controller parameters to minimize a cost function that represents the control goal. The project selected for SISO experiments a pressure controller in an oil transportation system. By controlling the valve position of a control valve for the reversal to the supply tank, the pressure in the oil transport system is regulated. A disturbance in oil pressure can be achieved by changing the position of a valve that lets oil through to the day tank. The selected MIMO-process is a pre-heater in a degassing process. In this process, a valve on the secondary side is utilized to control the flow in the secondary system. A valve on the primary side is utilized to control the district heating water flow through the heat exchanger to control the temperature on the secondary side. An increased secondary flow increases the heat demand and thus requiring an increase in primary flow to maintain the secondary side outlet temperature. This is the cross-coupling responsible for why it is an advantage to consider the process as multi-variable. Using the IFT method, the two original PID-controllers and a feed-forward controller is tuned simultaneously. IFT-method was difficult to implement but worked well in both simulations and in real processes

  2. Dopamine system: Manager of neural pathways

    Directory of Open Access Journals (Sweden)

    Simon eHong

    2013-12-01

    Full Text Available There are a growing number of roles that midbrain dopamine (DA neurons assume, such as, reward, aversion, alerting and vigor. Here I propose a theory that may be able to explain why the suggested functions of DA came about. It has been suggested that largely parallel cortico-basal ganglia-thalamo-cortico loops exist to control different aspects of behavior. I propose that (1 the midbrain DA system is organized in a similar manner, with different groups of DA neurons corresponding to these parallel neural pathways (NPs. The DA system can be viewed as the manager of these parallel NPs in that it recruits and activates only the task-relevant NPs when they are needed. It is likely that the functions of those NPs that have been consistently activated by the corresponding DA groups are facilitated. I also propose that (2 there are two levels of DA roles: the How and What roles. The How role is encoded in tonic and phasic DA neuron firing patterns and gives a directive to its target NP: how vigorously its function needs to be carried out. The tonic DA firing is to maintain a certain level of DA in the target NPs to support their expected behavioral and mental functions; it is only when a sudden unexpected boost or suppression of activity is required by the relevant target NP that DA neurons in the corresponding NP act in a phasic manner. The What role is the implementational aspect of the role of DA in the target NP, such as binding to D1 receptors to boost working memory. This What aspect of DA explains why DA seems to assume different functions depending on the region of the brain in which it is involved. In terms of the role of the lateral habenula (LHb, the LHb is expected to suppress maladaptive behaviors and mental processes by controlling the DA system. The demand-based smart management by the DA system may have given animals an edge in evolution with adaptive behaviors and a better survival rate in resource-scarce situations.

  3. The super collider transverse feedback system for suppression of the emittance growth and beam instabilities

    International Nuclear Information System (INIS)

    Lebedev, V.A.

    1993-01-01

    A super collider transverse feedback system designed to suppress injection errors, emittance growth due to external noises, and beam instabilities is considered. It is supposed that the feedback system should consist of two circuits: an injection damper operating just after injection and a super damper. To damp the emittance growth, the superdamper has to operate with the ultimate decrement close to the revolution frequency. The physics of such a feedback system and its main limitations are discussed. 9 refs.; 21 figs.; 1 tab

  4. Diagnostic Neural Network Systems for the Electronic Circuits

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

    Neural Networks is one of the most important artificial intelligent approaches for solving the diagnostic processes. This research concerns with uses the neural networks for diagnosis of the electronic circuits. Modern electronic systems contain both the analog and digital circuits. But, diagnosis of the analog circuits suffers from great complexity due to their nonlinearity. To overcome this problem, the proposed system introduces a diagnostic system that uses the neural network to diagnose both the digital and analog circuits. So, it can face the new requirements for the modern electronic systems. A fault dictionary method was implemented in the system. Experimental results are presented on three electronic systems. They are: artificial kidney, wireless network and personal computer systems. The proposed system has improved the performance of the diagnostic systems when applied for these practical cases

  5. Vein matching using artificial neural network in vein authentication systems

    Science.gov (United States)

    Noori Hoshyar, Azadeh; Sulaiman, Riza

    2011-10-01

    Personal identification technology as security systems is developing rapidly. Traditional authentication modes like key; password; card are not safe enough because they could be stolen or easily forgotten. Biometric as developed technology has been applied to a wide range of systems. According to different researchers, vein biometric is a good candidate among other biometric traits such as fingerprint, hand geometry, voice, DNA and etc for authentication systems. Vein authentication systems can be designed by different methodologies. All the methodologies consist of matching stage which is too important for final verification of the system. Neural Network is an effective methodology for matching and recognizing individuals in authentication systems. Therefore, this paper explains and implements the Neural Network methodology for finger vein authentication system. Neural Network is trained in Matlab to match the vein features of authentication system. The Network simulation shows the quality of matching as 95% which is a good performance for authentication system matching.

  6. Feedback Networks

    OpenAIRE

    Zamir, Amir R.; Wu, Te-Lin; Sun, Lin; Shen, William; Malik, Jitendra; Savarese, Silvio

    2016-01-01

    Currently, the most successful learning models in computer vision are based on learning successive representations followed by a decision layer. This is usually actualized through feedforward multilayer neural networks, e.g. ConvNets, where each layer forms one of such successive representations. However, an alternative that can achieve the same goal is a feedback based approach in which the representation is formed in an iterative manner based on a feedback received from previous iteration's...

  7. MDOT Pavement Management System : Prediction Models and Feedback System

    Science.gov (United States)

    2000-10-01

    As a primary component of a Pavement Management System (PMS), prediction models are crucial for one or more of the following analyses: : maintenance planning, budgeting, life-cycle analysis, multi-year optimization of maintenance works program, and a...

  8. A beam position feedback system for beam lines at the photon factory

    International Nuclear Information System (INIS)

    Katsura, T.; Kamiya, Y.; Haga, K.; Mitsuhashi, T.

    1987-01-01

    The beam position of the synchrotron radiation produced from the Storage Ring was stabilized by a twofold position feedback system. A digital feedback system was developed to suppress the diurnal beam movement (one cycle of sin-like drifting motion per day) which became a serious problem in low-emittance operation. The feedback was applied to the closed-orbit-distortion (COD) correction system in order to cancel the position variation at all the beam lines proportionately to the variation monitored at one beam line. An analog feedback system is also used to suppress frequency components faster than the slow diurnal movement

  9. Global Stability in Dynamical Systems with Multiple Feedback Mechanisms

    DEFF Research Database (Denmark)

    Andersen, Morten; Vinther, Frank; Ottesen, Johnny T.

    2016-01-01

    A class of n-dimensional ODEs with up to n feedbacks from the n’th variable is analysed. The feedbacks are represented by non-specific, bounded, non-negative C1 functions. The main result is the formulation and proof of an easily applicable criterion for existence of a globally stable fixed point...

  10. Biological and geophysical feedbacks with fire in the Earth system

    Science.gov (United States)

    Archibald, S.; Lehmann, C. E. R.; Belcher, C. M.; Bond, W. J.; Bradstock, R. A.; Daniau, A.-L.; Dexter, K. G.; Forrestel, E. J.; Greve, M.; He, T.; Higgins, S. I.; Hoffmann, W. A.; Lamont, B. B.; McGlinn, D. J.; Moncrieff, G. R.; Osborne, C. P.; Pausas, J. G.; Price, O.; Ripley, B. S.; Rogers, B. M.; Schwilk, D. W.; Simon, M. F.; Turetsky, M. R.; Van der Werf, G. R.; Zanne, A. E.

    2018-03-01

    Roughly 3% of the Earth’s land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels—namely plants and their litter—that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

  11. Using the Context of User Feedback in Recommender Systems

    Directory of Open Access Journals (Sweden)

    Ladislav Peska

    2016-12-01

    Full Text Available Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context may be of high importance. In this paper, we present a model of relevant contextual features affecting user feedback, propose methods leveraging those features, publish a dataset of real e-commerce users containing multiple user feedback indicators as well as its context and finally present results of purchase prediction and recommendation experiments. Off-line experiments with real users of a Czech travel agency website corroborated the importance of leveraging presentation context in both purchase prediction and recommendation tasks.

  12. Use of neural networks in the analysis of complex systems

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms) to some of the problems of complex engineering systems has the potential to enhance the safety reliability and operability of these systems. The work described here deals with complex systems or parts of such systems that can be isolated from the total system. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network. The neural networks are usually simulated on modern high-speed computers that carry out the calculations serially. However, it is possible to implement neural networks using specially designed microchips where the network calculations are truly carried out in parallel, thereby providing virtually instantaneous outputs for each set of inputs. Specific applications described include: Diagnostics: State of the Plant; Hybrid System for Transient Identification; Detection of Change of Mode in Complex Systems; Sensor Validation; Plant-Wide Monitoring; Monitoring of Performance and Efficiency; and Analysis of Vibrations. Although the specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  13. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  14. Bio-inspired spiking neural network for nonlinear systems control.

    Science.gov (United States)

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

    2018-08-01

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

  15. Design of the ILC Prototype FONT4 Digital Intra-Train Beam-Based Feedback System

    International Nuclear Information System (INIS)

    Burrows, P.; Queen Mary, U. of London; Christian, G.B.; Hartin, A.F.; Dabiri Khah, H.; White, G.R.; Oxford U.; Clarke, C.C.; Perry, C.; Oxford Instruments; Kalinin, A.; Daresbury; McCormick, D.J.; Molloy, S.; Ross, M.C.; SLAC

    2007-01-01

    We present the design of the FONT4 digital intra-train beam position feedback system prototype and preliminary results of initial beam tests at the Accelerator Test Facility (ATF) at KEK. The feedback system incorporates a fast analogue beam position monitor (BPM) front-end signal processor, a digital feedback board, and a kicker driver amplifier. The short bunchtrain, comprising 3 electron bunches separated by c. 150ns, in the ATF extraction line was used to test components of the prototype feedback system

  16. MATHEMATICAL MODEL OF AUTOMATED REHABILITATION SYSTEM WITH BIOLOGICAL FEEDBACK FOR REHABILITATION AND DEVELOPMENT OF MUSCULOSKELETAL SYSTEM

    Directory of Open Access Journals (Sweden)

    Kirill A. Kalyashin

    2013-01-01

    Full Text Available In order to increase the efficiency and safety of rehabilitation of musculoskeletal system, the model and the algorithm for patient interaction with automated rehabilitation system with biological feedback was developed, based on registration and management of the second functional parameter, which prevents risks of overwork while intensive exercises.

  17. Identification and prediction of dynamic systems using an interactively recurrent self-evolving fuzzy neural network.

    Science.gov (United States)

    Lin, Yang-Yin; Chang, Jyh-Yeong; Lin, Chin-Teng

    2013-02-01

    This paper presents a novel recurrent fuzzy neural network, called an interactively recurrent self-evolving fuzzy neural network (IRSFNN), for prediction and identification of dynamic systems. The recurrent structure in an IRSFNN is formed as an external loops and internal feedback by feeding the rule firing strength of each rule to others rules and itself. The consequent part in the IRSFNN is composed of a Takagi-Sugeno-Kang (TSK) or functional-link-based type. The proposed IRSFNN employs a functional link neural network (FLNN) to the consequent part of fuzzy rules for promoting the mapping ability. Unlike a TSK-type fuzzy neural network, the FLNN in the consequent part is a nonlinear function of input variables. An IRSFNNs learning starts with an empty rule base and all of the rules are generated and learned online through a simultaneous structure and parameter learning. An on-line clustering algorithm is effective in generating fuzzy rules. The consequent update parameters are derived by a variable-dimensional Kalman filter algorithm. The premise and recurrent parameters are learned through a gradient descent algorithm. We test the IRSFNN for the prediction and identification of dynamic plants and compare it to other well-known recurrent FNNs. The proposed model obtains enhanced performance results.

  18. FY1995 study of feedback type gait training system; 1995 nendo feedback gata hoko kuren sochi ni kansuru kenkyu kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    The purpose of this project is to develop and demonstrate the utility of feedback type gait training equipment designed for the measurement and evaluation by a walking training of the aged or patient. As similar concepts of walking training, a locomotion in the water for the aged is applied in rehabilitation. Our development of this study established the system of a suspending mechanism which revolves around the prop, and a walking on the circular type force plate by the aged or patient. It is possible to detect a walking reaction force of several patients from force plate simultaneously. And then, the data from force plate makes feedback signal to put up the patient like a buoyancy in the water. Concerning the evaluations of walking pattern a step range, a hanging ratio and a walking speed, etc. are acquired for each patient by the acknowledgment base. This system is actively able to perform a walking training continuously compared with conventional passive gait equipment. (NEDO)

  19. Anomaly detection in an automated safeguards system using neural networks

    International Nuclear Information System (INIS)

    Whiteson, R.; Howell, J.A.

    1992-01-01

    An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

  20. Will they like me? Neural and behavioral responses to social-evaluative peer feedback in socially and non-socially anxious females.

    Science.gov (United States)

    van der Molen, Melle J W; Harrewijn, Anita; Westenberg, P Michiel

    2018-03-07

    The current study examined neural and behavioral responses to social-evaluative feedback processing in social anxiety. Twenty-two non-socially and 17 socially anxious females (mean age = 19.57 years) participated in a Social Judgment Paradigm in which they received peer acceptance/rejection feedback that was either congruent or incongruent with their prior predictions. Results indicated that socially anxious participants believed they would receive less social acceptance feedback than non-socially anxious participants. EEG results demonstrated that unexpected social rejection feedback elicited a significant increase in theta (4-8 Hz) power relative to other feedback conditions. This theta response was only observed in non-socially anxious individuals. Together, results corroborate cognitive-behavioral studies demonstrating a negative expectancy bias in socially anxiety with respect to social evaluation. Furthermore, the present findings highlight a functional role for theta oscillatory dynamics in processing cues that convey social-evaluative threat, and this social threat-monitoring mechanism seems less sensitive in socially anxious females. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Adaptive neural networks control for camera stabilization with active suspension system

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-08-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to unintentional vibrations caused by road roughness. This article presents an adaptive neural network approach mixed with linear quadratic regulator control for a quarter-car active suspension system to stabilize the image captured area of the camera. An active suspension system provides extra force through the actuator which allows it to suppress vertical vibration of sprung mass. First, to deal with the road disturbance and the system uncertainties, radial basis function neural network is proposed to construct the map between the state error and the compensation component, which can correct the optimal state-feedback control law. The weights matrix of radial basis function neural network is adaptively tuned online. Then, the closed-loop stability and asymptotic convergence performance is guaranteed by Lyapunov analysis. Finally, the simulation results demonstrate that the proposed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  2. Atmosphere-ocean feedbacks in a coastal upwelling system

    Science.gov (United States)

    Alves, J. M. R.; Peliz, A.; Caldeira, R. M. A.; Miranda, P. M. A.

    2018-03-01

    The COAWST (Coupled Ocean-Atmosphere-Wave-Sediment Transport) modelling system is used in different configurations to simulate the Iberian upwelling during the 2012 summer, aiming to assess the atmosphere-ocean feedbacks in the upwelling dynamics. When model results are compared with satellite measurements and in-situ data, two-way coupling is found to have a moderate impact in data-model statistics. A significant reinforcement of atmosphere-ocean coupling coefficients is, however, observed in the two-way coupled run, and in the WRF and ROMS runs forced by previously simulated SST and wind fields, respectively. The increasing in the coupling coefficient is associated with slight, but potentially important changes in the low-level coastal jet in the atmospheric marine boundary layer. While these results do not imply the need for fully coupled simulations in many applications, they show that in seasonal numerical studies such simulations do not degrade the overall model performance, and contribute to produce better dynamical fields.

  3. Beam monitors and transverse feedback system of TRISTAN Main Ring

    International Nuclear Information System (INIS)

    Ieiri, T.; Ishii, H.; Kishiro, J.; Mizumachi, Y.; Mori, K.; Nakajima, K.; Ogata, A.; Shintake, T.; Tejima, M.

    1987-01-01

    The construction of 30 GeV TRISTAN Main Ring (MR) started in 1983 soon after the commissioning of 8 GeV Accumulation Ring (AR). The authors prepared 392 position monitors, 6 synchrotron radiation monitors, 9 screen monitors, 2 DCCT's, 3 scrapers, 12 bunch monitors, transverse feedback systems for two beams and DC separators. Since the required monitoring devices of AR and MR are almost the same, the experiences in AR were very useful in the design of MR monitors. However, machine parameters of two rings are very different and the authors had to review the performance of each item. From the monitor point of view the most important is the difference of revolution frequency; 794.6 kHz for AR and 99.33 kHz for MR. This means that average beam current of MR is 1/8 as small as AR current with the same bunch number and intensity. Therefore, the sensitivity of each monitor must be better in MR. The second difference is that MR should be used as a collider from the beginning. Therefore they must prepare for multi-beam and multi-bunch operation

  4. Robust MPC with Output Feedback of Integrating Systems

    Directory of Open Access Journals (Sweden)

    J. M. Perez

    2012-01-01

    Full Text Available In this work, it is presented a new contribution to the design of a robust MPC with output feedback, input constraints, and uncertain model. Multivariable predictive controllers have been used in industry to reduce the variability of the process output and to allow the operation of the system near to the constraints, where it is usually located the optimum operating point. For this reason, new controllers have been developed with the objective of achieving better performance, simpler control structure, and robustness with respect to model uncertainty. In this work, it is proposed a model predictive controller based on a nonminimal state space model where the state is perfectly known. It is an infinite prediction horizon controller, and it is assumed that there is uncertainty in the stable part of the model, which may also include integrating modes that are frequently present in the process plants. The method is illustrated with a simulation example of the process industry using linear models based on a real process.

