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Sample records for observer-based robust adaptive

  1. Robust observer-based adaptive fuzzy sliding mode controller

    NASA Astrophysics Data System (ADS)

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

    In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

  2. Reduced-order observer-based robust synchronisation control of cold rolling mills with measurement delay

    NASA Astrophysics Data System (ADS)

    Jiao, Xiaohong; Mei, Zhisong

    2010-10-01

    To improve the quality of strip thickness, synchronisation control is investigated for cold rolling mills driven by dual-cylinder electro-hydraulic servo systems. Realising synchronised control in hydraulic automatic gauge control (HAGC) systems of cold rolling mills has challenges with not only the inherent nonlinearities of hydraulic servo systems and uncertainties of load variation but also measurement delay of strip thickness. Since all states are not measurable in practice, output feedback robust synchronisation control problem should be addressed for uncertain nonlinear systems with output delay. Thus, a reduced-order observer-based robust synchronous controller is presented by employing Lyapunov functional stability theory. The controller designed by incorporating the integral of the position synchronisation error of two pistons into state variables successfully guarantees asymptotic convergence to zero of both tracking errors and synchronisation error simultaneously regardless of the nonlinearities and uncertainties as well as the measurement delay. Simulation results in a model obtained from a real cold strip rolling mill demonstrate the effectiveness of the approach.

  3. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  4. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

    The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.

  5. Adaptive control: Stability, convergence, and robustness

    NASA Technical Reports Server (NTRS)

    Sastry, Shankar; Bodson, Marc

    1989-01-01

    The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.

  6. Robust, Practical Adaptive Control for Launch Vehicles

    NASA Technical Reports Server (NTRS)

    Orr, Jeb. S.; VanZwieten, Tannen S.

    2012-01-01

    A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

  7. Robust adaptive control for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Kahveci, Nazli E.

    anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

  8. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  10. Robust adaptive vibration control of a flexible structure.

    PubMed

    Khoshnood, A M; Moradi, H M

    2014-07-01

    Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system.

  11. Robust adaptive regulation without persistent excitation

    NASA Technical Reports Server (NTRS)

    Lozano-Leal, Rogelio

    1988-01-01

    A globally convergent adaptive regulator for minimum or nonminimum phase systems subject to bounded distrubances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the new representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least Squares identification algorithm with a dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given.

  12. Robust adaptive regulation without persistent excitation

    NASA Technical Reports Server (NTRS)

    Lozano-Leal, Rogelio

    1989-01-01

    A globally convergent adaptive regulator for minimum- or nonminimum-phase systems subject to bounded disturbances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least-Squares identification algorithm a with dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given.

  13. Robust Wiener filtering for Adaptive Optics

    SciTech Connect

    Poyneer, L A

    2004-06-17

    In many applications of optical systems, the observed field in the pupil plane has a non-uniform phase component. This deviation of the phase of the field from uniform is called a phase aberration. In imaging systems this aberration will degrade the quality of the images. In the case of a large astronomical telescope, random fluctuations in the atmosphere lead to significant distortion. These time-varying distortions can be corrected using an Adaptive Optics (AO) system, which is a real-time control system composed of optical, mechanical and computational parts. Adaptive optics is also applicable to problems in vision science, laser propagation and communication. For a high-level overview, consult this web site. For an in-depth treatment of the astronomical case, consult these books.

  14. Robust Adaptive Control In Hilbert Space

    NASA Technical Reports Server (NTRS)

    Wen, John Ting-Yung; Balas, Mark J.

    1990-01-01

    Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.

  15. Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.

    PubMed

    Fei, Juntao; Zhou, Jian

    2012-12-01

    In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.

  16. Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

    PubMed

    Peng, Jinzhu; Yu, Jie; Wang, Jie

    2014-07-01

    In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. PMID:24917071

  17. Robust Adaptive Data Encoding and Restoration

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur; Halyo, Nesim

    2000-01-01

    This is the final report for NASA cooperative agreement and covers the period from 01 October, 1997 to 11 April, 2000. The research during this period was performed in three primary, but related, areas. 1. Evaluation of integrated information adaptive imaging. 2. Improvements in memory utilization and performance of the multiscale retinex with color restoration (MSRCR). 3. Commencement of a theoretical study to evaluate the non-linear retinex image enhancement technique. The research resulted in several publications, and an intellectual property disclosure to the NASA patent council in May, 1999.

  18. Adaptive robust control of the EBR-II reactor

    SciTech Connect

    Power, M.A.; Edwards, R.M.

    1996-05-01

    Simulation results are presented for an adaptive H{sub {infinity}} controller, a fixed H{sub {infinity}} controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H{sub {infinity}} controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H{sub {infinity}} and classical controllers. This makes for a superior and more robust controller.

  19. Robust design of configurations and parameters of adaptable products

    NASA Astrophysics Data System (ADS)

    Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua

    2014-03-01

    An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

  20. Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

    PubMed

    Tong, Shaocheng; Sui, Shuai; Li, Yongming

    2015-12-01

    In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

  1. Robust time and frequency domain estimation methods in adaptive control

    NASA Technical Reports Server (NTRS)

    Lamaire, Richard Orville

    1987-01-01

    A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

  2. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system. PMID:24808035

  3. Robust local search for spacecraft operations using adaptive noise

    NASA Technical Reports Server (NTRS)

    Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

    2004-01-01

    Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

  4. Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

    PubMed Central

    Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

    2016-01-01

    Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

  5. Robust adaptive dynamic programming with an application to power systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2013-07-01

    This brief presents a novel framework of robust adaptive dynamic programming (robust-ADP) aimed at computing globally stabilizing and suboptimal control policies in the presence of dynamic uncertainties. A key strategy is to integrate ADP theory with techniques in modern nonlinear control with a unique objective of filling up a gap in the past literature of ADP without taking into account dynamic uncertainties. Neither the system dynamics nor the system order are required to be precisely known. As an illustrative example, the computational algorithm is applied to the controller design of a two-machine power system. PMID:24808528

  6. Robust control of a bimorph mirror for adaptive optics systems.

    PubMed

    Baudouin, Lucie; Prieur, Christophe; Guignard, Fabien; Arzelier, Denis

    2008-07-10

    We apply robust control techniques to an adaptive optics system including a dynamic model of the deformable mirror. The dynamic model of the mirror is a modification of the usual plate equation. We propose also a state-space approach to model the turbulent phase. A continuous time control of our model is suggested, taking into account the frequential behavior of the turbulent phase. An H(infinity) controller is designed in an infinite-dimensional setting. Because of the multivariable nature of the control problem involved in adaptive optics systems, a significant improvement is obtained with respect to traditional single input-single output methods.

  7. Variable Neural Adaptive Robust Control: A Switched System Approach

    SciTech Connect

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  8. Decentralized adaptive control of robot manipulators with robust stabilization design

    NASA Technical Reports Server (NTRS)

    Yuan, Bau-San; Book, Wayne J.

    1988-01-01

    Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

  9. How MAP kinase modules function as robust, yet adaptable, circuits

    PubMed Central

    Tian, Tianhai; Harding, Angus

    2014-01-01

    Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution. PMID:25483189

  10. An adaptive robust controller for time delay maglev transportation systems

    NASA Astrophysics Data System (ADS)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  11. How protein materials balance strength, robustness, and adaptability

    PubMed Central

    Buehler, Markus J.; Yung, Yu Ching

    2010-01-01

    Proteins form the basis of a wide range of biological materials such as hair, skin, bone, spider silk, or cells, which play an important role in providing key functions to biological systems. The focus of this article is to discuss how protein materials are capable of balancing multiple, seemingly incompatible properties such as strength, robustness, and adaptability. To illustrate this, we review bottom-up materiomics studies focused on the mechanical behavior of protein materials at multiple scales, from nano to macro. We focus on alpha-helix based intermediate filament proteins as a model system to explain why the utilization of hierarchical structural features is vital to their ability to combine strength, robustness, and adaptability. Experimental studies demonstrating the activation of angiogenesis, the growth of new blood vessels, are presented as an example of how adaptability of structure in biological tissue is achieved through changes in gene expression that result in an altered material structure. We analyze the concepts in light of the universality and diversity of the structural makeup of protein materials and discuss the findings in the context of potential fundamental evolutionary principles that control their nanoscale structure. We conclude with a discussion of multiscale science in biology and de novo materials design. PMID:20676305

  12. Robust flicker evaluation method for low power adaptive dimming LCDs

    NASA Astrophysics Data System (ADS)

    Kim, Seul-Ki; Song, Seok-Jeong; Nam, Hyoungsik

    2015-05-01

    This paper describes a robust dimming flicker evaluation method of adaptive dimming algorithms for low power liquid crystal displays (LCDs). While the previous methods use sum of square difference (SSD) values without excluding the image sequence information, the proposed modified SSD (mSSD) values are obtained only with the dimming flicker effects by making use of differential images. The proposed scheme is verified for eight dimming configurations of two dimming level selection methods and four temporal filters over three test videos. Furthermore, a new figure of merit is introduced to cover the dimming flicker as well as image qualities and power consumption.