  5. Representation of neural networks as Lotka-Volterra systems

    International Nuclear Information System (INIS)

    Moreau, Yves; Vandewalle, Joos; Louies, Stephane; Brenig, Leon

    1999-01-01

    We study changes of coordinates that allow the representation of the ordinary differential equations describing continuous-time recurrent neural networks into differential equations describing predator-prey models--also called Lotka-Volterra systems. We transform the equations for the neural network first into quasi-monomial form, where we express the vector field of the dynamical system as a linear combination of products of powers of the variables. In practice, this transformation is possible only if the activation function is the hyperbolic tangent or the logistic sigmoied. From this quasi-monomial form, we can directly transform the system further into Lotka-Volterra equations. The resulting Lotka-Volterra system is of higher dimension than the original system, but the behavior of its first variables is equivalent to the behavior of the original neural network

  6. Uplink Contention-based CSI Feedback with Prioritized Layers for a Multi-Carrier System

    DEFF Research Database (Denmark)

    Kaneko, Megumi; Hayashi, Kazunori; Popovski, Petar

    2012-01-01

    , several works have considered contention-based CSI feedback in the UL control channel. We propose such a feedback scheme for a generic MC system, based on the idea of variable collision protection, where the probability that a feedback information experiences a collision depends on its importance......Optimized resource allocation of the Downlink (DL) in wireless systems utilizing Multi-Carrier (MC) transmission requires Channel State Information (CSI) feedback for each user/subchannel to the Base Station (BS), consuming a high amount of Uplink (UL) radio resources. To alleviate this problem...

  7. Global output feedback stabilisation of stochastic high-order feedforward nonlinear systems with time-delay

    Science.gov (United States)

    Zhang, Kemei; Zhao, Cong-Ran; Xie, Xue-Jun

    2015-12-01

    This paper considers the problem of output feedback stabilisation for stochastic high-order feedforward nonlinear systems with time-varying delay. By using the homogeneous domination theory and solving several troublesome obstacles in the design and analysis, an output feedback controller is constructed to drive the closed-loop system globally asymptotically stable in probability.

  8. Design and evaluation of a Flight Envelope Protection haptic feedback system

    NARCIS (Netherlands)

    Ellerbroek, J.; Rodriguez Martin, M.J.M.; Lombaerts, T; van Paassen, M.M.; Mulder, M.

    2016-01-01

    This paper describes the design and evaluation of a shared control, haptic feedback system to communicate Flight Envelope Protection System intent. The concept uses a combination of stiffness feedback and vibration to communicate proximity of the aircraft state to flight envelope boundaries. In

  9. A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

    Science.gov (United States)

    Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

    2016-01-01

    In this research, we propose a Social Learning Management System (SLMS) enabling real-time and reliable feedback for incorrect answers by learners using a social network service (SNS). The proposed system increases the accuracy of learners' assessment results by using a confidence scale and a variety of social feedback that is created and shared…

  10. Systematic design and simulation of a tearing mode suppression feedback control system for the TEXTOR tokamak

    NARCIS (Netherlands)

    Hennen, B.A.; Westerhof, E.; Nuij, Pwjm; M.R. de Baar,; Steinbuch, M.

    2012-01-01

    Suppression of tearing modes is essential for the operation of tokamaks. This paper describes the design and simulation of a tearing mode suppression feedback control system for the TEXTOR tokamak. The two main control tasks of this feedback control system are the radial alignment of electron

  11. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

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

  12. Neural network training by Kalman filtering in process system monitoring

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-03-01

    Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

  13. Thermal photovoltaic solar integrated system analysis using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

  14. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

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

  15. High speed digital interfacing for a neural data acquisition system

    Directory of Open Access Journals (Sweden)

    Bahr Andreas

    2016-09-01

    Full Text Available Diseases like schizophrenia and genetic epilepsy are supposed to be caused by disorders in the early development of the brain. For the further investigation of these relationships a custom designed application specific integrated circuit (ASIC was developed that is optimized for the recording from neonatal mice [Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. 16 Channel Neural Recording Integrated Circuit with SPI Interface and Error Correction Coding. Proc. 9th BIOSTEC 2016. Biodevices: Rome, Italy, 2016; 1: 263; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. Development of a neural recording mixed signal integrated circuit for biomedical signal acquisition. Biomed Eng Biomed Tech Abstracts 2015; 60(S1: 298–299; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider WH. 16 Channel Neural Recording Mixed Signal ASIC. CDNLive EMEA 2015 Conference Proceedings, 2015.]. To enable the live display of the neural signals a multichannel neural data acquisition system with live display functionality is presented. It implements a high speed data transmission from the ASIC to a computer with a live display functionality. The system has been successfully implemented and was used in a neural recording of a head-fixed mouse.

  16. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  17. Microfluidic systems for stem cell-based neural tissue engineering.

    Science.gov (United States)

    Karimi, Mahdi; Bahrami, Sajad; Mirshekari, Hamed; Basri, Seyed Masoud Moosavi; Nik, Amirala Bakhshian; Aref, Amir R; Akbari, Mohsen; Hamblin, Michael R

    2016-07-05

    Neural tissue engineering aims at developing novel approaches for the treatment of diseases of the nervous system, by providing a permissive environment for the growth and differentiation of neural cells. Three-dimensional (3D) cell culture systems provide a closer biomimetic environment, and promote better cell differentiation and improved cell function, than could be achieved by conventional two-dimensional (2D) culture systems. With the recent advances in the discovery and introduction of different types of stem cells for tissue engineering, microfluidic platforms have provided an improved microenvironment for the 3D-culture of stem cells. Microfluidic systems can provide more precise control over the spatiotemporal distribution of chemical and physical cues at the cellular level compared to traditional systems. Various microsystems have been designed and fabricated for the purpose of neural tissue engineering. Enhanced neural migration and differentiation, and monitoring of these processes, as well as understanding the behavior of stem cells and their microenvironment have been obtained through application of different microfluidic-based stem cell culture and tissue engineering techniques. As the technology advances it may be possible to construct a "brain-on-a-chip". In this review, we describe the basics of stem cells and tissue engineering as well as microfluidics-based tissue engineering approaches. We review recent testing of various microfluidic approaches for stem cell-based neural tissue engineering.

  18. The effects of driver identity on driving safety in a retrospective feedback system.

    Science.gov (United States)

    Zhao, Guozhen; Wu, Changxu

    2012-03-01

    Retrospective feedback that provides detailed information on a driver's performance in critical driving situations at the end of a trip enhances his/her driving behaviors and safe driving habits. Although this has been demonstrated by a previous study, retrospective feedback can be further improved and applied to non-critical driving situations, which is needed for transportation safety. To propose a new retrospective feedback system that uses driver identity (i.e., a driver's name) and to experimentally study its effects on measures of driving performance and safety in a driving simulator. We conducted a behavioral experimental study with 30 participants. "Feedback type" was a between-subject variable with three conditions: no feedback (control group), feedback without driver identity, and feedback with driver identity. We measured multiple aspects of participants' driving behavior. To control for potential confounds, factors that were significantly correlated with driving behavior (e.g., age and driving experience) were all entered as covariates into a multivariate analysis of variance. To examine the effects of speeding on collision severity in driving simulation studies, we also developed a new index - momentum of potential collision - with a set of equations. Subjects who used a feedback system with driver identity had the fewest speeding violations and central-line crossings, spent the least amount of time speeding and crossing the central line, had the lowest speeding and central-line crossing magnitude, ran the fewest red lights, and had the smallest momentum of potential collision compared to the groups with feedback without driver identity and without feedback (control group). The new retrospective feedback system with driver identity has the potential to enhance a person's driving safety (e.g., speeding, central-line crossing, momentum of potential collision), which is an indication of the valence of one's name in a feedback system design. Copyright

  19. On a new time-delayed feedback control of chaotic systems

    International Nuclear Information System (INIS)

    Tian Lixin; Xu Jun; Sun Mei; Li Xiuming

    2009-01-01

    In this paper, using the idea of the successive dislocation feedback method, a new time-delayed feedback control method called the successive dislocation time-delayed feedback control (SDTDFC) is designed. Firstly, the idea of SDTDFC is introduced. Then some analytic sufficient conditions of the chaos control from the SDTDFC approach are derived for stabilization. Finally, some established results are further clarified via a case study of the Lorenz system with the numerical simulations.

  20. Switched-Observer-Based Adaptive Neural Control of MIMO Switched Nonlinear Systems With Unknown Control Gains.

    Science.gov (United States)

    Long, Lijun; Zhao, Jun

    2017-07-01

    In this paper, the problem of adaptive neural output-feedback control is addressed for a class of multi-input multioutput (MIMO) switched uncertain nonlinear systems with unknown control gains. Neural networks (NNs) are used to approximate unknown nonlinear functions. In order to avoid the conservativeness caused by adoption of a common observer for all subsystems, an MIMO NN switched observer is designed to estimate unmeasurable states. A new switched observer-based adaptive neural control technique for the problem studied is then provided by exploiting the classical average dwell time (ADT) method and the backstepping method and the Nussbaum gain technique. It effectively handles the obstacle about the coexistence of multiple Nussbaum-type function terms, and improves the classical ADT method, since the exponential decline property of Lyapunov functions for individual subsystems is no longer satisfied. It is shown that the technique proposed is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop system under a class of switching signals with ADT, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the approach proposed is illustrated by its application to a two inverted pendulum system.

  1. Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system.

    Science.gov (United States)

    Blana, Dimitra; Kirsch, Robert F; Chadwick, Edward K

    2009-05-01

    A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4 degrees in ideal conditions, and less than 10 degrees even in the case of considerable fatigue and external disturbances.

  2. Distributed User Selection in Network MIMO Systems with Limited Feedback

    KAUST Repository

    Elkhalil, Khalil; Eltayeb, Mohammed E.; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.

    2015-01-01

    We propose a distributed user selection strategy in a network MIMO setting with M base stations serving K users. Each base station is equipped with L antennas, where LM ≪ K. The conventional selection strategy is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Such technique, however, requires perfect channel state information at the transmitter (CSIT), which might not be available or need large feedback overhead. This paper proposes an alternative distributed user selection technique where each user sets a timer that is inversely proportional to his channel quality indicator (CQI), as a means to reduce the feedback overhead. The proposed strategy allows only the user with the highest CQI to respond with a feedback. Such technique, however, remains collision free only if the transmission time is shorter than the difference between the strongest user timer and the second strongest user timer. To overcome the situation of longer transmission times, the paper proposes another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and all users encode their feedback information and send it back to the base-stations simultaneously. The paper shows that the problem can be formulated as a block sparse recovery problem which is agnostic on the transmission time, which makes it a good alternative to the timer approach when collision is dominant.

  3. Distributed User Selection in Network MIMO Systems with Limited Feedback

    KAUST Repository

    Elkhalil, Khalil

    2015-09-06

    We propose a distributed user selection strategy in a network MIMO setting with M base stations serving K users. Each base station is equipped with L antennas, where LM ≪ K. The conventional selection strategy is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Such technique, however, requires perfect channel state information at the transmitter (CSIT), which might not be available or need large feedback overhead. This paper proposes an alternative distributed user selection technique where each user sets a timer that is inversely proportional to his channel quality indicator (CQI), as a means to reduce the feedback overhead. The proposed strategy allows only the user with the highest CQI to respond with a feedback. Such technique, however, remains collision free only if the transmission time is shorter than the difference between the strongest user timer and the second strongest user timer. To overcome the situation of longer transmission times, the paper proposes another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and all users encode their feedback information and send it back to the base-stations simultaneously. The paper shows that the problem can be formulated as a block sparse recovery problem which is agnostic on the transmission time, which makes it a good alternative to the timer approach when collision is dominant.

  4. Operation and performance of a longitudinal feedback system using digital signal processing

    International Nuclear Information System (INIS)

    Teytelman, D.; Fox, J.; Hindi, H.

    1994-01-01

    A programmable longitudinal feedback system using a parallel array of AT ampersand T 1610 digital signal processors has been developed as a component of the PEP-II R ampersand D program. This system has been installed at the Advanced Light Source (LBL) and implements full speed bunch by bunch signal processing for storage rings with bunch spacing of 4ns. Open and closed loop results showing the action of the feedback system are presented, and the system is shown to damp coupled-bunch instabilities in the ALS. A unified PC-based software environment for the feedback system operation is also described

  5. Web/smart phone based control and feedback systems for irrigation systems

    Science.gov (United States)

    The role of the internet and mobile devices in the control and feedback of irrigation systems is reviewed. This role is placed in the larger context of four distinct components required for irrigation management, including 1. the control panel; 2. remote control; 3. soil, plant, and weather (SPW) se...

  6. Recurrent fuzzy neural network backstepping control for the prescribed output tracking performance of nonlinear dynamic systems.

    Science.gov (United States)

    Han, Seong-Ik; Lee, Jang-Myung

    2014-01-01

    This paper proposes a backstepping control system that uses a tracking error constraint and recurrent fuzzy neural networks (RFNNs) to achieve a prescribed tracking performance for a strict-feedback nonlinear dynamic system. A new constraint variable was defined to generate the virtual control that forces the tracking error to fall within prescribed boundaries. An adaptive RFNN was also used to obtain the required improvement on the approximation performances in order to avoid calculating the explosive number of terms generated by the recursive steps of traditional backstepping control. The boundedness and convergence of the closed-loop system was confirmed based on the Lyapunov stability theory. The prescribed performance of the proposed control scheme was validated by using it to control the prescribed error of a nonlinear system and a robot manipulator. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator

    Science.gov (United States)

    González Ochoa, Héctor O.; Perales, Gualberto Solís; Epstein, Irving R.; Femat, Ricardo

    2018-05-01

    We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.

  8. Effects of realistic force feedback in a robotic assisted minimally invasive surgery system.

    Science.gov (United States)

    Moradi Dalvand, Mohsen; Shirinzadeh, Bijan; Nahavandi, Saeid; Smith, Julian

    2014-06-01

    Robotic assisted minimally invasive surgery systems not only have the advantages of traditional laparoscopic procedures but also restore the surgeon's hand-eye coordination and improve the surgeon's precision by filtering hand tremors. Unfortunately, these benefits have come at the expense of the surgeon's ability to feel. Several research efforts have already attempted to restore this feature and study the effects of force feedback in robotic systems. The proposed methods and studies have some shortcomings. The main focus of this research is to overcome some of these limitations and to study the effects of force feedback in palpation in a more realistic fashion. A parallel robot assisted minimally invasive surgery system (PRAMiSS) with force feedback capabilities was employed to study the effects of realistic force feedback in palpation of artificial tissue samples. PRAMiSS is capable of actually measuring the tip/tissue interaction forces directly from the surgery site. Four sets of experiments using only vision feedback, only force feedback, simultaneous force and vision feedback and direct manipulation were conducted to evaluate the role of sensory feedback from sideways tip/tissue interaction forces with a scale factor of 100% in characterising tissues of varying stiffness. Twenty human subjects were involved in the experiments for at least 1440 trials. Friedman and Wilcoxon signed-rank tests were employed to statistically analyse the experimental results. Providing realistic force feedback in robotic assisted surgery systems improves the quality of tissue characterization procedures. Force feedback capability also increases the certainty of characterizing soft tissues compared with direct palpation using the lateral sides of index fingers. The force feedback capability can improve the quality of palpation and characterization of soft tissues of varying stiffness by restoring sense of touch in robotic assisted minimally invasive surgery operations.

  9. Adaptive Synchronization of Memristor-based Chaotic Neural Systems

    Directory of Open Access Journals (Sweden)

    Xiaofang Hu

    2014-11-01

    Full Text Available Chaotic neural networks consisting of a great number of chaotic neurons are able to reproduce the rich dynamics observed in biological nervous systems. In recent years, the memristor has attracted much interest in the efficient implementation of artificial synapses and neurons. This work addresses adaptive synchronization of a class of memristor-based neural chaotic systems using a novel adaptive backstepping approach. A systematic design procedure is presented. Simulation results have demonstrated the effectiveness of the proposed adaptive synchronization method and its potential in practical application of memristive chaotic oscillators in secure communication.