  13. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    PubMed Central

    Quagliotti, Fulvia

    2014-01-01

    The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required. PMID:24688411

  14. Robust adaptive backstepping control for reentry reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Wu, Zhong; Du, Yijiang

    2016-09-01

    During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.

  15. Nonlinear mode decomposition: a noise-robust, adaptive decomposition method.

    PubMed

    Iatsenko, Dmytro; McClintock, Peter V E; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool-nonlinear mode decomposition (NMD)-which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques-which, together with the adaptive choice of their parameters, make it extremely noise robust-and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  16. Robustness via Run-Time Adaptation of Contingent Plans

    NASA Technical Reports Server (NTRS)

    Bresina, John L.; Washington, Richard; Norvig, Peter (Technical Monitor)

    2000-01-01

    In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.

  17. Nonlinear mode decomposition: a noise-robust, adaptive decomposition method.

    PubMed

    Iatsenko, Dmytro; McClintock, Peter V E; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool-nonlinear mode decomposition (NMD)-which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques-which, together with the adaptive choice of their parameters, make it extremely noise robust-and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download. PMID:26465549

  18. Robust stochastic resonance: Signal detection and adaptation in impulsive noise

    NASA Astrophysics Data System (ADS)

    Kosko, Bart; Mitaim, Sanya

    2001-11-01

    Stochastic resonance (SR) occurs when noise improves a system performance measure such as a spectral signal-to-noise ratio or a cross-correlation measure. All SR studies have assumed that the forcing noise has finite variance. Most have further assumed that the noise is Gaussian. We show that SR still occurs for the more general case of impulsive or infinite-variance noise. The SR effect fades as the noise grows more impulsive. We study this fading effect on the family of symmetric α-stable bell curves that includes the Gaussian bell curve as a special case. These bell curves have thicker tails as the parameter α falls from 2 (the Gaussian case) to 1 (the Cauchy case) to even lower values. Thicker tails create more frequent and more violent noise impulses. The main feedback and feedforward models in the SR literature show this fading SR effect for periodic forcing signals when we plot either the signal-to-noise ratio or a signal correlation measure against the dispersion of the α-stable noise. Linear regression shows that an exponential law γopt(α)=cAα describes this relation between the impulsive index α and the SR-optimal noise dispersion γopt. The results show that SR is robust against noise ``outliers.'' So SR may be more widespread in nature than previously believed. Such robustness also favors the use of SR in engineering systems. We further show that an adaptive system can learn the optimal noise dispersion for two standard SR models (the quartic bistable model and the FitzHugh-Nagumo neuron model) for the signal-to-noise ratio performance measure. This also favors practical applications of SR and suggests that evolution may have tuned the noise-sensitive parameters of biological systems.

  19. Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

    NASA Astrophysics Data System (ADS)

    Samaras, C.; Cook, L.

    2015-12-01

    Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

  20. Distributed reinforcement learning for adaptive and robust network intrusion response

    NASA Astrophysics Data System (ADS)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  1. Robust image registration using adaptive coherent point drift method

    NASA Astrophysics Data System (ADS)

    Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong

    2016-04-01

    Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.

  2. Robust identification of local adaptation from allele frequencies.

    PubMed

    Günther, Torsten; Coop, Graham

    2013-09-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

  3. Robust Identification of Local Adaptation from Allele Frequencies

    PubMed Central

    Günther, Torsten; Coop, Graham

    2013-01-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

  4. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations.

    PubMed

    Egbert, Matthew D; Pérez-Mercader, Juan

    2016-01-01

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism's internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving "interoceptively," i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579

  5. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations

    PubMed Central

    Egbert, Matthew D.; Pérez-Mercader, Juan

    2016-01-01

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism’s internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving “interoceptively,” i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579

  6. Optimization under uncertainty: Adaptive variance reduction, adaptive metamodeling, and investigation of robustness measures

    NASA Astrophysics Data System (ADS)

    Medina, Juan Camilo

    This dissertation offers computational and theoretical advances for optimization under uncertainty problems that utilize a probabilistic framework for addressing such uncertainties, and adopt a probabilistic performance as objective function. Emphasis is placed on applications that involve potentially complex numerical and probability models. A generalized approach is adopted, treating the system model as a "black-box" and relying on stochastic simulation for evaluating the probabilistic performance. This approach can impose, though, an elevated computational cost, and two of the advances offered in this dissertation aim at decreasing the computational burden associated with stochastic simulation when integrated with optimization applications. The first one develops an adaptive implementation of importance sampling (a popular variance reduction technique) by sharing information across the iterations of the numerical optimization algorithm. The system model evaluations from the current iteration are utilized to formulate importance sampling densities for subsequent iterations with only a small additional computational effort. The characteristics of these densities as well as the specific model parameters these densities span are explicitly optimized. The second advancement focuses on adaptive tuning of a kriging metamodel to replace the computationally intensive system model. A novel implementation is considered, establishing a metamodel with respect to both the uncertain model parameters as well as the design variables, offering significant computational savings. Additionally, the adaptive selection of certain characteristics of the metamodel, such as support points or order of basis functions, is considered by utilizing readily available information from the previous iteration of the optimization algorithm. The third advancement extends to a different application and considers the assessment of the appropriateness of different candidate robust designs. A novel

  7. Adaptive robust controller based on integral sliding mode concept

    NASA Astrophysics Data System (ADS)

    Taleb, M.; Plestan, F.

    2016-09-01

    This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

  8. Adaptive robust control of longitudinal and transverse electron beam profiles

    NASA Astrophysics Data System (ADS)

    Rezaeizadeh, Amin; Schilcher, Thomas; Smith, Roy S.

    2016-05-01

    Feedback control of the longitudinal and transverse electron beam profiles are considered to be critical for beam control in accelerators. In the feedback scheme, the longitudinal or transverse beam profile is measured and compared to a desired profile to give an error estimate. The error is then used to act on the appropriate actuators to correct the profile. The role of the transverse feedback is to steer the beam in a particular trajectory, known as the "orbit." The common approach for orbit correction is based on approximately inverting the response matrix, and in the best case, involves regulating or filtering the singular values. In the current contribution, a more systematic and structured way of handling orbit correction is introduced giving robustness against uncertainties in the response matrix. Moreover, the input bounds are treated to avoid violating the limits of the corrector currents. The concept of the robust orbit correction has been successfully tested at the SwissFEL injector test facility. In the SwissFEL machine, a photo-injector laser system extracts electrons from a cathode and a similar robust control method is developed for the longitudinal feedback control of the current profile of the electron bunch. The method manipulates the angles of the crystals in the laser system to produce a desired charge distribution over the electron bunch length. This approach paves the way towards automation of laser pulse stacking.

  9. Non-adaptive robust filters for speckle noise reduction

    NASA Astrophysics Data System (ADS)

    Frery, Alejandro C.; Santanna, Sidnei J. S.

    1993-06-01

    After briefly reviewing some classical filters for speckle removal, five filters with characteristics of robustness, suitable for speckle noise reduction, are derived and implemented. These filters are the ones based on the trimmed maximum likelihood and moments estimators, the ones based on the median, on the inter-quartile range, and on the median absolute deviation. Assuming that observations within a synthetic aperture radar image are outcomes of independent Rayleigh random variables, these filters exhibit a good performance from both the signal-to-noise reduction and from the edge preserving criteria. The problem of filtering in an image is posed as an estimation problem.

  10. Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

    NASA Astrophysics Data System (ADS)

    Wang, Xiuzhong; Srinivas, Chukka

    2016-03-01

    This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

  11. Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

    2009-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

  12. Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

    PubMed

    Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

    2016-03-01

    This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem.

  13. Shape adaptive, robust iris feature extraction from noisy iris images.

    PubMed

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-10-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

  14. Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

    NASA Astrophysics Data System (ADS)

    Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  15. A methodology for adaptable and robust ecosystem services assessment

    USGS Publications Warehouse

    Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

    2014-01-01

    Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

  16. A Methodology for Adaptable and Robust Ecosystem Services Assessment

    PubMed Central

    Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

    2014-01-01

    Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts. PMID:24625496

  17. Robustness

    NASA Technical Reports Server (NTRS)

    Ryan, R.

    1993-01-01

    Robustness is a buzz word common to all newly proposed space systems design as well as many new commercial products. The image that one conjures up when the word appears is a 'Paul Bunyon' (lumberjack design), strong and hearty; healthy with margins in all aspects of the design. In actuality, robustness is much broader in scope than margins, including such factors as simplicity, redundancy, desensitization to parameter variations, control of parameter variations (environments flucation), and operational approaches. These must be traded with concepts, materials, and fabrication approaches against the criteria of performance, cost, and reliability. This includes manufacturing, assembly, processing, checkout, and operations. The design engineer or project chief is faced with finding ways and means to inculcate robustness into an operational design. First, however, be sure he understands the definition and goals of robustness. This paper will deal with these issues as well as the need for the requirement for robustness.