  10. Increasing Personal Value Congruence in Computerized Decision Support Using System Feedback

    Directory of Open Access Journals (Sweden)

    Bryan Hosack

    2014-02-01

    Full Text Available The Theory of Universals in Values (TUV, a reliable and validated conceptualization of personal values used in psychology, is used to examine the effect of system feedback delivered by a Decision Support System (DSS on personal values. The results indicate that value-based decision-making behavior can be influenced by DSS feedback to address value congruence in decision-making. User behavior was shown to follow the outcomes expected by operant theory when feedback was supportive and to follow the outcomes of reactance theory when feedback was challenging. This result suggests that practitioners and Information System (IS researchers should consider user values when designing computerized decision feedback to adjust a system’s design such that the potential user backlash is avoided or congruence between organizational and personal values is achieved.

  11. Synchronization control of cross-strict feedback hyperchaotic system based on cross active backstepping design

    International Nuclear Information System (INIS)

    Wang Jing; Gao Jinfeng; Ma Xikui

    2007-01-01

    This Letter presents a novel cross active backstepping design method for synchronization control of cross-strict feedback hyperchaotic system, in which the ordinary backstepping design is unavailable. The proposed control method, combining backstepping design and active control approach, extends the application of backstepping technique in chaos control. Based on this method, different combinations of controllers can be designed to meet the needs of different applications. The proposed method is applied to achieve chaos synchronization of two identical cross-strict feedback hyperchaotic systems. Also it is used to implement synchronization between cross-strict feedback hyperchaotic system and Roessler hyperchaotic system. Numerical examples illustrate the validity of the control method

  12. The Potential of User Feedback Through the Iterative Refining of Queries in an Image Retrieval System

    NARCIS (Netherlands)

    Ben Moussa, Maher; Pasch, Marco; Hiemstra, Djoerd; van der Vet, P.E.; Huibers, Theo W.C.; Marchand-Maillet, Stephane; Bruno, Eric; Nürnberger, Andreas; Detyniecki, Marcin

    2007-01-01

    Inaccurate or ambiguous expressions in queries lead to poor results in information retrieval. We assume that iterative user feedback can improve the quality of queries. To this end we developed a system for image retrieval that utilizes user feedback to refine the user’s search query. This is done

  13. Effects of error feedback on a nonlinear bistable system with stochastic resonance

    International Nuclear Information System (INIS)

    Li Jian-Long; Zhou Hui

    2012-01-01

    In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing

  14. Expectations and feedback in user-system communication

    NARCIS (Netherlands)

    Engel, F.L.; Haakma, R.

    1993-01-01

    In terms of speed and accuracy of intention transfer, normal human conversation proves to be very efficient: exchanged messages carry only sufficient information relative to contextual knowledge assumed to be present at the receiver's end. Furthermore, by receiving layered feedback from the

  15. Affective feedback in a tutoring system for procedural tasks

    NARCIS (Netherlands)

    Heylen, Dirk K.J.; André, E.; Vissers, M.; Dybkjaer, L.; Minker, W.; op den Akker, Hendrikus J.A.; Heisterkamp, P.; Nijholt, Antinus

    2004-01-01

    We discuss the affective aspects of tutoring dialogues in an ITS -called INES- that helps students to practice nursing tasks using a haptic device and a virtual environment. Special attention is paid to affective control in the tutoring process by means of selecting the appropriate feedback, taking

  16. Thoracic ROM measurement system with visual bio-feedback: system design and biofeedback evaluation.

    Science.gov (United States)

    Ando, Takeshi; Kawamura, Kazuya; Fujitani, Junko; Koike, Tomokazu; Fujimoto, Masashi; Fujie, Masakatsu G

    2011-01-01

    Patients with diseases such as chronic obstructive pulmonary disease (COPD) need to improve their thorax mobility. Thoracic ROM is one of the simplest and most useful indexes to evaluate the respiratory function. In this paper, we have proposed the prototype of a simple thoracic ROM measurement system with real-time visual bio-feedback in the chest expansion test. In this system, the thoracic ROM is measured using a wire-type linear encoder whose wire is wrapped around the thorax. In this paper, firstly, the repeatability and reliability of measured thoracic ROM was confirmed as a first report of the developed prototype. Secondly, we analyzed the effect of the bio-feedback system on the respiratory function. The result of the experiment showed that it was easier to maintain a large and stable thoracic ROM during deep breathing by using the real-time visual biofeedback system of the thoracic ROM.

  17. Integrated evolutionary computation neural network quality controller for automated systems

    Energy Technology Data Exchange (ETDEWEB)

    Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

    1999-06-01

    With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

  18. Optical neural network system for pose determination of spinning satellites

    Science.gov (United States)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  19. Effect of biased feedback on motor imagery learning in BCI-teleoperation system

    Directory of Open Access Journals (Sweden)

    Maryam eAlimardani

    2014-04-01

    Full Text Available Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users’ BC performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects’ performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects’ BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects’ online performance, evaluation of brain activity patterns revealed that subjects’ self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects’ motor imagery skills.

  20. Real time global orbit feedback system for NSLS x-ray ring

    International Nuclear Information System (INIS)

    Yu, L.H.; Biscardi, R.; Bittner, J.; Fauchet, A.M.; Krinsky, F.S.; Nawrocky, R.J.; Rothman, J.; Singh, O.V.; Yang, K.M.

    1991-01-01

    We report on the design and commissioning of a real time harmonic global orbit feedback system for the NSLS X-ray ring. This system uses 8 pick-up electrode position monitors and 16 trim dipole magnets to eliminate 3 harmonic components of the orbit fluctuations. Because of the larger number of position monitors and trim magnets, the X-ray ring feedback system differs from the previously reported VUV ring system in that the Fourier analysis and harmonic generation networks are comprised of MDAC boards controlled by computer. The implementation of the global feedback system has resulted in a dramatic improvement of orbit stability, by more than a factor of five everywhere. Simultaneous operation of the global and several local bump feedback systems has been achieved. 4 refs., 5 figs

  1. ℋ∞ constant gain state feedback stabilization of stochastic hybrid systems with Wiener process

    Directory of Open Access Journals (Sweden)

    E. K. Boukas

    2004-01-01

    Full Text Available This paper considers the stabilization problem of the class of continuous-time linear stochastic hybrid systems with Wiener process. The ℋ∞ state feedback stabilization problem is treated. A state feedback controller with constant gain that does not require access to the system mode is designed. LMI-based conditions are developed to design the state feedback controller with constant gain that stochastically stabilizes the studied class of systems and, at the same time, achieve the disturbance rejection of a desired level. The minimum disturbance rejection is also determined. Numerical examples are given to show the usefulness of the proposed results.

  2. Feedback control and adaptive control of the energy resource chaotic system

    International Nuclear Information System (INIS)

    Sun Mei; Tian Lixin; Jiang Shumin; Xu Jun

    2007-01-01

    In this paper, the problem of control for the energy resource chaotic system is considered. Two different method of control, feedback control (include linear feedback control, non-autonomous feedback control) and adaptive control methods are used to suppress chaos to unstable equilibrium or unstable periodic orbits. The Routh-Hurwitz criteria and Lyapunov direct method are used to study the conditions of the asymptotic stability of the steady states of the controlled system. The designed adaptive controller is robust with respect to certain class of disturbances in the energy resource chaotic system. Numerical simulations are presented to show these results

  3. Phase and amplitude feedback control system for the Los Alamos free-electron laser

    International Nuclear Information System (INIS)

    Lynch, M.T.; Tallerico, P.J.; Higgins, E.F.

    1985-01-01

    Phase and amplitude feedback control systems for the Los Alamos free-electron laser (FEL) are described. Beam-driven voltages are very high in the buncher cavity because the electron gun is pulsed at the fifth subharmonic of the buncher resonant frequency. The high beam loading necessitated a novel feedback and drive configuration for the buncher. A compensation cirucit has been added to the gun/driver system to reduce observed drift. Extremely small variations in the accelerator gradients had dramatic effects on the laser output power. These problems and how they were solved are described and plans for improvements in the feedback control system are discussed. 5 refs., 7 figs

  4. The neural system of metacognition accompanying decision-making in the prefrontal cortex

    Science.gov (United States)

    Qiu, Lirong; Su, Jie; Ni, Yinmei; Bai, Yang; Zhang, Xuesong; Li, Xiaoli

    2018-01-01

    Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel “decision–redecision” paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities—commonly occurring in both tasks—indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes—positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable. PMID:29684004

  5. The FONT5 Bunch-by-Bunch Position and Angle Feedback System at ATF2

    Science.gov (United States)

    Apsimon, R. J.; Bett, D. R.; Burrows, P. N.; Christian, G. B.; Constance, B.; Davis, M. R.; Gerbershagen, A.; Perry, C.; Resta-Lopez, J.

    The FONT5 upstream beam-based feedback system at ATF2 is designed to correct the position and angle jitter at the entrance to the ATF2 final-focus system, and also to demonstrate a prototype intra-train feedback system for the International Linear Collider interaction point. We discuss the hardware, from stripline BPMs to kickers, and RF and digital signal processing, as well as presenting results from the latest beam tests at ATF2.

  6. Fast digital feedback control systems for accelerator RF system using FPGA

    International Nuclear Information System (INIS)

    Bagduwal, Pritam Singh; Sharma, Dheeraj; Tiwari, Nitesh; Lad, M.; Hannurkar, P.R.

    2012-01-01

    Feedback control system plays important role for proper injection and acceleration of beam in particle accelerators by providing the required amplitude and phase stability of RF fields in accelerating structures. Advancement in the field of digital technology enables us to develop fast digital feedback control system for RF applications. Digital Low Level RF (LLRF) system offers the inherent advantages of Digital System like flexibility, adaptability, good repeatability and reduced long time drift errors compared to analog system. To implement the feedback control algorithm, I/Q control scheme is used. By properly sampling the down converted IF signal using fast ADC we get accurate feedback signal and also eliminates the need of two separate detectors for amplitude and phase detection. Controller is implemented in Vertex-4 FPGA. Codes for control algorithms which controls the amplitude and phase in all four quadrants with good accuracy are written in the VHDL. I/Q modulator works as common actuator for both amplitude and phase correction. Synchronization between RF, LO and ADC clock is indispensable and has been achieved by deriving the clock and LO signal from RF signal itself. Control system has been successfully tested in lab with phase and amplitude stability better then ±1% and ±1° respectively. High frequency RF signal is down converted to IF using the super heterodyne technique. Super heterodyne principal not only brings the RF signal to the Low IF frequency at which it can be easily processed but also enables us to use the same hardware and software for other RF frequencies with some minor modification. (author)

  7. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  8. Neural network based system for script identification in Indian ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual ...

  9. Development of a hybrid system of artificial neural networks and ...

    African Journals Online (AJOL)

    Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market. ... attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining.

  10. Delayed feedback on the dynamical model of a financial system

    International Nuclear Information System (INIS)

    Son, Woo-Sik; Park, Young-Jai

    2011-01-01

    Research highlights: → Effect of delayed feedbacks on the financial model. → Proof on the occurrence of Hopf bifurcation by local stability analysis. → Numerical bifurcation analysis on delay differential equations. → Observation of supercritical and subcritical Hopf, fold limit cycle, Neimark-Sacker, double Hopf and generalized Hopf bifurcations. - Abstract: We investigate the effect of delayed feedbacks on the financial model, which describes the time variation of the interest rate, the investment demand, and the price index, for establishing the fiscal policy. By local stability analysis, we theoretically prove the occurrences of Hopf bifurcation. Through numerical bifurcation analysis, we obtain the supercritical and subcritical Hopf bifurcation curves which support the theoretical predictions. Moreover, the fold limit cycle and Neimark-Sacker bifurcation curves are detected. We also confirm that the double Hopf and generalized Hopf codimension-2 bifurcation points exist.

  11. Analysis, Design, and Evaluation of Acoustic Feedback Cancellation Systems for Hearing Aids

    DEFF Research Database (Denmark)

    Guo, Meng

    2013-01-01

    Acoustic feedback problems occur when the output loudspeaker signal of an audio system is partly returned to the input microphone via an acoustic coupling through the air. This problem often causes significant performance degradations in applications such as public address systems and hearing aids....... In the worst case, the audio system becomes unstable and howling occurs. In this work, first we analyze a general multiple microphone audio processing system, where a cancellation system using adaptive filters is used to cancel the effect of acoustic feedback. We introduce and derive an accurate approximation...... in acoustic feedback cancellation for hearing aids. It utilizes a probe noise signal which is generated with a specific characteristic so that it can facilitate an unbiased adaptive filter estimation with fast tracking of feedback path variations/changes despite its low signal level. We show in a hearing aid...

  12. A neural network based artificial vision system for licence plate recognition.

    Science.gov (United States)

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

  13. Evaluation of strip-line pick-up system for the SPS wideband transverse feedback system

    CERN Document Server

    Kotzian, G; Steinhagen, R J; Valuch, D; Wehrle, U

    2017-01-01

    The proposed SPS Wideband Transverse Feedback sys- tem requires a wide-band pick-up system to be able to de- tect intra-bunch motion within the SPS proton bunches, captured and accelerated in a 200 MHz bucket. We present the electro-magnetic design of transverse beam position pick-up options optimised for installation in the SPS and evaluate their performance reach with respect to direct time domain sampling of the intra-bunch motion. The analy- sis also discusses the achieved subsystem responses of the associated cabling with new low dispersion smooth wall coaxial cables, wide-band generation of intensity and posi- tion signals by means of 180 degree RF hybrids as well as passive techniques to electronically suppress the beam off- set signal, needed to optimise the dynamic range and posi- tion resolution of the planned digital intra-bunch feedback system.

  14. Neural mechanisms of selective attention in the somatosensory system.

    Science.gov (United States)

    Gomez-Ramirez, Manuel; Hysaj, Kristjana; Niebur, Ernst

    2016-09-01

    Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. Copyright © 2016 the American Physiological Society.

  15. Frequency-difference-dependent stochastic resonance in neural systems

    Science.gov (United States)

    Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

    2017-08-01

    Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

  16. Fault diagnosis system of electromagnetic valve using neural network filter

    International Nuclear Information System (INIS)

    Hayashi, Shoji; Odaka, Tomohiro; Kuroiwa, Jousuke; Ogura, Hisakazu

    2008-01-01

    This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection. (author)

  17. General Output Feedback Stabilization for Fractional Order Systems: An LMI Approach

    Directory of Open Access Journals (Sweden)

    Yiheng Wei

    2014-01-01

    Full Text Available This paper is concerned with the problem of general output feedback stabilization for fractional order linear time-invariant (FO-LTI systems with the fractional commensurate order 0<α<2. The objective is to design suitable output feedback controllers that guarantee the stability of the resulting closed-loop systems. Based on the slack variable method and our previous stability criteria, some new results in the form of linear matrix inequality (LMI are developed to the static and dynamic output feedback controllers synthesis for the FO-LTI system with 0<α<1. Furthermore, the results are extended to stabilize the FO-LTI systems with 1≤α<2. Finally, robust output feedback control is discussed. Numerical examples are given to illustrate the effectiveness of the proposed design methods.

  18. A feedback regulatory loop involving microRNA-9 and nuclear receptor TLX in neural stem cell fate determination.

    Science.gov (United States)

    Zhao, Chunnian; Sun, GuoQiang; Li, Shengxiu; Shi, Yanhong

    2009-04-01

    MicroRNAs have been implicated as having important roles in stem cell biology. MicroRNA-9 (miR-9) is expressed specifically in neurogenic areas of the brain and may be involved in neural stem cell self-renewal and differentiation. We showed previously that the nuclear receptor TLX is an essential regulator of neural stem cell self-renewal. Here we show that miR-9 suppresses TLX expression to negatively regulate neural stem cell proliferation and accelerate neural differentiation. Introducing a TLX expression vector that is not prone to miR-9 regulation rescued miR-9-induced proliferation deficiency and inhibited precocious differentiation. In utero electroporation of miR-9 in embryonic brains led to premature differentiation and outward migration of the transfected neural stem cells. Moreover, TLX represses expression of the miR-9 pri-miRNA. By forming a negative regulatory loop with TLX, miR-9 provides a model for controlling the balance between neural stem cell proliferation and differentiation.

  19. Feedback loops and reciprocal regulation: recurring motifs in the systems biology of the cell cycle

    OpenAIRE

    Ferrell, James E.

    2013-01-01

    The study of eukaryotic cell cycle regulation over the last several decades has led to a remarkably detailed understanding of the complex regulatory system that drives this fundamental process. This allows us to now look for recurring motifs in the regulatory system. Among these are negative feedback loops, which underpin checkpoints and generate cell cycle oscillations; positive feedback loops, which promote oscillations and make cell cycle transitions switch-like and unidirectional; and rec...

  20. Theoretical and experimental study of Chen chaotic system with notch filter feedback control

    International Nuclear Information System (INIS)

    Ming, Zhang Xiao; Jian-Hua, Peng; Ju-Fang, Chen

    2010-01-01

    Since the past two decades, the time delay feedback control method has attracted more and more attention in chaos control studies because of its simplicity and efficiency compared with other chaos control schemes. Recently, it has been proposed to suppress low-dimensional chaos with the notch filter feedback control method, which can be implemented in a laser system. In this work, we have analytically determined the controllable conditions for notch filter feedback controlling of Chen chaotic system in terms of the Hopf bifurcation theory. The conditions for notch filter feedback controlled Chen chaoitc system having a stable limit cycle solution are given. Meanwhile, we also analysed the Hopf bifurcation direction, which is very important for parameter settings in notch filter feedback control applications. Finally, we apply the notch filter feedback control methods to the electronic circuit experiments and numerical simulations based on the theoretical analysis. The controlling results of notch filter feedback control method well prove the feasibility and reliability of the theoretical analysis. (general)

  1. Synthesis of recurrent neural networks for dynamical system simulation.

    Science.gov (United States)

    Trischler, Adam P; D'Eleuterio, Gabriele M T

    2016-08-01

    We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Three neural network based sensor systems for environmental monitoring

    International Nuclear Information System (INIS)

    Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1994-05-01

    Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

  3. Singularity-Free Neural Control for the Exponential Trajectory Tracking in Multiple-Input Uncertain Systems with Unknown Deadzone Nonlinearities

    Directory of Open Access Journals (Sweden)

    J. Humberto Pérez-Cruz

    2014-01-01

    Full Text Available The trajectory tracking for a class of uncertain nonlinear systems in which the number of possible states is equal to the number of inputs and each input is preceded by an unknown symmetric deadzone is considered. The unknown dynamics is identified by means of a continuous time recurrent neural network in which the control singularity is conveniently avoided by guaranteeing the invertibility of the coupling matrix. Given this neural network-based mathematical model of the uncertain system, a singularity-free feedback linearization control law is developed in order to compel the system state to follow a reference trajectory. By means of Lyapunov-like analysis, the exponential convergence of the tracking error to a bounded zone can be proven. Likewise, the boundedness of all closed-loop signals can be guaranteed.

  4. Auditory display as feedback for a novel eye-tracking system for sterile operating room interaction.

    Science.gov (United States)

    Black, David; Unger, Michael; Fischer, Nele; Kikinis, Ron; Hahn, Horst; Neumuth, Thomas; Glaser, Bernhard

    2018-01-01

    The growing number of technical systems in the operating room has increased attention on developing touchless interaction methods for sterile conditions. However, touchless interaction paradigms lack the tactile feedback found in common input devices such as mice and keyboards. We propose a novel touchless eye-tracking interaction system with auditory display as a feedback method for completing typical operating room tasks. Auditory display provides feedback concerning the selected input into the eye-tracking system as well as a confirmation of the system response. An eye-tracking system with a novel auditory display using both earcons and parameter-mapping sonification was developed to allow touchless interaction for six typical scrub nurse tasks. An evaluation with novice participants compared auditory display with visual display with respect to reaction time and a series of subjective measures. When using auditory display to substitute for the lost tactile feedback during eye-tracking interaction, participants exhibit reduced reaction time compared to using visual-only display. In addition, the auditory feedback led to lower subjective workload and higher usefulness and system acceptance ratings. Due to the absence of tactile feedback for eye-tracking and other touchless interaction methods, auditory display is shown to be a useful and necessary addition to new interaction concepts for the sterile operating room, reducing reaction times while improving subjective measures, including usefulness, user satisfaction, and cognitive workload.

  5. IMI's teaching design, feedback system and its localization

    Science.gov (United States)

    Wen, Tingting; Zhang, Xuexin

    2017-08-01

    In Britain, the Institute of the Motor Industry (IMI) sets the National Occupational Standards for all sectors of the automotive industry. The IMI certificate and associated training programs are well recognized for its high quality both in the United Kingdom (UK) and internationally. Using China's first groups studying IMI Level 3 certificate for teachers and Level 2 certificate for students as a sample, we analyzed the seven central aspects in IMI teaching, namely, assessment standard, environment, method, content, procedure, quality control and feedback. We then proposed strategies and guidelines for its localization in China, which would be particularly important for the establishment and expansion of IMI centers.

  6. Neural multigrid for gauge theories and other disordered systems

    International Nuclear Information System (INIS)

    Baeker, M.; Kalkreuter, T.; Mack, G.; Speh, M.

    1992-09-01

    We present evidence that multigrid works for wave equations in disordered systems, e.g. in the presence of gauge fields, no matter how strong the disorder, but one needs to introduce a 'neural computations' point of view into large scale simulations: First, the system must learn how to do the simulations efficiently, then do the simulation (fast). The method can also be used to provide smooth interpolation kernels which are needed in multigrid Monte Carlo updates. (orig.)

  7. Neural computing thermal comfort index for HVAC systems

    International Nuclear Information System (INIS)

    Atthajariyakul, S.; Leephakpreeda, T.

    2005-01-01

    The primary purpose of a heating, ventilating and air conditioning (HVAC) system within a building is to make occupants comfortable. Without real time determination of human thermal comfort, it is not feasible for the HVAC system to yield controlled conditions of the air for human comfort all the time. This paper presents a practical approach to determine human thermal comfort quantitatively via neural computing. The neural network model allows real time determination of the thermal comfort index, where it is not practical to compute the conventional predicted mean vote (PMV) index itself in real time. The feed forward neural network model is proposed as an explicit function of the relation of the PMV index to accessible variables, i.e. the air temperature, wet bulb temperature, globe temperature, air velocity, clothing insulation and human activity. An experiment in an air conditioned office room was done to demonstrate the effectiveness of the proposed methodology. The results show good agreement between the thermal comfort index calculated from the neural network model in real time and those calculated from the conventional PMV model

  8. Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control

    International Nuclear Information System (INIS)

    Fu Shi-Hui; Lu Qi-Shao; Du Ying

    2012-01-01

    Adaptive H ∞ synchronization of chaotic systems via linear and nonlinear feedback control is investigated. The chaotic systems are redesigned by using the generalized Hamiltonian systems and observer approach. Based on Lyapunov's stability theory, linear and nonlinear feedback control of adaptive H ∞ synchronization is established in order to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance on an H ∞ -norm constraint. Adaptive H ∞ synchronization of chaotic systems via three kinds of control is investigated with applications to Lorenz and Chen systems. Numerical simulations are also given to identify the effectiveness of the theoretical analysis. (general)

  9. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  10. Nonclassical state generation for linear quantum systems via nonlinear feedback control

    International Nuclear Information System (INIS)

    Ohki, Kentaro; Tsumura, Koji; Takeuchi, Reiji

    2017-01-01

    In this paper, we propose a measurement nonlinear feedback control scheme to generate Wigner-function negativity in an optical cavity having dynamics described as a linear quantum system. In general, linear optical quantum systems can be easily constructed with reliable devices; therefore, the idea of constructing the entire system with such an optical system and nonlinear feedback is reasonable for generating Wigner-function negativity. However, existing studies have insufficiently examined the realizability or actual implementation of feedback control, which essentially requires fast responses from the sensors and actuators. In order to solve this problem, we consider the realizable feedback control of the optical phase of a pumping beam supplied to a cavity by using electro-optical modulation, which can be utilized as a fast control actuator. Then, we introduce mathematical models of the feedback-controlled system and evaluate its effect on the generation of the Wigner-function negativity by using numerical simulation. Through various numerical simulations, we show that the proposed feedback control can effectively generate the negativity of the Wigner function. (paper)

  11. Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

    Science.gov (United States)

    Si, Wenjie; Dong, Xunde; Yang, Feifei

    2018-03-01

    This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Beam stability in synchrotrons with digital transverse feedback systems in dependence on beam tunes

    International Nuclear Information System (INIS)

    Zhabitskij, V.M.

    2011-01-01

    The beam stability problem in synchrotrons with a digital transverse feedback system (TFS) is studied. The TFS damper kicker (DK) corrects the transverse momentum of a bunch in proportion to its displacement from the closed orbit measured at the location of the beam position monitor (BPM). It is shown that the area and configuration of the beam stability separatrix depend on the beam tune, the feedback gain, the phase balance between the phase advance from BPM to DK and the phase response of the feedback chain at the betatron frequency

  13. Numerical Simulation of the Oscillations in a Mixer: An Internal Aeroacoustic Feedback System

    Science.gov (United States)

    Jorgenson, Philip C. E.; Loh, Ching Y.

    2004-01-01

    The space-time conservation element and solution element method is employed to numerically study the acoustic feedback system in a high temperature, high speed wind tunnel mixer. The computation captures the self-sustained feedback loop between reflecting Mach waves and the shear layer. This feedback loop results in violent instabilities that are suspected of causing damage to some tunnel components. The computed frequency is in good agreement with the available experimental data. The physical phenomena are explained based on the numerical results.

  14. Digital closed orbit feedback system for the advanced photon source storage ring

    International Nuclear Information System (INIS)

    Chung, Y.; Barr, D.; Decker, G.

    1995-01-01

    The Advanced Photon Source (APS) is a dedicated third-generation synchrotron light source with a nominal energy of 7 GeV and a circumference of 1104 m. The closed orbit feedback system for the APS storage ring employs unified global and local feedback systems for stabilization of particle and photon beams based on digital signal processing (DSP). Hardware and software aspects of the system will be described in this paper. In particular, we will discuss global and local orbit feedback algorithms, PID (proportional, integral, and derivative) control algorithm, application of digital signal processing to compensate for vacuum chamber eddy current effects, resolution of the interaction between global and local systems through decoupling, self-correction of the local bump closure error, user interface through the APS control system, and system performance in the frequency and time domains. The system hardware including the DSPs is distributed in 20 VME crates around the ring, and the entire feedback system runs synchronously at 4-kHz sampling frequency in order to achieve a correction bandwidth exceeding 100 Hz. The required data sharing between the global and local feedback systems is facilitated via the use of fiber-optically-networked reflective memories

  15. Feedback dynamics and cell function: Why systems biology is called Systems Biology.

    Science.gov (United States)

    Wolkenhauer, Olaf; Mesarovic, Mihajlo

    2005-05-01

    A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

  16. Analysis of the DWPF glass pouring system using neural networks

    International Nuclear Information System (INIS)

    Calloway, T.B. Jr.; Jantzen, C.M.

    1997-01-01

    Neural networks were used to determine the sensitivity of 39 selected Melter/Melter Off Gas and Melter Feed System process parameters as related to the Defense Waste Processing Facility (DWPF) Melter Pour Spout Pressure during the overall analysis and resolution of the DWPF glass production and pouring issues. Two different commercial neural network software packages were used for this analysis. Models were developed and used to determine the critical parameters which accurately describe the DWPF Pour Spout Pressure. The model created using a low-end software package has a root mean square error of ± 0.35 inwc ( 2 = 0.77) with respect to the plant data used to validate and test the model. The model created using a high-end software package has a R 2 = 0.97 with respect to the plant data used to validate and test the model. The models developed for this application identified the key process parameters which contribute to the control of the DWPF Melter Pour Spout pressure during glass pouring operations. The relative contribution and ranking of the selected parameters was determined using the modeling software. Neural network computing software was determined to be a cost-effective software tool for process engineers performing troubleshooting and system performance monitoring activities. In remote high-level waste processing environments, neural network software is especially useful as a replacement for sensors which have failed and are costly to replace. The software can be used to accurately model critical remotely installed plant instrumentation. When the instrumentation fails, the software can be used to provide a soft sensor to replace the actual sensor, thereby decreasing the overall operating cost. Additionally, neural network software tools require very little training and are especially useful in mining or selecting critical variables from the vast amounts of data collected from process computers

  17. Neural Computations in a Dynamical System with Multiple Time Scales.

    Science.gov (United States)

    Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

    2016-01-01

    Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

  18. Statistical Physics of Neural Systems with Nonadditive Dendritic Coupling

    Directory of Open Access Journals (Sweden)

    David Breuer

    2014-03-01

    Full Text Available How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such nonadditive dendritic processing on single-neuron responses and the performance of associative-memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality.

  19. Synchronization of chaotic systems and identification of nonlinear systems by using recurrent hierarchical type-2 fuzzy neural networks.

    Science.gov (United States)

    Mohammadzadeh, Ardashir; Ghaemi, Sehraneh

    2015-09-01

    This paper proposes a novel approach for training of proposed recurrent hierarchical interval type-2 fuzzy neural networks (RHT2FNN) based on the square-root cubature Kalman filters (SCKF). The SCKF algorithm is used to adjust the premise part of the type-2 FNN and the weights of defuzzification and the feedback weights. The recurrence property in the proposed network is the output feeding of each membership function to itself. The proposed RHT2FNN is employed in the sliding mode control scheme for the synchronization of chaotic systems. Unknown functions in the sliding mode control approach are estimated by RHT2FNN. Another application of the proposed RHT2FNN is the identification of dynamic nonlinear systems. The effectiveness of the proposed network and its learning algorithm is verified by several simulation examples. Furthermore, the universal approximation of RHT2FNNs is also shown. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.

    Science.gov (United States)

    Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael

    2018-02-01

    We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

  1. Performance Analysis of Simple Channel Feedback Schemes for a Practical OFDMA System

    DEFF Research Database (Denmark)

    Pedersen, Klaus, I.; Kolding, Troels; Kovacs, Istvan

    2009-01-01

    In this paper, we evaluate the tradeoff between the amount of uplink channel feedback information and the orthogonal frequency-division multiple access (OFDMA) downlink performance with opportunistic frequency-domain packet scheduling. Three candidate channel feedback schemes are investigated......, including practical aspects, such as the effects of terminal measurement errors, bandwidth measurement granularity, quantization, and uplink signaling delays. The performance is evaluated by means of system-level simulations with detailed modeling of various radio resource-management algorithms, etc. Our...... results show that the optimal tradeoff between the channel feedback and the downlink OFDMA system performance depends on the radio channel frequency coherence bandwidth. We conclude that the so-called average best-M scheme is the most attractive channel feedback solution, where only the average channel...

  2. COMMISSIONING OF THE DIGITAL TRANSVERSE BUNCH-BY-BUNCH FEEDBACK SYSTEM FOR THE TLS

    International Nuclear Information System (INIS)

    HU, K.H.; KUO, C.H.; CHOU, P.J.; LEE, D.; HSU, S.Y.; CHEN, J.; WANG, C.J.; HSU, K.T.; KOBAYASHI, K.; NAKAMURA, T.; CHAO, A.W.; WENG, W.T.

    2006-01-01

    Multi-bunch instabilities degrade beam quality through increased beam emittance, energy spread and even beam loss. Feedback systems are used to suppress multi-bunch instabilities associated with the resistive wall of the beam ducts, cavity-like structures, and trapped ions. A new digital transverse bunch-by-bunch feedback system has recently been commissioned at the Taiwan Light Source, and has replaced the previous analog system. The new system has the advantages that it enlarges the tune acceptance and improves damping for transverse instability at high currents, such that top-up operation is achieved. After a coupled-bunch transverse instability was suppressed, more than 350 mA was successfully stored during preliminary commissioning. In this new system, a single feedback loop simultaneously suppresses both horizontal and vertical multi-bunch instabilities. Investigating the characteristics of the feedback loop and further improving the system performances are the next short-term goals. The feedback system employs the latest generation of field-programmable gate array (FPGA) processor to process bunch signals. Memory has been installed to capture up to 250 msec of bunch oscillation signal, considering system diagnostics suitable to support various beam physics studies

  3. Digital closed orbit feedback system for the Advanced Photon Source storage ring

    International Nuclear Information System (INIS)

    Chung, Y.; Barr, D.; Decker, G.; Galayda, J.; Lenkszus, F.; Lumpkin, A.; Votaw, A.J.

    1995-01-01

    Closed orbit feedback for the Advanced Photon Source (APS) storage ring employs unified global an local feedback systems for stabilization of particle and photon beams based on digital signal processing (DSP). Hardware and software aspects of the system will be described. In particular, we will discuss global and local orbit feedback algorithms, PID (proportional, integral, and derivative) control algorithm. application of digital signal processing to compensate for vacuum chamber eddy current effects, resolution of the interaction between global and local systems through decoupling, self-correction of the local bump closure error, user interface through the APS control system, and system performance in the frequency and time domains. The system hardware, including the DSPS, is distributed in 20 VNE crates around the ring, and the entire feedback system runs synchronously at 4-kHz sampling frequency in order to achieve a correction bandwidth exceeding 100 Hz. The required data sharing between the global and local feedback systems is facilitated via the use of fiber-optically-networked reflective memories

  4. The patient comment card: a system to gather customer feedback.

    Science.gov (United States)

    Nelson, E C; Larson, C O; Davies, A R; Gustafson, D; Ferreira, P L; Ware, J E

    1991-09-01

    Continuous patient feedback can give important information to hospitals about the quality of care they provide. The Patient Comment Card (PCC), a brief form that can be used to gather open-ended comments from patients and to measure quality, was developed during a two-year period and was extensively evaluated in a series of three pilot tests involving more than 2,000 patients discharged from five hospitals. Evaluation results demonstrate that the questionnaire elicits useful comments from patients and can generate statistically reliable scores and valid quality measures. However, in a field trial in four hospitals, low response rates (15%-27%) reflected, first, lack of follow-up of non-respondents, and second, the fact that most of the PCC quality scores were upwardly biased; these inflated scores were likely to reflect the low response rate. Tools such as the PCC should be used judiciously, given the possible abuses and misinterpretations of hospital quality scores.