  18. Joint Robust Transmit/Receive Adaptive Beamforming for MIMO Radar Using Probability-Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Weiyu; Vorobyov, Sergiy A.

    2016-01-01

    A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.

  19. A fast, robust, and simple implicit method for adaptive time-stepping on adaptive mesh-refinement grids

    NASA Astrophysics Data System (ADS)

    Commerçon, B.; Debout, V.; Teyssier, R.

    2014-03-01

    Context. Implicit solvers present strong limitations when used on supercomputing facilities and in particular for adaptive mesh-refinement codes. Aims: We present a new method for implicit adaptive time-stepping on adaptive mesh-refinement grids. We implement it in the radiation-hydrodynamics solver we designed for the RAMSES code for astrophysical purposes and, more particularly, for protostellar collapse. Methods: We briefly recall the radiation-hydrodynamics equations and the adaptive time-stepping methodology used for hydrodynamical solvers. We then introduce the different types of boundary conditions (Dirichlet, Neumann, and Robin) that are used at the interface between levels and present our implementation of the new method in the RAMSES code. The method is tested against classical diffusion and radiation-hydrodynamics tests, after which we present an application for protostellar collapse. Results: We show that using Dirichlet boundary conditions at level interfaces is a good compromise between robustness and accuracy and that it can be used in structure formation calculations. The gain in computational time over our former unique time step method ranges from factors of 5 to 50 depending on the level of adaptive time-stepping and on the problem. We successfully compare the old and new methods for protostellar collapse calculations that involve highly non linear physics. Conclusions: We have developed a simple but robust method for adaptive time-stepping of implicit scheme on adaptive mesh-refinement grids. It can be applied to a wide variety of physical problems that involve diffusion processes.

  20. Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

    PubMed

    Huang, X N; Ren, H P

    2016-01-01

    Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043

  1. Multivariable output feedback robust adaptive tracking control design for a class of delayed systems

    NASA Astrophysics Data System (ADS)

    Mirkin, Boris; Gutman, Per-Olof

    2015-02-01

    In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.

  2. Robust speech perception: Recognize the familiar, generalize to the similar, and adapt to the novel

    PubMed Central

    Kleinschmidt, Dave F.; Jaeger, T. Florian

    2016-01-01

    Successful speech perception requires that listeners map the acoustic signal to linguistic categories. These mappings are not only probabilistic, but change depending on the situation. For example, one talker’s /p/ might be physically indistinguishable from another talker’s /b/ (cf. lack of invariance). We characterize the computational problem posed by such a subjectively non-stationary world and propose that the speech perception system overcomes this challenge by (1) recognizing previously encountered situations, (2) generalizing to other situations based on previous similar experience, and (3) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (1) to (3) can be understood as inference under uncertainty about the appropriate generative model for the current talker, thereby facilitating robust speech perception despite the lack of invariance. We focus on two critical aspects of the ideal adapter. First, in situations that clearly deviate from previous experience, listeners need to adapt. We develop a distributional (belief-updating) learning model of incremental adaptation. The model provides a good fit against known and novel phonetic adaptation data, including perceptual recalibration and selective adaptation. Second, robust speech recognition requires listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these two aspects of the ideal adapter provide a unifying explanation for adaptation, talker-specificity, and generalization across talkers and groups of talkers (e.g., accents and dialects). The ideal adapter provides a guiding framework for future investigations into speech perception and adaptation, and more broadly language comprehension. PMID:25844873

  3. Adaptive SVM fusion for robust multi-biometrics verification with missing data

    NASA Astrophysics Data System (ADS)

    Zhai, Xiuna; Zhao, Yan; Wang, Jingyan; Li, Yongping

    2013-03-01

    Conventional multimodal biometrics systems usually do not account for missing data (missing modalities or incomplete score lists) that is commonly encountered in real applications. The presence of missing data in multimodal biometric systems can be inconvenient to the client, as the system will reject the submitted biometric data and request for another trial. In such cases, robust multimodal biometric verification is needed. In this paper, we present the criteria, fusion method and performance metrics of a robust multimodal biometrics verification system that verifies the client's identity at any condition of data missing. A novel adaptive SVM classification method is proposed for missing dimensional values, which can handle the missing data in multimodal biometrics. We show that robust multibiometrics imposes additional requirements on multimodal fusion when compared to conventional multibiometrics. We also argue that the usual performance metrics of false accept and false reject rates are insufficient yardsticks for robust verification and propose new metrics against which we benchmark our system.