  5. Plasma control techniques of the ASDEX feedback system

    International Nuclear Information System (INIS)

    Schneider, F.

    1981-01-01

    In the ASDEX tokamak the shots are exactly preprogrammed and most of the disturbances are reproducible. So a computer can learn from one shot how to correct the next one. With this sort of disturbance feedforward one can also introduce a 'negative delay' in the program to compensate even fast and strong disturbances withous unwanted overswing or oscillations. The feedforward in conjunction with feedback control allows production of a magnetically limited plasma from the very beginning without any wall or limiter contact. This is a reason why in ASDEX the loop voltage on breakdown can be as low as 5 V/sup 2/. The plasma column can be controlled in the vacuum vessel even after disruptions have occurred

  6. A New Kicker for the TLS Longitudinal Feedback System

    CERN Document Server

    Lau, Wai-Keung; Dehler, Micha; Hsu, Kuo-Tung; Hsu, San-Yuang; Jung Chou Ping; Wei Chen, Cheng; Yang Chen Huan; Yang Tze Te

    2005-01-01

    A new longitudinal kicker that is modified from the Swiss Light Source (SLS) design to fit into the TLS storage ring. It will be served as the actuator in the longitudinal multi-bunch feedback control loop. Beam coupling impedance has been calculated by Gdfidl with a PC cluster. Previous to the installation of this new kicker, bench measurement has been performed in the laboratory to characterize this new kicker. The experimental setups for bandwidth and coaxial wire measurement of longitudinal coupling impedance and their corresponding test results will be reported. As a cross check, bead-pull measurement has also been done to verify the beam coupling measurement by coaxial wire method at the kicker center frequency. Longitudinal field profile of the accelerating mode along the beam path has also been mapped. High order cavity modes of the kicker have also been observed and their effects on the beam are evaluated.

  7. Neural network-based expert system for severe accident management

    International Nuclear Information System (INIS)

    Klopp, G.T.; Silverman, E.B.

    1992-01-01

    This paper presents the results of the second phase of a three-phase Severe Accident Management expert system program underway at Commonwealth Edison Company (CECo). Phase I successfully demonstrated the feasibility of Artificial Neural Networks to support several of the objectives of severe accident management. Simulated accident scenarios were generated by the Modular Accident Analysis Program (MAAP) code currently in use by CECo as part of their Individual Plant Evaluations (IPE)/Accident Management Program. The primary objectives of the second phase were to develop and demonstrate four capabilities of neural networks with respect to nuclear power plant severe accident monitoring and prediction. The results of this work would form the foundation of a demonstration system which included expert system performance features. These capabilities included the ability to: (1) Predict the time available prior to support plate (and reactor vessel) failure; (2) Calculate the time remaining until recovery actions were too late to prevent core damage; (3) Predict future parameter values of each of the MAAP parameter variables; and (4) Detect simulated sensor failure and provide best-value estimates for further processing in the presence of a sensor failure. A variety of accident scenarios for the Zion and Dresden plants were used to train and test the neural network expert system. These included large and small break LOCAs as well as a range of transient events. 3 refs., 1 fig., 1 tab

  8. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  9. Neural Mechanisms and Information Processing in Recognition Systems

    Directory of Open Access Journals (Sweden)

    Mamiko Ozaki

    2014-10-01

    Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

  10. Signatures of Biogeomorphic Feedbacks in Salt-Marsh Systems

    Science.gov (United States)

    D'Alpaos, Andrea; Marani, Marco

    2015-04-01

    Salt-marsh ecosystems which play a large role in the bio-geomorphological evolution of intertidal areas. Dense stands of halophytic vegetations which populate salt marshes largely control the dynamics of these ecosystems influencing marsh hydrodynamics and sediment transport through enhanced flow resistance and settling, and direct particle capture by plant stems. Moreover, plants are also known to increase vertical accretion through direct organic accretion. Field evidence and the results of biomorphodynamic models indeed show that the interplay between physical and biological processes generates some striking biological and morphological patterns at different scales. One such pattern, vegetation zonation, consists in a mosaic of vegetation patches, of approximately uniform composition, displaying sharp transitions in the presence of extremely small topographic gradients. Here we develop a two-dimensional model which describes the mutual interaction and adjustment between tidal flows, sediment transport and morphology mediated by vegetation influence. The model allows us describe the coupled evolution of marsh platforms and channel networks cutting through them. A number of different scenarios were modelled to analyze the changes induced in bio-geomorphic patterns by plants with different characteristics, within marshes characterized by different drainage densities, or subjected to changing environmental forcing such as rates of relative sea level rise and sediment supply. Model results emphasize that zonation patterns are a signature of bio-geomorphic feedbacks with vegetation acting as a landscape constructor which feeds back on, directly alters, and contributes to shape tidal environments. In addition, model results show that biogeomorphic feedbacks critically affect the response and the resilience of salt-marsh landscapes to changes in the environmental forcing.

  11. The phase detection and calculation for low hybrid wave phase-feedback control system

    International Nuclear Information System (INIS)

    Liu Qiang; Liang Hao; Zhou Yongzhao; Shan Jiafang

    2008-01-01

    A method of phase detection and calculation for low hybrid wave phase-feedback control system and the implementing the algorithms on DSP cores embedded in FPGA is introduced. By taking the advantages of matlab-aided design and algorithms optimization to carry out parallel processing of multi-channel phase calculation in FPGA with rich resources, the purposed of fast phase-feedback control is achieved under the need of complicated mathematical operations. (authors)

  12. Feedback controlled dephasing and population relaxation in a two-level system

    International Nuclear Information System (INIS)

    Wang Jin

    2009-01-01

    This Letter presents the maximum achievable stability and purity that can be obtained in a two-level system with both dephasing and population relaxation processes by using homodyne-mediated feedback control. An analytic formula giving the optimal amplitudes of the driving and feedback for the steady-state is also presented. Experimental examples are used to show the importance of controlling the dephasing process.

  13. Nonlinear dynamical system approaches towards neural prosthesis

    International Nuclear Information System (INIS)

    Torikai, Hiroyuki; Hashimoto, Sho

    2011-01-01

    An asynchronous discrete-state spiking neurons is a wired system of shift registers that can mimic nonlinear dynamics of an ODE-based neuron model. The control parameter of the neuron is the wiring pattern among the registers and thus they are suitable for on-chip learning. In this paper an asynchronous discrete-state spiking neuron is introduced and its typical nonlinear phenomena are demonstrated. Also, a learning algorithm for a set of neurons is presented and it is demonstrated that the algorithm enables the set of neurons to reconstruct nonlinear dynamics of another set of neurons with unknown parameter values. The learning function is validated by FPGA experiments.

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

    Science.gov (United States)

    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

  15. Sympathetic neural modulation of the immune system

    International Nuclear Information System (INIS)

    Madden, K.S.

    1989-01-01

    One route by which the central nervous system communicates with lymphoid organs in the periphery is through the sympathetic nervous system (SNS). To study SNS regulation of immune activity in vivo, selective removal of peripheral noradrenergic nerve fibers was achieved by administration of the neurotoxic drug, 6-hydroxydopamine (6-OHDA), to adult mice. To assess SNS influence on lymphocyte proliferation in vitro, uptake of 125 iododeoxyuridine ( 125 IUdR), a DNA precursor, was measured following 6-OHDA treatment. Sympathectomy prior to epicutaneous immunization with TNCB did not alter draining lymph nodes (LN) cell proliferation, whereas 6-OHDA treatment before footpad immunization with KLH reduced DNA synthesis in popliteal LN by 50%. In mice which were not deliberately immunized, sympathectomy stimulated 125 IUdR uptake inguinal and axillary LN, spleen, and bone marrow. In vitro, these LN and spleen cells exhibited decreased proliferation responses to the T cell mitogen, concanavalin A (Con A), whereas lipopolysaccharide (LPS)-stimulated IgG secretion was enhanced. Studies examining 51 Cr-labeled lymphocyte trafficking to LN suggested that altered cell migration may play a part in sympathectomy-induced changes in LN cell function

  16. Utility of an app-based system to improve feedback following workplace-based assessment.

    Science.gov (United States)

    Lefroy, Janet; Roberts, Nicola; Molyneux, Adrian; Bartlett, Maggie; Gay, Simon; McKinley, Robert

    2017-05-31

    To determine whether an app-based software system to support production and storage of assessment feedback summaries makes workplace-based assessment easier for clinical tutors and enhances the educational impact on medical students. We monitored our workplace assessor app's usage by Year 3 to 5 medical students in 2014-15 and conducted focus groups with Year 4 medical students and interviews with clinical tutors who had used the apps. Analysis was by constant comparison using a framework based on elements of van der Vleuten's utility index. The app may enhance the content of feedback for students. Using a screen may be distracting if the app is used during feedback discussions.    Educational impact was reduced by students' perceptions that an easy-to-produce feedback summary is less valuable than one requiring more tutor time and effort. Tutors' typing, dictation skills and their familiarity with mobile devices varied. This influenced their willingness to use the assessment and feedback mobile app rather than the equivalent web app. Electronic feedback summaries had more real and perceived uses than anticipated both for tutors and students including perceptions that they were for the school rather than the student. Electronic workplace-based assessment systems can be acceptable to tutors and can make giving detailed written feedback more practical but can interrupt the social interaction required for the feedback conversation. Tutor training and flexible systems will be required to minimise unwanted consequences. The educational impact on both tutors and students of providing pre-formulated advice within the app is worth further study.

  17. Chaos control for the family of Roessler systems using feedback controllers

    International Nuclear Information System (INIS)

    Liao Xiaoxin; Yu Pei

    2006-01-01

    This paper presents a new method for controlling chaos in several classical chaotic Roessler systems using feedback control strategy. In particular, for an arbitrarily given equilibrium point of a Roessler system, we design explicit and simple feedback control laws by which the equilibrium point is globally and exponentially stabilized. Six typical Roessler systems are studied, and explicit formulas are derived for estimating the convergence rate of these systems. Numerical examples are presented to illustrate the theoretical results. A mistake has been found in the existing literature, and a correct result is given

  18. Lyapunov-based Stability of Feedback Interconnections of Negative Imaginary Systems

    KAUST Repository

    Ghallab, Ahmed G.

    2017-10-19

    Feedback control systems using sensors and actuators such as piezoelectric sensors and actuators, micro-electro-mechanical systems (MEMS) sensors and opto-mechanical sensors, are allowing new advances in designing such high precision technologies. The negative imaginary control systems framework allows for robust control design for such high precision systems in the face of uncertainties due to unmodelled dynamics. The stability of the feedback interconnection of negative imaginary systems has been well established in the literature. However, the proofs of stability feedback interconnection which are used in some previous papers have a shortcoming due to a matrix inevitability issue. In this paper, we provide a new and correct Lyapunov-based proof of one such result and show that the result is still true.

  19. Finite-time stabilization of uncertain nonholonomic systems in feedforward-like form by output feedback.

    Science.gov (United States)

    Gao, Fangzheng; Wu, Yuqiang; Zhang, Zhongcai

    2015-11-01

    This paper investigates the problem of finite-time stabilization by output feedback for a class of nonholonomic systems in chained form with uncertainties. Comparing with the existing relevant literature, a distinguishing feature of the systems under investigation is that the x-subsystem is a feedforward-like rather than feedback-like system. This renders the existing control methods inapplicable to the control problems of the systems. A constructive design procedure for output feedback control is given. The designed controller renders that the states of closed-loop system are regulated to zero in a finite time. Two simulation examples are provided to illustrate the effectiveness of the proposed approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Lyapunov-based Stability of Feedback Interconnections of Negative Imaginary Systems

    KAUST Repository

    Ghallab, Ahmed G.; Mabrok, Mohamed; Petersen, Ian R.

    2017-01-01

    Feedback control systems using sensors and actuators such as piezoelectric sensors and actuators, micro-electro-mechanical systems (MEMS) sensors and opto-mechanical sensors, are allowing new advances in designing such high precision technologies. The negative imaginary control systems framework allows for robust control design for such high precision systems in the face of uncertainties due to unmodelled dynamics. The stability of the feedback interconnection of negative imaginary systems has been well established in the literature. However, the proofs of stability feedback interconnection which are used in some previous papers have a shortcoming due to a matrix inevitability issue. In this paper, we provide a new and correct Lyapunov-based proof of one such result and show that the result is still true.

  1. Integrated regional changes in arctic climate feedbacks: Implications for the global climate system

    Science.gov (United States)

    McGuire, A.D.; Chapin, F. S.; Walsh, J.E.; Wirth, C.; ,

    2006-01-01

    The Arctic is a key part of the global climate system because the net positive energy input to the tropics must ultimately be resolved through substantial energy losses in high-latitude regions. The Arctic influences the global climate system through both positive and negative feedbacks that involve physical, ecological, and human systems of the Arctic. The balance of evidence suggests that positive feedbacks to global warming will likely dominate in the Arctic during the next 50 to 100 years. However, the negative feedbacks associated with changing the freshwater balance of the Arctic Ocean might abruptly launch the planet into another glacial period on longer timescales. In light of uncertainties and the vulnerabilities of the climate system to responses in the Arctic, it is important that we improve our understanding of how integrated regional changes in the Arctic will likely influence the evolution of the global climate system. Copyright ?? 2006 by Annual Reviews. All rights reserved.

  2. A Complete Parametric Solutions of Eigenstructure Assignment by State-Derivative Feedback for Linear Control Systems

    Directory of Open Access Journals (Sweden)

    T. H. S. Abdelaziz

    2005-01-01

    Full Text Available In this paper we introduce a complete parametric approach for solving the problem of eigenstructure assignment via state-derivative feedback for linear systems. This problem is always solvable for any controllable systems iff the open-loop system matrix is nonsingular. In this work, two parametric solutions to the feedback gain matrix are introduced that describe the available degrees of freedom offered by the state-derivative feedback in selecting the associated eigenvectors from an admissible class. These freedoms can be utilized to improve robustness of the closed-loop system. Accordingly, the sensitivity of the assigned eigenvalues to perturbations in the system and gain matrix is minimized. Numerical examples are included to show the effectiveness of the proposed approach. 

  3. Parameter identification technique for uncertain chaotic systems using state feedback and steady-state analysis.

    Science.gov (United States)

    Zaher, Ashraf A

    2008-03-01

    A technique is introduced for identifying uncertain and/or unknown parameters of chaotic dynamical systems via using simple state feedback. The proposed technique is based on bringing the system into a stable steady state and then solving for the unknown parameters using a simple algebraic method that requires access to the complete or partial states of the system depending on the dynamical model of the chaotic system. The choice of the state feedback is optimized in terms of practicality and causality via employing a single feedback signal and tuning the feedback gain to ensure both stability and identifiability. The case when only a single scalar time series of one of the states is available is also considered and it is demonstrated that a synchronization-based state observer can be augmented to the state feedback to address this problem. A detailed case study using the Lorenz system is used to exemplify the suggested technique. In addition, both the Rössler and Chua systems are examined as possible candidates for utilizing the proposed methodology when partial identification of the unknown parameters is considered. Finally, the dependence of the proposed technique on the structure of the chaotic dynamical model and the operating conditions is discussed and its advantages and limitations are highlighted via comparing it with other methods reported in the literature.

  4. Assessing Whether Students Seek Constructive Criticism: The Design of an Automated Feedback System for a Graphic Design Task

    Science.gov (United States)

    Cutumisu, Maria; Blair, Kristen P.; Chin, Doris B.; Schwartz, Daniel L.

    2017-01-01

    We introduce a choice-based assessment strategy that measures students' choices to seek constructive feedback and to revise their work. We present the feedback system of a game we designed to assess whether students choose positive or negative feedback and choose to revise their posters in the context of a poster design task, where they learn…

  5. Research of the master-slave robot surgical system with the function of force feedback.

    Science.gov (United States)

    Shi, Yunyong; Zhou, Chaozheng; Xie, Le; Chen, Yongjun; Jiang, Jun; Zhang, Zhenfeng; Deng, Ze

    2017-12-01

    Surgical robots lack force feedback, which may lead to operation errors. In order to improve surgical outcomes, this research developed a new master-slave surgical robot, which was designed with an integrated force sensor. The new structure designed for the master-slave robot employs a force feedback mechanism. A six-dimensional force sensor was mounted on the tip of the slave robot's actuator. Sliding model control was adopted to control the slave robot. According to the movement of the master system manipulated by the surgeon, the slave's movement and the force feedback function were validated. The motion was completed, the standard deviation was calculated, and the force data were detected. Hence, force feedback was realized in the experiment. The surgical robot can help surgeons to complete trajectory motions with haptic sensation. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Bifurcation Regulations Governed by Delay Self-Control Feedback in a Stochastic Birhythmic System

    Science.gov (United States)

    Ma, Zhidan; Ning, Lijuan

    2017-12-01

    We aim to investigate bifurcation behaviors in a stochastic birhythmic van der Pol (BVDP) system subjected to delay self-control feedback. First, the harmonic approximation is adopted to drive the delay self-control feedback to state variables without delay. Then, Fokker-Planck-Kolmogorov (FPK) equation and stationary probability density function (SPDF) for amplitude are obtained by applying stochastic averaging method. Finally, dynamical scenarios of the change of delay self-control feedback as well as noise that markedly influence bifurcation performance are observed. It is found that: the big feedback strength and delay will suppress the large amplitude limit cycle (LC) while the relatively big noise strength facilitates the large amplitude LC, which imply the proposed regulation strategies are feasible. Interestingly enough, the inner LC is never destroyed due to noise. Furthermore, the validity of analytical results was verified by Monte Carlo simulation of the dynamics.

  7. A state variable approach to the BESSY II local beam-position-feedback system

    International Nuclear Information System (INIS)

    Gilpatrick, J.D.; Khan, S.; Kraemer, D.

    1996-01-01

    At the BESSY II facility, stability of the electron beam position and angle near insertion devices (IDs) is of utmost importance. Disturbances due to ground motion could result in unwanted broad-bandwidth beam-jitter which decreases the electron (and resultant photon) beam's effective brightness. Therefore, feedback techniques must be used. Operating over a frequency range of 100-Hz, a local feedback system will correct these beam-trajectory errors using the four bumps around IDs. This paper reviews how the state-variable feedback approach can be applied to real-time correction of these beam position and angle errors. A frequency-domain solution showing beam jitter reduction is presented. Finally, this paper reports results of a beam-feedback test at BESSY I

  8. Group support system and explanatory feedback: An experimental study of mitigating halo effect

    Directory of Open Access Journals (Sweden)

    Intiyas Utami

    2015-12-01

    Full Text Available Comprehensive assessment potentially leads to halo effect that will affect accuracy of auditors decision-making process. Biased initial audit decision will potentially influence final audit decision. It is there-fore necessary to mitigate halo effect that is the consequence of auditors good impression on clients initial condition. This re-search aims to empirically show that halo effect can be mitigated by explanatory feedback and Group Support System (GSS. The researchers experimentally mani-pulate explanatory feedback and GSS using online web-site. The subjects are stu-dents who have already taken auditing courses. The results show that: 1 explanato-ry feedback can mitigate halo effect so that audit decision will be more accurate 2 GSS can also mitigate halo effect 3 explanatory feedback and GSS are the best me-thods to mitigate halo effect.

  9. Fuzzy-Neural Automatic Daylight Control System

    Directory of Open Access Journals (Sweden)

    Grif H. Şt.

    2011-12-01

    Full Text Available The paper presents the design and the tuning of a CMAC controller (Cerebellar Model Articulation Controller implemented in an automatic daylight control application. After the tuning process of the controller, the authors studied the behavior of the automatic lighting control system (ALCS in the presence of luminance disturbances. The luminance disturbances were produced by the authors in night conditions and day conditions as well. During the night conditions, the luminance disturbances were produced by turning on and off a halogen desk lamp. During the day conditions the luminance disturbances were produced in two ways: by daylight contributions changes achieved by covering and uncovering a part of the office window and by turning on and off a halogen desk lamp. During the day conditions the luminance disturbances, produced by turning on and off the halogen lamp, have a smaller amplitude than those produced during the night conditions. The luminance disturbance during the night conditions was a helpful tool to select the proper values of the learning rate for CMAC controller. The luminance disturbances during the day conditions were a helpful tool to demonstrate the right setting of the CMAC controller.

  10. Autogenic-Feedback Training Exercise (AFTE) Method and System

    Science.gov (United States)

    Cowings, Patricia S. (Inventor)

    1997-01-01

    The Autogenic-Feedback Training Exercise (AFTE) method of the present invention is a combined application of physiologic and perceptual training techniques. such as autogenic therapy and biofeedback. This combined therapy approach produces a methodology that is appreciably more effective than either of the individual techniques used separately. The AFTE method enables sufficient magnitude of control necessary to significantly reduce the behavioral and physiologic reactions to severe environmental stressors. It produces learned effects that are persistent over time and are resistant to extinction and it can be administered in a short period of time. The AFTE method may be used efficiently in several applications, among which are the following: to improve pilot and crew performance during emergency flying conditions; to train people to prevent the occurrence of nausea and vomiting associated with motion and sea sickness, or morning sickness in early pregnancy; as a training method for preventing or counteracting air-sickness symptoms in high-performance military aircraft; for use as a method for cardiovascular training, as well as for multiple other autonomic responses, which may contribute to the alleviation of Space Motion Sickness (SMS) in astronauts and cosmonauts; training people suffering from migraine or tension headaches to control peripheral blood flow and reduce forehead and/or trapezius muscle tension; training elderly people suffering from fecal incontinence to control their sphincter muscles; training cancer patients to reduce the nauseagenic effects of chemotherapy; and training patients with Chronic Intestinal Pseudo-obstruction (CIP).

  11. Reliability analysis of a consecutive r-out-of-n: F system based on neural networks

    International Nuclear Information System (INIS)

    Habib, Aziz; Alsieidi, Ragab; Youssef, Ghada

    2009-01-01

    In this paper, we present a generalized Markov reliability and fault-tolerant model, which includes the effects of permanent fault and intermittent fault for reliability evaluations based on neural network techniques. The reliability of a consecutive r-out-of-n: F system was obtained with a three-layer connected neural network represents a discrete time state reliability Markov model of the system. Such that we fed the neural network with the desired reliability of the system under design. Then we extracted the parameters of the system from the neural weights at the convergence of the neural network to the desired reliability. Finally, we obtain simulation results.

  12. Study on real-time force feedback for a master-slave interventional surgical robotic system.

    Science.gov (United States)

    Guo, Shuxiang; Wang, Yuan; Xiao, Nan; Li, Youxiang; Jiang, Yuhua

    2018-04-13

    In robot-assisted catheterization, haptic feedback is important, but is currently lacking. In addition, conventional interventional surgical robotic systems typically employ a master-slave architecture with an open-loop force feedback, which results in inaccurate control. We develop herein a novel real-time master-slave (RTMS) interventional surgical robotic system with a closed-loop force feedback that allows a surgeon to sense the true force during remote operation, provide adequate haptic feedback, and improve control accuracy in robot-assisted catheterization. As part of this system, we also design a unique master control handle that measures the true force felt by a surgeon, providing the basis for the closed-loop control of the entire system. We use theoretical and empirical methods to demonstrate that the proposed RTMS system provides a surgeon (using the master control handle) with a more accurate and realistic force sensation, which subsequently improves the precision of the master-slave manipulation. The experimental results show a substantial increase in the control accuracy of the force feedback and an increase in operational efficiency during surgery.

  13. Methane Feedbacks to the Global Climate System in a Warmer World

    Science.gov (United States)

    Dean, Joshua F.; Middelburg, Jack J.; Röckmann, Thomas; Aerts, Rien; Blauw, Luke G.; Egger, Matthias; Jetten, Mike S. M.; de Jong, Anniek E. E.; Meisel, Ove H.; Rasigraf, Olivia; Slomp, Caroline P.; in't Zandt, Michiel H.; Dolman, A. J.

    2018-03-01

    Methane (CH4) is produced in many natural systems that are vulnerable to change under a warming climate, yet current CH4 budgets, as well as future shifts in CH4 emissions, have high uncertainties. Climate change has the potential to increase CH4 emissions from critical systems such as wetlands, marine and freshwater systems, permafrost, and methane hydrates, through shifts in temperature, hydrology, vegetation, landscape disturbance, and sea level rise. Increased CH4 emissions from these systems would in turn induce further climate change, resulting in a positive climate feedback. Here we synthesize biological, geochemical, and physically focused CH4 climate feedback literature, bringing together the key findings of these disciplines. We discuss environment-specific feedback processes, including the microbial, physical, and geochemical interlinkages and the timescales on which they operate, and present the current state of knowledge of CH4 climate feedbacks in the immediate and distant future. The important linkages between microbial activity and climate warming are discussed with the aim to better constrain the sensitivity of the CH4 cycle to future climate predictions. We determine that wetlands will form the majority of the CH4 climate feedback up to 2100. Beyond this timescale, CH4 emissions from marine and freshwater systems and permafrost environments could become more important. Significant CH4 emissions to the atmosphere from the dissociation of methane hydrates are not expected in the near future. Our key findings highlight the importance of quantifying whether CH4 consumption can counterbalance CH4 production under future climate scenarios.

  14. ASSESSMENT OF THE VOLUNTEERED GEOGRAPHIC INFORMATION FEEDBACK SYSTEM FOR THE DUTCH TOPOGRAPHICAL KEY REGISTER

    Directory of Open Access Journals (Sweden)

    M. Grus

    2015-08-01

    Full Text Available Since Topographical Key Register has become an open data the amount of users increased enormously. The highest grow was in the private users group. The increasing number of users and their growing demand for high actuality of the topographic data sets motivates the Dutch Kadaster to innovate and improve the Topographical Key Register (BRT. One of the initiatives was to provide a voluntary geographical information project aiming at providing a user-friendly feedback system adjusted to all kinds of user groups. The feedback system is a compulsory element of the Topographical Key Register in the Netherlands. The Dutch Kadaster is obliged to deliver a feedback system and the key-users are obliged to use it. The aim of the feedback system is to improve the quality and stimulate the usage of the data. The results of the pilot shows that the user-friendly and open to everyone feedback system contributes enormously to improve the quality of the topographic dataset.

  15. Practice of knowledge management for institutes--take the construction of experience feedback system as the example

    International Nuclear Information System (INIS)

    Wu Kaiping

    2014-01-01

    The construction of experience feedback system is an important part and breakthrough point of institutes' knowledge management. It is significant for institutes' design, management, development and innovation. This article introduces the concept of experience feedback for institutes. It also goes details of the content of experience feedback system construction for institutes, including the founding of experience feedback organizational mechanism, the development of experience feedback system, construction of knowledge database system, the construction of knowledge resources, and the appraisal of experience feedback's performance. Furthermore, the recognition and support of leaders, understanding and cooperation of relative departments, and corporation's culture of encouraging knowledge sharing, also are the important guarantees for the good effects of institutes' experience feedback work. (author)

  16. Dynamics of a neural system with a multiscale architecture

    Science.gov (United States)

    Breakspear, Michael; Stam, Cornelis J

    2005-01-01

    The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

  17. Artificial Neural Network for Location Estimation in Wireless Communication Systems

    Directory of Open Access Journals (Sweden)

    Chien-Sheng Chen

    2012-03-01

    Full Text Available In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS. To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA measurements and the angle of arrival (AOA information to locate MS when three base stations (BSs are available. Artificial neural networks (ANN are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line, based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  18. Artificial neural network for location estimation in wireless communication systems.

    Science.gov (United States)

    Chen, Chien-Sheng

    2012-01-01

    In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  19. Semi-empirical neural network models of controlled dynamical systems

    Directory of Open Access Journals (Sweden)

    Mihail V. Egorchev

    2017-12-01

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

  20. Stochastic resonance in a bistable system subject to multi-time-delayed feedback and aperiodic signal

    International Nuclear Information System (INIS)

    Li Jianlong; Zeng Lingzao

    2010-01-01

    We discuss in detail the effects of the multi-time-delayed feedback driven by an aperiodic signal on the output of a stochastic resonance (SR) system. The effective potential function and dynamical probability density function (PDF) are derived. To measure the performance of the SR system in the presence of a binary random signal, the bit error rate (BER) defined by the dynamical PDF is employed, as is commonly used in digital communications. We find that the delay time, strength of the feedback, and number of time-delayed terms can change the effective potential function and the effective amplitude of the signal, and then affect the BER of the SR system. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the multi-time-delayed feedback on SR and give a guidance to nonlinear systems in the application of information processing.

  1. Event-Triggered Output-Feedback Control for Disturbed Linear Systems

    Directory of Open Access Journals (Sweden)

    Hao Jiang

    2018-01-01

    Full Text Available In the last few decades, event-triggered control received considerable attention, because of advantages in reducing the resource utilization, such as communication load and processor. In this paper, we propose an event-triggered output-feedback controller for disturbed linear systems, in order to achieve both better resource utilization and disturbance attenuation properties at the same time. Based on our prior work on state-feedback H∞ control for disturbed systems, we propose an approach to design an output-feedback H∞ controller for the system whose states are not completely observable, and a sufficient condition guaranteeing the asymptotic stability and robustness of the system is given in the form of LMIs (Linear Matrix Inequalities.

  2. Development of an accident diagnosis system using a dynamic neural network for nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Seung Jun; Kim, Jong Hyun; Seong, Poong Hyun

    2004-01-01

    In this work, an accident diagnosis system using the dynamic neural network is developed. In order to help the plant operators to quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support system and accident diagnosis systems have been developed. Neural networks have been recognized as a good method to implement an accident diagnosis system. However, conventional accident diagnosis systems that used neural networks did not consider a time factor sufficiently. If the neural network could be trained according to time, it is possible to perform more efficient and detailed accidents analysis. Therefore, this work suggests a dynamic neural network which has different features from existing dynamic neural networks. And a simple accident diagnosis system is implemented in order to validate the dynamic neural network. After training of the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performances

  3. An active feedback system to control synchrotron oscillations in the SLC Damping Rings

    International Nuclear Information System (INIS)

    Corredoura, P.L.; Pellegrin, J.L.; Schwarz, H.D.; Sheppard, J.C.

    1989-03-01

    Initially the SLC Damping Rings accomplished Robinson instability damping by operating the RF accelerating cavities slightly detuned. In order to be able to run the cavities tuned and achieve damping for Robinson instability and synchrotron oscillations at injection an active feedback system has been developed. This paper describes the theoretical basis for the feedback system and the development of the hardware. Extensive measurements of the loop response including stored beam were performed. Overall performance of the system is also reported. 3 refs., 6 figs

  4. Robust output feedback H-infinity control and filtering for uncertain linear systems

    CERN Document Server

    Chang, Xiao-Heng

    2014-01-01

    "Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.

  5. Variance decomposition shows the importance of human-climate feedbacks in the Earth system

    Science.gov (United States)

    Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.

    2017-12-01

    The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.

  6. Control system of hexacopter using color histogram footprint and convolutional neural network

    Science.gov (United States)

    Ruliputra, R. N.; Darma, S.

    2017-07-01

    The development of unmanned aerial vehicles (UAV) has been growing rapidly in recent years. The use of logic thinking which is implemented into the program algorithms is needed to make a smart system. By using visual input from a camera, UAV is able to fly autonomously by detecting a target. However, some weaknesses arose as usage in the outdoor environment might change the target's color intensity. Color histogram footprint overcomes the problem because it divides color intensity into separate bins that make the detection tolerant to the slight change of color intensity. Template matching compare its detection result with a template of the reference image to determine the target position and use it to position the vehicle in the middle of the target with visual feedback control based on Proportional-Integral-Derivative (PID) controller. Color histogram footprint method localizes the target by calculating the back projection of its histogram. It has an average success rate of 77 % from a distance of 1 meter. It can position itself in the middle of the target by using visual feedback control with an average positioning time of 73 seconds. After the hexacopter is in the middle of the target, Convolutional Neural Networks (CNN) classifies a number contained in the target image to determine a task depending on the classified number, either landing, yawing, or return to launch. The recognition result shows an optimum success rate of 99.2 %.

  7. Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs.

    Science.gov (United States)

    Andrews, Steven S; Peria, William J; Yu, Richard C; Colman-Lerner, Alejandro; Brent, Roger

    2016-11-23

    Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Investigation of control system of traction electric drive with feedbacks on load

    Science.gov (United States)

    Kuznetsov, N. K.; Iov, I. A.; Iov, A. A.

    2018-03-01

    In the article, by the example of a walking excavator, the results of a study of a control system of traction electric drive with a rigid and flexible feedback on the load are mentioned. Based on the analysis of known works, the calculation scheme has been chosen; the equations of motion of the electromechanical system have been obtained, taking into account the elasticity of the rope and feedbacks on the load in the elastic element. A simulation model of this system has been developed and mathematical modeling of the transient processes to evaluate the influence of feedback on the dynamic characteristics of the mechanism and its efficiency of work was carried out. It is shown that the use of rigid and flexible feedbacks makes it possible to reduce dynamic loads in the traction mechanism and to limit the elastic oscillation of the executive mechanism in transient operating modes in comparison with the standard control system; however, there is some decrease in productivity. It has been also established that the sign-variable of the loading of the electric drive, connected with the opening of the backlashes in the gearbox due to the action of feedbacks on the load in the elastic element, under certain conditions, can lead to undesirable phenomena in the operation of the drive and a decrease in the reliability of its operation.