  4. Iterative Robust Capon Beamforming with Adaptively Updated Array Steering Vector Mismatch Levels

    PubMed Central

    Sun, Liguo

    2014-01-01

    The performance of the conventional adaptive beamformer is sensitive to the array steering vector (ASV) mismatch. And the output signal-to interference and noise ratio (SINR) suffers deterioration, especially in the presence of large direction of arrival (DOA) error. To improve the robustness of traditional approach, we propose a new approach to iteratively search the ASV of the desired signal based on the robust capon beamformer (RCB) with adaptively updated uncertainty levels, which are derived in the form of quadratically constrained quadratic programming (QCQP) problem based on the subspace projection theory. The estimated levels in this iterative beamformer present the trend of decreasing. Additionally, other array imperfections also degrade the performance of beamformer in practice. To cover several kinds of mismatches together, the adaptive flat ellipsoid models are introduced in our method as tight as possible. In the simulations, our beamformer is compared with other methods and its excellent performance is demonstrated via the numerical examples. PMID:27355008

  5. A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

    NASA Astrophysics Data System (ADS)

    Chen, Xianshun; Feng, Liang; Ong, Yew Soon

    2012-07-01

    In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

  6. Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

    NASA Astrophysics Data System (ADS)

    Du, Bing; Ruan, Chun

    With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

  7. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    PubMed

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method.

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

    PubMed

    Xia, Kewei; Huo, Wei

    2016-05-01

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

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

    PubMed

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. PMID:26892402

  10. A robust adaptive sampling method for faster acquisition of MR images.

    PubMed

    Vellagoundar, Jaganathan; Machireddy, Ramasubba Reddy

    2015-06-01

    A robust adaptive k-space sampling method is proposed for faster acquisition and reconstruction of MR images. In this method, undersampling patterns are generated based on magnitude profile of a fully acquired 2-D k-space data. Images are reconstructed using compressive sampling reconstruction algorithm. Simulation experiments are done to assess the performance of the proposed method under various signal-to-noise ratio (SNR) levels. The performance of the method is better than non-adaptive variable density sampling method when k-space SNR is greater than 10dB. The method is implemented on a fully acquired multi-slice raw k-space data and a quality assurance phantom data. Data reduction of up to 60% is achieved in the multi-slice imaging data and 75% is achieved in the phantom imaging data. The results show that reconstruction accuracy is improved over non-adaptive or conventional variable density sampling method. The proposed sampling method is signal dependent and the estimation of sampling locations is robust to noise. As a result, it eliminates the necessity of mathematical model and parameter tuning to compute k-space sampling patterns as required in non-adaptive sampling methods.

  11. A robust adaptive nonlinear fault-tolerant controller via norm estimation for reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Hu, Chaofang; Gao, Zhifei; Ren, Yanli; Liu, Yunbing

    2016-11-01

    In this paper, a reusable launch vehicle (RLV) attitude control problem with actuator faults is addressed via the robust adaptive nonlinear fault-tolerant control (FTC) with norm estimation. Firstly, the accurate tracking task of attitude angles in the presence of parameter uncertainties and external disturbances is considered. A fault-free controller is proposed using dynamic surface control (DSC) combined with fuzzy adaptive approach. Furthermore, the minimal learning parameter strategy via norm estimation technique is introduced to reduce the multi-parameter adaptive computation burden of fuzzy approximation of the lump uncertainties. Secondly, a compensation controller is designed to handle the partial loss fault of actuator effectiveness. The unknown maximum eigenvalue of actuator efficiency loss factors is estimated online. Moreover, stability analysis guarantees that all signals of the closed-loop control system are semi-global uniformly ultimately bounded. Finally, illustrative simulations show the effectiveness of the proposed method.