  9. Evaluation of State-of-the-Art Acoustic Feedback Cancellation Systems for Hearing Aids

    DEFF Research Database (Denmark)

    Guo, Meng; Jensen, Søren Holdt; Jensen, Jesper

    2013-01-01

    This research evaluates four state-of-the-art acoustic feedback cancellation systems in hearing aids in terms of the cancellation performance, sound quality degradation, and computational complexity. The authors compared a traditional full-band system to a system with a prediction error method...... in a full band, a subband system, a subband system with frequency shifting, and a recently proposed subband system with a novel probe noise deployment. All systems outperformed the traditional full-band system in cancellation performance, especially the subband system with probe noise is most effective...... for cancellation. However, in all cases there was a trade-off between performance and computational cost. With a 3-times increase in computation load, the probe noise based cancellation system can be realized that functions even in the most challenging feedback situation....

  10. Terrestrial biogeochemical feedbacks in the climate system: from past to future

    Energy Technology Data Exchange (ETDEWEB)

    Arneth, A.; Harrison, S. P.; Zaehle, S.; Tsigaridis, K; Menon, S; Bartlein, P.J.; Feichter, J; Korhola, A; Kulmala, M; O' Donnell, D; Schurgers, G; Sorvari, S; Vesala, T

    2010-01-05

    The terrestrial biosphere plays a major role in the regulation of atmospheric composition, and hence climate, through multiple interlinked biogeochemical cycles (BGC). Ice-core and other palaeoenvironmental records show a fast response of vegetation cover and exchanges with the atmosphere to past climate change, although the phasing of these responses reflects spatial patterning and complex interactions between individual biospheric feedbacks. Modern observations show a similar responsiveness of terrestrial biogeochemical cycles to anthropogenically-forced climate changes and air pollution, with equally complex feedbacks. For future conditions, although carbon cycle-climate interactions have been a major focus, other BGC feedbacks could be as important in modulating climate changes. The additional radiative forcing from terrestrial BGC feedbacks other than those conventionally attributed to the carbon cycle is in the range of 0.6 to 1.6 Wm{sup -2}; all taken together we estimate a possible maximum of around 3 Wm{sup -2} towards the end of the 21st century. There are large uncertainties associated with these estimates but, given that the majority of BGC feedbacks result in a positive forcing because of the fundamental link between metabolic stimulation and increasing temperature, improved quantification of these feedbacks and their incorporation in earth system models is necessary in order to develop coherent plans to manage ecosystems for climate mitigation.

  11. Mean Velocity Prediction Information Feedback Strategy in Two-Route Systems under ATIS

    Directory of Open Access Journals (Sweden)

    Jianqiang Wang

    2015-02-01

    Full Text Available Feedback contents of previous information feedback strategies in advanced traveler information systems are almost real-time traffic information. Compared with real-time information, prediction traffic information obtained by a reliable and effective prediction algorithm has many undisputable advantages. In prediction information environment, a traveler is prone to making a more rational route-choice. For these considerations, a mean velocity prediction information feedback strategy (MVPFS is presented. The approach adopts the autoregressive-integrated moving average model (ARIMA to forecast short-term traffic flow. Furthermore, prediction results of mean velocity are taken as feedback contents and displayed on a variable message sign to guide travelers' route-choice. Meanwhile, discrete choice model (Logit model is selected to imitate more appropriately travelers' route-choice behavior. In order to investigate the performance of MVPFS, a cellular automaton model with ARIMA is adopted to simulate a two-route scenario. The simulation shows that such innovative prediction feedback strategy is feasible and efficient. Even more importantly, this study demonstrates the excellence of prediction feedback ideology.

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

    CERN Document Server

    Liu, Jinkun

    2013-01-01

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

  13. Feedback linearization based control of a variable air volume air conditioning system for cooling applications.

    Science.gov (United States)

    Thosar, Archana; Patra, Amit; Bhattacharyya, Souvik

    2008-07-01

    Design of a nonlinear control system for a Variable Air Volume Air Conditioning (VAVAC) plant through feedback linearization is presented in this article. VAVAC systems attempt to reduce building energy consumption while maintaining the primary role of air conditioning. The temperature of the space is maintained at a constant level by establishing a balance between the cooling load generated in the space and the air supply delivered to meet the load. The dynamic model of a VAVAC plant is derived and formulated as a MIMO bilinear system. Feedback linearization is applied for decoupling and linearization of the nonlinear model. Simulation results for a laboratory scale plant are presented to demonstrate the potential of keeping comfort and maintaining energy optimal performance by this methodology. Results obtained with a conventional PI controller and a feedback linearizing controller are compared and the superiority of the proposed approach is clearly established.

  14. Develop feedback system for intelligent dynamic resource allocation to improve application performance.

    Energy Technology Data Exchange (ETDEWEB)

    Gentile, Ann C.; Brandt, James M.; Tucker, Thomas (Open Grid Computing, Inc., Austin, TX); Thompson, David

    2011-09-01

    This report provides documentation for the completion of the Sandia Level II milestone 'Develop feedback system for intelligent dynamic resource allocation to improve application performance'. This milestone demonstrates the use of a scalable data collection analysis and feedback system that enables insight into how an application is utilizing the hardware resources of a high performance computing (HPC) platform in a lightweight fashion. Further we demonstrate utilizing the same mechanisms used for transporting data for remote analysis and visualization to provide low latency run-time feedback to applications. The ultimate goal of this body of work is performance optimization in the face of the ever increasing size and complexity of HPC systems.

  15. Down sampled signal processing for a B Factory bunch-by-bunch feedback system

    International Nuclear Information System (INIS)

    Hindi, H.; Hosseini, W.; Briggs, D.; Fox, J.; Hutton, A.

    1992-03-01

    A bunch-by-bunch feedback scheme is studied for damping coupled bunch synchrotron oscillations in the proposed PEP II B Factory. The quasi-linear feedback systems design incorporates a phase detector to provide a quantized measure of bunch phase, digital signal processing to compute an error correction signal and a kicker system to correct the energy of the bunches. A farm of digital processors, operating in parallel, is proposed to compute correction signals for the 1658 bunches of the B Factory. This paper studies the use of down sampled processing to reduce the computational complexity of the feedback system. We present simulation results showing the effect of down sampling on beam dynamics. Results show that down sampled processing can reduce the scale of the processing task by a factor of 10

  16. Simulations of the TESLA Linear Collider with a Fast Feedback System

    CERN Document Server

    Schulte, Daniel; White, G

    2003-01-01

    The tolerances on the beams as they collide at the interaction point of the TESLA linear collider are very tight due to the nano-metre scale final vertical bunch spot sizes. Ground motion causes the beams to increase in emittance and drift out of collision leading to dramatic degradation of luminosity performance. To combat this, both slow orbit and fast intra-train feedback systems will be used. The design of these feedback systems depends critically on how component misalignment effects the beam throughout the whole accelerator. A simulation has been set up to study in detail the accelerator performance under such conditions by merging the codes of PLACET, MERLIN and GUINEA-PIG together with Simulink code to model feedback systems, all under a Matlab environment.

  17. Approaching system equilibrium with accurate or not accurate feedback information in a two-route system

    Science.gov (United States)

    Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi

    2015-02-01

    With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.

  18. Theory and Applications of Discontinuous State Feedback Generating Chaos for Linear Systems

    International Nuclear Information System (INIS)

    Xiao-Dan, Zhang; Zhen, Wang; Pin-Dong, Zhao

    2008-01-01

    We investigate a kind of chaos generating technique on a type of n-dimensional linear differential systems by adding feedback control items under a discontinuous state. This method is checked with some examples of numeric simulation. A constructive theorem is proposed for generalized synchronization related to the above chaotic system

  19. Design considerations for a feedback system to control self-bunching in ion-storage rings

    International Nuclear Information System (INIS)

    Ziemann, V.

    2001-02-01

    We discuss the feasibility of a feedback system to cure self-bunching of the electron-cooled coasting ion-beam in CELSIUS. Such a system may also aid stable operation of accumulator rings for future spallation neutron sources or heavy ion rings used for inertial fusion energy production

  20. Stability investigations of the ASDEX feedback system with filters for reducing thyristor noise

    International Nuclear Information System (INIS)

    Crisanti, F.; Schneider, F.

    1983-06-01

    A computer program for analysing the absolute and relative stabilities of any complex system by the root-locus method was developed. It is used to reanalyse the present horizontal position feed-back control in the ASDEX tokamak and to select the optimum parameters for this system with RCL filters for reducing thyristor noise. (orig.)

  1. Nonlinear feedback synchronisation control between fractional-order and integer-order chaotic systems

    International Nuclear Information System (INIS)

    Jia Li-Xin; Dai Hao; Hui Meng

    2010-01-01

    This paper focuses on the synchronisation between fractional-order and integer-order chaotic systems. Based on Lyapunov stability theory and numerical differentiation, a nonlinear feedback controller is obtained to achieve the synchronisation between fractional-order and integer-order chaotic systems. Numerical simulation results are presented to illustrate the effectiveness of this method

  2. Neural Computations in a Dynamical System with Multiple Time Scales

    Directory of Open Access Journals (Sweden)

    Yuanyuan Mi

    2016-09-01

    Full Text Available Neural systems display rich short-term dynamics at various levels, e.g., spike-frequencyadaptation (SFA at single neurons, and short-term facilitation (STF and depression (STDat neuronal synapses. These dynamical features typically covers a broad range of time scalesand exhibit large diversity in different brain regions. It remains unclear what the computationalbenefit for the brain to have such variability in short-term dynamics is. In this study, we proposethat the brain can exploit such dynamical features to implement multiple seemingly contradictorycomputations in a single neural circuit. To demonstrate this idea, we use continuous attractorneural network (CANN as a working model and include STF, SFA and STD with increasing timeconstants in their dynamics. Three computational tasks are considered, which are persistent activity,adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, andhence cannot be implemented by a single dynamical feature or any combination with similar timeconstants. However, with properly coordinated STF, SFA and STD, we show that the network isable to implement the three computational tasks concurrently. We hope this study will shed lighton the understanding of how the brain orchestrates its rich dynamics at various levels to realizediverse cognitive functions.

  3. Neural network application to aircraft control system design

    Science.gov (United States)

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

    1991-01-01

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

  4. Neural network application to aircraft control system design

    Science.gov (United States)

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

    1991-01-01

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

  5. Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder.

    Science.gov (United States)

    Wittenborn, A K; Rahmandad, H; Rick, J; Hosseinichimeh, N

    2016-02-01

    Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics. We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder. The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression. Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention.

  6. The Vibe of Skating; Design and Testing of a Vibro-Tactile Feedback System

    Directory of Open Access Journals (Sweden)

    Arjen J. Jansen

    2018-03-01

    Full Text Available Providing athletes with real-time feedback on their performance is becoming common in many sports, also in speed skating. This research-by-design project aims at finding a tool that allows the speed skater to get real-time feedback on his performance. Speed skaters often mention a so-called “good feeling” when skating behind a better skater. It is the feeling nearly every speed skater is after when skating alone; skate with less power while maintaining the same speed and feeling of ease. A longer push-off phase at a constant cadence has proven to contribute to this ideal situation but is hard for the coach alone to influence this. Therefore, a system was designed that measures the skating cadence and challenges the skater to change his skating stroke by means of vibro-tactile feedback. Four subjects have tested the feedback system. From this test, we concluded that the system provides meaningful feedback towards changing the skating cycle.

  7. Neural Network Based Intrusion Detection System for Critical Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Ondrej Linda; Milos Manic

    2009-07-01

    Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

  8. Neural Network Target Identification System for False Alarm Reduction

    Science.gov (United States)

    Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

    2009-01-01

    A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

  9. Olfactory systems and neural circuits that modulate predator odor fear

    Directory of Open Access Journals (Sweden)

    Lorey K. Takahashi

    2014-03-01

    Full Text Available When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS and accessory olfactory systems (AOS detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray, paraventricular nucleus of the hypothalamus, and the medial amygdala appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal stress hormone secretion. The medial amygdala also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus appear prominently involve in predator odor fear behavior. The basolateral amygdala, medial hypothalamic nuclei, and medial prefrontal cortex are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator odors activate

  10. Olfactory systems and neural circuits that modulate predator odor fear

    Science.gov (United States)

    Takahashi, Lorey K.

    2014-01-01

    When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS) and accessory olfactory systems (AOS) detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray (DPAG), paraventricular nucleus (PVN) of the hypothalamus, and the medial amygdala (MeA) appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal (HPA) stress hormone secretion. The MeA also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus (VHC) appear prominently involved in predator odor fear behavior. The basolateral amygdala (BLA), medial hypothalamic nuclei, and medial prefrontal cortex (mPFC) are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator

  11. Comparison of Multiple-Microphone and Single-Loudspeaker Adaptive Feedback/Echo Cancellation Systems

    DEFF Research Database (Denmark)

    Guo, Meng; Elmedyb, Thomas Bo; Jensen, Søren Holdt

    2011-01-01

    Recently, we introduced a frequency domain measure - the power transfer function - to predict the convergence rate, system stability bound and the steady-state behavior across time and frequency of a least mean square based feedback/echo cancellation algorithm in a general multiple-microphone and......Recently, we introduced a frequency domain measure - the power transfer function - to predict the convergence rate, system stability bound and the steady-state behavior across time and frequency of a least mean square based feedback/echo cancellation algorithm in a general multiple...

  12. Evaluation of the global orbit correction algorithm for the APS real-time orbit feedback system

    International Nuclear Information System (INIS)

    Carwardine, J.; Evans, K. Jr.

    1997-01-01

    The APS real-time orbit feedback system uses 38 correctors per plane and has available up to 320 rf beam position monitors. Orbit correction is implemented using multiple digital signal processors. Singular value decomposition is used to generate a correction matrix from a linear response matrix model of the storage ring lattice. This paper evaluates the performance of the APS system in terms of its ability to correct localized and distributed sources of orbit motion. The impact of regulator gain and bandwidth, choice of beam position monitors, and corrector dynamics are discussed. The weighted least-squares algorithm is reviewed in the context of local feedback

  13. Exponential synchronization of the Genesio-Tesi chaotic system via a novel feedback control

    International Nuclear Information System (INIS)

    Park, Ju H

    2007-01-01

    A novel feedback control scheme is proposed for exponential synchronization of the Genesio-Tesi chaotic system. The feedback controller consists of two parts: a linear dynamic control law and a nonlinear control one. For exponential synchronization between the drive and response Genesio-Tesi systems, the Lyapunov stability analysis is used. Then an existence criterion for the stabilizing controller is presented in terms of linear matrix inequalities (LMIs). The LMIs can be solved easily by various convex optimization algorithms. Finally, a numerical simulation is illustrated to show the effectiveness of the proposed chaos synchronization scheme

  14. Bunch-by-bunch longitudinal feedback system for PEP-II

    International Nuclear Information System (INIS)

    Oxoby, G.; Claus, R.; Fox, J.

    1994-06-01

    This paper describes the implementation of the bunch-by-bunch longitudinal feedback system for the PEP-II B Factory. Bunch spacing down to 2 ns is achieved using 500 Megasamples per second A/D and D/A converters, and AT ampersand T 1610 Digital Signal Processors are integrated to run a downsampled feedback algorithm for each bunch in parallel. This general purpose programmable system, packaged in VXI and VME, is modular and scalable to offer portability to other accelerator rings. The control and monitoring hardware and software architecture have been developed to provide ease of operation as well as diagnostic tools for machine physics

  15. An Artificial Immune System with Feedback Mechanisms for Effective Handling of Population Size

    Science.gov (United States)

    Gao, Shangce; Wang, Rong-Long; Ishii, Masahiro; Tang, Zheng

    This paper represents a feedback artificial immune system (FAIS). Inspired by the feedback mechanisms in the biological immune system, the proposed algorithm effectively manipulates the population size by increasing and decreasing B cells according to the diversity of the current population. Two kinds of assessments are used to evaluate the diversity aiming to capture the characteristics of the problem on hand. Furthermore, the processing of adding and declining the number of population is designed. The validity of the proposed algorithm is tested for several traveling salesman benchmark problems. Simulation results demonstrate the efficiency of the proposed algorithm when compared with the traditional genetic algorithm and an improved clonal selection algorithm.

  16. Equilibrium of a two-route system with delayed information feedback strategies

    International Nuclear Information System (INIS)

    Zhao, Xiao-mei; Xie, Dong-fan; Gao, Zi-you; Gao, Liang

    2013-01-01

    In intelligent transport system, some advanced information feedback strategies have been developed to reduce the oscillations and enhance the capacity on the road level. However, seldom strategies have considered the information delay and user equilibrium (UE) objective. Here, a derivative cost feedback strategy (DCFS) is proposed to reduce the influence of the delay, based on the UE principle. The simulation results show that in both no-delay and delay information cases, DCFS are the best and can make the system reaching the UE. Because DCFS can predict the trend of the travel cost.

  17. Equilibrium of a two-route system with delayed information feedback strategies

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xiao-mei, E-mail: xmzhao@bjtu.edu.cn [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China); Xie, Dong-fan, E-mail: dfxie@bjtu.edu.cn [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China); Gao, Zi-you, E-mail: zygao@bjtu.edu.cn [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China); Gao, Liang, E-mail: lianggao@bjtu.edu.cn [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China)

    2013-12-09

    In intelligent transport system, some advanced information feedback strategies have been developed to reduce the oscillations and enhance the capacity on the road level. However, seldom strategies have considered the information delay and user equilibrium (UE) objective. Here, a derivative cost feedback strategy (DCFS) is proposed to reduce the influence of the delay, based on the UE principle. The simulation results show that in both no-delay and delay information cases, DCFS are the best and can make the system reaching the UE. Because DCFS can predict the trend of the travel cost.

  18. Factorization and the synthesis of optimal feedback gains for distributed parameter systems

    Science.gov (United States)

    Milman, Mark H.; Scheid, Robert E.

    1990-01-01

    An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.

  19. General, database-driven fast-feedback system for the Stanford Linear Collider

    International Nuclear Information System (INIS)

    Rouse, F.; Allison, S.; Castillo, S.; Gromme, T.; Hall, B.; Hendrickson, L.; Himel, T.; Krauter, K.; Sass, B.; Shoaee, H.

    1991-05-01

    A new feedback system has been developed for stabilizing the SLC beams at many locations. The feedback loops are designed to sample and correct at the 60 Hz repetition rate of the accelerator. Each loop can be distributed across several of the standard 80386 microprocessors which control the SLC hardware. A new communications system, KISNet, has been implemented to pass signals between the microprocessors at this rate. The software is written in a general fashion using the state space formalism of digital control theory. This allows a new loop to be implemented by just setting up the online database and perhaps installing a communications link. 3 refs., 4 figs

  20. Finite-time output feedback stabilization of high-order uncertain nonlinear systems

    Science.gov (United States)

    Jiang, Meng-Meng; Xie, Xue-Jun; Zhang, Kemei

    2018-06-01

    This paper studies the problem of finite-time output feedback stabilization for a class of high-order nonlinear systems with the unknown output function and control coefficients. Under the weaker assumption that output function is only continuous, by using homogeneous domination method together with adding a power integrator method, introducing a new analysis method, the maximal open sector Ω of output function is given. As long as output function belongs to any closed sector included in Ω, an output feedback controller can be developed to guarantee global finite-time stability of the closed-loop system.

  1. A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

    Science.gov (United States)

    Samarasinghe, S; Ling, H

    In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced

  2. System identification of an unmanned quadcopter system using MRAN neural

    Science.gov (United States)

    Pairan, M. F.; Shamsudin, S. S.

    2017-12-01

    This project presents the performance analysis of the radial basis function neural network (RBF) trained with Minimal Resource Allocating Network (MRAN) algorithm for real-time identification of quadcopter. MRAN’s performance is compared with the RBF with Constant Trace algorithm for 2500 input-output pair data sampling. MRAN utilizes adding and pruning hidden neuron strategy to obtain optimum RBF structure, increase prediction accuracy and reduce training time. The results indicate that MRAN algorithm produces fast training time and more accurate prediction compared with standard RBF. The model proposed in this paper is capable of identifying and modelling a nonlinear representation of the quadcopter flight dynamics.

  3. To Stabilize Power Systems from Various Kind of Oscillations using a State Feedback Controller

    International Nuclear Information System (INIS)

    Afridi, M. A.

    2012-01-01

    Damping of electromechanical oscillations in power systems is one of the major concerns in the operation of power system since many years. These oscillations cause improper of the power system incorporating losses. This thesis work presents the coordinated AVR+PSS structure, called the Desensitized four loops Regulator, designed to damp these oscillations in the power system. It is shown here that it is possible to transform the structure of this controller into any standard IEEE AVR+PSS structure. The AVR+PSS structure obtained through this structure is efficient to damp out many types of oscillations present in the Power system. These models are to be incorporated with the generator models to get a power system model with state feedback control. On simulating the system in Simulink with the controllers we have obtained the power system model with state feedback control and observed that how these controllers are helpful in damping the oscillations. (author)

  4. Systematic design and simulation of a tearing mode suppression feedback control system for the TEXTOR tokamak

    International Nuclear Information System (INIS)

    Hennen, B.A.; Westerhof, E.; De Baar, M.R.; Nuij, P.W.J.M.; Steinbuch, M.

    2012-01-01

    Suppression of tearing modes is essential for the operation of tokamaks. This paper describes the design and simulation of a tearing mode suppression feedback control system for the TEXTOR tokamak. The two main control tasks of this feedback control system are the radial alignment of electron cyclotron resonance heating and current drive (ECRH/ECCD) with a tearing mode and the stabilization of a mode at a specific width. In order to simulate these control tasks, the time evolution of a tearing mode subject to suppression by ECRH/ECCD and destabilization by a magnetic perturbation field is modelled using the generalized Rutherford equation. The model includes an equilibrium model and an ECRH/ECCD launcher model. The dynamics and static equilibria of this model are analysed. The model is linearized and based on the linearized model, linear feedback controllers are designed and simulated, demonstrating both alignment and width control of tearing modes in TEXTOR. (paper)

  5. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1991-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such ''virtual measurements'' the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up or performance can be determined. In the methodology presented the output of a virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control valve of an experimental reactor using data obtained during a start-up. The enhanced noise tolerance of the methodology is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems. 8 refs., 11 figs., 1 tab

  6. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1992-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such virtual measurements the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up-or performance can be determined. In the methodology presented the output of virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems

  7. Fast digital transverse feedback system for bunch train operation in CESR

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, J T; Billing, M G; Dobbins, J A [Cornell Univ., Ithaca, NY (United States). Lab. of Nuclear Studies; and others

    1996-08-01

    We have developed a time domain transverse feedback system with the high bandwidth needed to control transverse instabilities when the CESR e{sup +}e{sup -} collider is filled with trains of closely spaced bunches. This system is based on parallel digital processors and a stripline driver. It is capable of acting on arbitrary patterns of bunches having a minimum spacing of 14 ns. Several simplifying features have been introduced. A single shorted stripline kicker driven by one power amplifier is used to control both counter-rotating beams. The desired feedback phase is achieved by sampling the bunch position at a single location on two independently selectable beam revolutions. The system adapts to changes in the betatron tune, bunch pattern, or desired damping rate through the loading of new parameters into the digital processors via the CESR control system. The feedback system also functions as a fast gated bunch current monitor. Both vertical and horizontal loops are now used in CESR operation. The measured betatron damping rates with the transverse feedback system in operation are in agreement with the analytical prediction and a computer simulation developed in connection with this work. (author)

  8. Instruction, Feedback and Biometrics: The User Interface for Fingerprint Authentication Systems

    Science.gov (United States)

    Riley, Chris; Johnson, Graham; McCracken, Heather; Al-Saffar, Ahmed

    Biometric authentication is the process of establishing an individual’s identity through measurable characteristics of their behaviour, anatomy or physiology. Biometric technologies, such as fingerprint systems, are increasingly being used in a diverse range of contexts from immigration control, to banking and personal computing. As is often the case with emerging technologies, the usability aspects of system design have received less attention than technical aspects. Fingerprint systems pose a number of challenges for users and past research has identified issues with correct finger placement, system feedback and instruction. This paper describes the development of an interface for fingerprint systems using an iterative, participative design approach. During this process, several different methods for the presentation of instruction and feedback were identified. The different types of instruction and feedback were tested in a study involving 82 participants. The results showed that feedback had a statistically significant effect on overall system performance, but instruction did not. The design recommendations emerging from this study, and the use of participatory design in this context, are discussed.

  9. Fast digital transverse feedback system for bunch train operation in CESR

    International Nuclear Information System (INIS)

    Rogers, J.T.; Billing, M.G.; Dobbins, J.A.

    1996-01-01

    We have developed a time domain transverse feedback system with the high bandwidth needed to control transverse instabilities when the CESR e + e - collider is filled with trains of closely spaced bunches. This system is based on parallel digital processors and a stripline driver. It is capable of acting on arbitrary patterns of bunches having a minimum spacing of 14 ns. Several simplifying features have been introduced. A single shorted stripline kicker driven by one power amplifier is used to control both counter-rotating beams. The desired feedback phase is achieved by sampling the bunch position at a single location on two independently selectable beam revolutions. The system adapts to changes in the betatron tune, bunch pattern, or desired damping rate through the loading of new parameters into the digital processors via the CESR control system. The feedback system also functions as a fast gated bunch current monitor. Both vertical and horizontal loops are now used in CESR operation. The measured betatron damping rates with the transverse feedback system in operation are in agreement with the analytical prediction and a computer simulation developed in connection with this work. (author)

  10. Consistency properties of chaotic systems driven by time-delayed feedback

    Science.gov (United States)

    Jüngling, T.; Soriano, M. C.; Oliver, N.; Porte, X.; Fischer, I.

    2018-04-01

    Consistency refers to the property of an externally driven dynamical system to respond in similar ways to similar inputs. In a delay system, the delayed feedback can be considered as an external drive to the undelayed subsystem. We analyze the degree of consistency in a generic chaotic system with delayed feedback by means of the auxiliary system approach. In this scheme an identical copy of the nonlinear node is driven by exactly the same signal as the original, allowing us to verify complete consistency via complete synchronization. In the past, the phenomenon of synchronization in delay-coupled chaotic systems has been widely studied using correlation functions. Here, we analytically derive relationships between characteristic signatures of the correlation functions in such systems and unequivocally relate them to the degree of consistency. The analytical framework is illustrated and supported by numerical calculations of the logistic map with delayed feedback for different replica configurations. We further apply the formalism to time series from an experiment based on a semiconductor laser with a double fiber-optical feedback loop. The experiment constitutes a high-quality replica scheme for studying consistency of the delay-driven laser and confirms the general theoretical results.

  11. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

    OpenAIRE

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

  12. Mode Selection Rules for a Two-Delay System with Positive and Negative Feedback Loops

    Science.gov (United States)

    Takahashi, Kin'ya; Kobayashi, Taizo

    2018-04-01

    The mode selection rules for a two-delay system, which has negative feedback with a short delay time t1 and positive feedback with a long delay time t2, are studied numerically and theoretically. We find two types of mode selection rules depending on the strength of the negative feedback. When the strength of the negative feedback |α1| (α1 0), 2m + 1-th harmonic oscillation is well sustained in a neighborhood of t1/t2 = even/odd, i.e., relevant condition. In a neighborhood of the irrelevant condition given by t1/t2 = odd/even or t1/t2 = odd/odd, higher harmonic oscillations are observed. However, if |α1| is slightly less than α2, a different mode selection rule works, where the condition t1/t2 = odd/even is relevant and the conditions t1/t2 = odd/odd and t1/t2 = even/odd are irrelevant. These mode selection rules are different from the mode selection rule of the normal two-delay system with two positive feedback loops, where t1/t2 = odd/odd is relevant and the others are irrelevant. The two types of mode selection rules are induced by individually different mechanisms controlling the Hopf bifurcation, i.e., the Hopf bifurcation controlled by the "boosted bifurcation process" and by the "anomalous bifurcation process", which occur for |α1| below and above the threshold value αth, respectively.

  13. Advantages of externally powered prosthesis with feedback system using pseudo-cineplasty.

    Science.gov (United States)

    Nambu, Seiji; Ikebuchi, Mitsuhiko; Taniguchi, Masashi; Park, Choong Sik; Kitagawa, Takahiro; Nakajima, Shigeyoshi; Koike, Tatsuya

    2014-01-01

    Externally powered upper-limb prostheses are difficult to use because of the lack of sensory feedback. Neuroprostheses have recently been developed for people with upper-limb amputation but are complicated, expensive, and still developing. We therefore designed a simple system by combining pseudo-cineplasty with extended physiological proprioception to provide sensory feedback to the body. We penetrated the palmaris longus tendon percutaneously with a metal ring, similar to that used in body piercing, in a nondisabled subject as a pseudo-cineplasty. The tendon and ring were connected to the system, and a sensory feedback experiment was performed. We investigated the ability of the user to determine the size of an object grasped by the prosthetic hand without visual information. The subject could distinguish between large and small objects with 100% accuracy and between small, medium, and large objects with 80% accuracy. In pseudo-cineplasty, control and sensory feedback are natural because the prosthetic hand is controlled by muscle contraction. Tension transmitted from the prosthetic hand is sensed via muscle spindles and skin sensors. This technique allows only partial sensory feedback but appears to offer several advantages over other human-machine interfaces.

  14. Research of a New 6-Dof Force Feedback Hand Controller System

    Directory of Open Access Journals (Sweden)

    Xin Gao

    2014-01-01

    Full Text Available The field of teleoperation with force telepresence has expanded its scope to include manipulation at different scales and in virtual worlds, and the key component of which is force feedback hand controller. This paper presents a novel force feedback hand controller system, including a 3-dof translational and 3-dof rotational hand controllers, respectively, to implement position and posture teleoperation of the robot end effector. The 3-dof translational hand controller adopts innovative three-axes decoupling structure based on the linear motor; the 3-dof rotational hand controller adopts serial mechanism based on three-axes intersecting at one point, improving its overall stiffness. Based on the kinematics, statics, and dynamics analyses for two platforms separately, the system applies big closed-loop force control method based on the zero force/torque, improving the feedback force/torque accuracy effectively. Experimental results show that self-developed 6-dof force feedback hand controller has good mechanical properties. The translational hand controller has the following advantages: simple kinematics solver, fast dynamic response, and better than 0.05 mm accuracy of three-axis end positioning, while the advantages of the rotational hand controller are wide turning space, larger than 1 Nm feedback, greater than 180 degrees of operating space of three axes, respectively, and high operation precision.

  15. Modeling and Control of Collaborative Robot System using Haptic Feedback

    Directory of Open Access Journals (Sweden)

    Vivekananda Shanmuganatha

    2017-08-01

    Full Text Available When two robot systems can share understanding using any agreed knowledge, within the constraints of the system’s communication protocol, the approach may lead to a common improvement. This has persuaded numerous new research inquiries in human-robot collaboration. We have built up a framework prepared to do independent following and performing table-best protest object manipulation with humans and we have actualized two different activity models to trigger robot activities. The idea here is to explore collaborative systems and to build up a plan for them to work in a collaborative environment which has many benefits to a single more complex system. In the paper, two robots that cooperate among themselves are constructed. The participation linking the two robotic arms, the torque required and parameters are analyzed. Thus the purpose of this paper is to demonstrate a modular robot system which can serve as a base on aspects of robotics in collaborative robots using haptics.

  16. Stabilization of Networked Control Systems Under Feedback-based Communication

    National Research Council Canada - National Science Library

    Zhang, Lei; Hristu-Varsakelis, Dimitrios

    2004-01-01

    We study the stabilization of a networked control system (NSC) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller...

  17. Phase transitions in glassy systems via convolutional neural networks

    Science.gov (United States)

    Fang, Chao

    Machine learning is a powerful approach commonplace in industry to tackle large data sets. Most recently, it has found its way into condensed matter physics, allowing for the first time the study of, e.g., topological phase transitions and strongly-correlated electron systems. The study of spin glasses is plagued by finite-size effects due to the long thermalization times needed. Here we use convolutional neural networks in an attempt to detect a phase transition in three-dimensional Ising spin glasses. Our results are compared to traditional approaches.

  18. NEURAL NETWORK SYSTEM FOR DIAGNOSTICS OF AVIATION DESIGNATION PRODUCTS

    Directory of Open Access Journals (Sweden)

    В. Єременко

    2011-02-01

    Full Text Available In the article for solving the classification problem of the technical state of the  object, proposed to use a hybrid neural network with a Kohonen layer and multilayer perceptron. The information-measuring system can be used for standardless diagnostics, cluster analysis and to classify the products which made from composite materials. The advantage of this architecture is flexibility, high performance, ability to use different methods for collecting diagnostic information about unit under test, high reliability of information processing

  19. Fault Tolerant Neural Network for ECG Signal Classification Systems

    Directory of Open Access Journals (Sweden)

    MERAH, M.

    2011-08-01

    Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

  20. Optimizing Markovian modeling of chaotic systems with recurrent neural networks

    International Nuclear Information System (INIS)

    Cechin, Adelmo L.; Pechmann, Denise R.; Oliveira, Luiz P.L. de

    2008-01-01

    In this paper, we propose a methodology for optimizing the modeling of an one-dimensional chaotic time series with a Markov Chain. The model is extracted from a recurrent neural network trained for the attractor reconstructed from the data set. Each state of the obtained Markov Chain is a region of the reconstructed state space where the dynamics is approximated by a specific piecewise linear map, obtained from the network. The Markov Chain represents the dynamics of the time series in its statistical essence. An application to a time series resulted from Lorenz system is included