  12. VSS Robust Adaptive Control Including a Self-Tuning Controller for a Rotary Inverted Pendulum

    NASA Astrophysics Data System (ADS)

    Hirata, Hiroshi; Takabe, Tomohiro; Anabuki, Masatoshi; Ouchi, Shigeto

    So many papers with respect to the stabilization of the inverted pendulum are reported, because it is typically unstable system and is well used as example to verify many control theories. However, few approaches consider the inverted pendulum as unknown parameter system. This paper proposes a new VSS (Variable Structure System) robust adaptive control system including a self-tuning controller for a rotary inverted pendulum whose whole parameters are unknown. The control system prepares two kinds of adaptive controllers, and the stabilization of inverted pendulum is achieved by separating the system to two parts of the pendulum and the rotary arm. The rotational angle of the pendulum is stabilized by tracking type's VSS adaptive control method, and the rotary arm is simultaneously stabilized by STC (self-tuning control) system that assures the boundary reference angle of the pendulum. It is then not sufficient to construct STC system by using only adjustable parameter of VSS adaptive control system. Therefore, whole basic parameters are recursively estimated in order to realize STC system by using least squares parameter adaptive law, and it is achieved by superposing the perturbation signal to the stable adaptive control input on limited short interval. Furthermore, STC system designs LQ controller by developing an efficient QR method for real time operation. Finally, the validity of the proposed system is demonstrated through some numerical simulations and practical experimental result.

  13. Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

    PubMed

    Ye, Jinzuo; Chi, Chongwei; Xue, Zhenwen; Wu, Ping; An, Yu; Xu, Han; Zhang, Shuang; Tian, Jie

    2014-02-01

    Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

  14. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    PubMed Central

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  15. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  16. Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster.

    PubMed

    Williams, Caroline M; Watanabe, Miki; Guarracino, Mario R; Ferraro, Maria B; Edison, Arthur S; Morgan, Theodore J; Boroujerdi, Arezue F B; Hahn, Daniel A

    2014-12-01

    When ectotherms are exposed to low temperatures, they enter a cold-induced coma (chill coma) that prevents resource acquisition, mating, oviposition, and escape from predation. There is substantial variation in time taken to recover from chill coma both within and among species, and this variation is correlated with habitat temperatures such that insects from cold environments recover more quickly. This suggests an adaptive response, but the mechanisms underlying variation in recovery times are unknown, making it difficult to decisively test adaptive hypotheses. We use replicated lines of Drosophila melanogaster selected in the laboratory for fast (hardy) or slow (susceptible) chill-coma recovery times to investigate modifications to metabolic profiles associated with cold adaptation. We measured metabolite concentrations of flies before, during, and after cold exposure using nuclear magnetic resonance (NMR) spectroscopy to test the hypotheses that hardy flies maintain metabolic homeostasis better during cold exposure and recovery, and that their metabolic networks are more robust to cold-induced perturbations. The metabolites of cold-hardy flies were less cold responsive and their metabolic networks during cold exposure were more robust, supporting our hypotheses. Metabolites involved in membrane lipid synthesis, tryptophan metabolism, oxidative stress, energy balance, and proline metabolism were altered by selection on cold tolerance. We discuss the potential significance of these alterations.

  17. Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster

    PubMed Central

    Williams, CM; Watanabe, M; Guarracino, MR; Ferraro, MB; Edison, AS; Morgan, TJ; Boroujerdi, AFB; Hahn, DA

    2015-01-01

    When ectotherms are exposed to low temperatures, they enter a cold-induced coma (chill coma) that prevents resource acquisition, mating, oviposition, and escape from predation. There is substantial variation in time taken to recover from chill coma both within and among species, and this variation is correlated with habitat temperatures such that insects from cold environments recover more quickly. This suggests an adaptive response, but the mechanisms underlying variation in recovery times are unknown, making it difficult to decisively test adaptive hypotheses. We use replicated lines of Drosophila melanogaster selected in the laboratory for fast (hardy) or slow (susceptible) chill-coma recovery times to investigate modifications to metabolic profiles associated with cold adaptation. We measured metabolite concentrations of flies before, during, and after cold exposure using NMR spectroscopy to test the hypotheses that hardy flies maintain metabolic homeostasis better during cold exposure and recovery, and that their metabolic networks are more robust to cold-induced perturbations. The metabolites of cold-hardy flies were less cold responsive and their metabolic networks during cold exposure were more robust, supporting our hypotheses. Metabolites involved in membrane lipid synthesis, tryptophan metabolism, oxidative stress, energy balance, and proline metabolism were altered by selection on cold tolerance. We discuss the potential significance of these alterations. PMID:25308124

  18. Memory-based robust adaptive control of a variable length stepping nanomanipulator

    NASA Astrophysics Data System (ADS)

    Saeidpourazar, Reza; Jalili, Nader

    2007-04-01

    This paper presents the modeling and memory-based robust adaptive control of a variable length stepping nanomanipulator. A three degree of freedom (3DOF) nanomanipulator with revolute revolute prismatic (RRP) actuator structure, namely here MM3A, is utilized for a variety of nanomanipulation tasks. Unlike widely used Cartesian-structure nanomanipulators, the MM3A is equipped with revolute-piezoelectric actuators which result in outstanding performance for controlling the nanomanipulator's tip alignment during the nanomanipulation process. However, the RRP structure of the nanomanipulator introduces complicity in kinematic and dynamic equations of the system which needs to be addressed in order to control the nanomanipulation process. Dissimilar to the ordinary piezoelectric actuators which provide only a couple of micrometers working range, the piezoelectric actuators utilized in MM3A, namely Nanomotors, provide wide range of action (120° in revolute actuators and 12mm in prismatic actuator) with sub-nano scale precision (0.1 μrad in revolute actuators and 0.25 nm in prismatic actuator). This wide range of action combined with sub-nano scale precision is achieved using a special stick/slip moving principle of the Nanomotors. However, such stick/slip motion results in stepping movement of the MM3A. Hence, due to the RRP structure and stepping movement principle of the MM3A nanomanipulator, controller design for the nanomanipulation process is not a trivial task. In this paper, a novel memory-based robust adaptive controller is proposed to overcome these shortfalls. Following the development of the memory-based robust adaptive controller, numerical simulations of the proposed controller are preformed to demonstrate the positioning performance capability of the controller in nanomanipulation tasks.

  19. Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.

    PubMed

    Briat, Corentin; Gupta, Ankit; Khammash, Mustafa

    2016-01-27

    The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits. PMID:27136686

  20. Robust adaptive tracking control of MIMO nonlinear systems in the presence of actuator hysteresis

    NASA Astrophysics Data System (ADS)

    Fu, Guiyuan; Ou, Linlin; Zhang, Weidong

    2016-07-01

    Adaptive tracking control of a class of MIMO nonlinear system preceded by unknown hysteresis is investigated. Based on dynamic surface control, an adaptive robust control law is developed and compensators are designed to mitigate the influences of both the unknown bounded external uncertainties and the unknown Prandtl-Islinskii hysteresis. By adopting the low-pass filters, the explosion of complexity caused by tedious computation of the time derivatives of the virtual control laws is overcome. With the proposed control scheme, the closed-loop system is proved to be semi-globally ultimately bounded by the Lyapunov stability theory, and the output of the controlled system can track the desired trajectories with an arbitrarily small error. Finally, numerical simulations are given to verify the effectiveness of the proposed approach.

  1. Adaptive step-size strategy for noise-robust Fourier ptychographic microscopy.

    PubMed

    Zuo, Chao; Sun, Jiasong; Chen, Qian

    2016-09-01

    The incremental gradient approaches, such as PIE and ePIE, are widely used in the field of ptychographic imaging due to their great flexibility and computational efficiency. Nevertheless, their stability and reconstruction quality may be significantly degraded when non-negligible noise is present in the image. Though this problem is often attributed to the non-convex nature of phase retrieval, we found the reason for this is more closely related to the choice of the step-size, which needs to be gradually diminishing for convergence even in the convex case. To this end, we introduce an adaptive step-size strategy that decreases the step-size whenever sufficient progress is not made. The synthetic and real experiments on Fourier ptychographic microscopy show that the adaptive step-size strategy significantly improves the stability and robustness of the reconstruction towards noise yet retains the fast initial convergence speed of PIE and ePIE. More importantly, the proposed approach is simple, nonparametric, and does not require any preknowledge about the noise statistics. The great performance and limited computational complexity make it a very attractive and promising technique for robust Fourier ptychographic microscopy under noisy conditions. PMID:27607676

  2. Adaptive robust stabilisation for a class of uncertain nonlinear time-delay dynamical systems

    NASA Astrophysics Data System (ADS)

    Wu, Hansheng

    2013-02-01

    The problem of adaptive robust stabilisation is considered for a class of uncertain nonlinear dynamical systems with multiple time-varying delays. It is assumed that the upper bounds of the nonlinear delayed state perturbations are unknown and that the time-varying delays are any non-negative continuous and bounded functions which do not require that their derivatives have to be less than one. In particular, it is only required that the nonlinear uncertainties, which can also include time-varying delays, are bounded in any non-negative nonlinear functions which are not required to be known for the system designer. For such a class of uncertain nonlinear time-delay systems, a new method is presented whereby a class of continuous memoryless adaptive robust state feedback controllers with a rather simpler structure is proposed. It is also shown that the solutions of uncertain nonlinear time-delay systems can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, as an application, an uncertain nonlinear time-delay ecosystem with two competing species is given to demonstrate the validity of the results.

  3. Simple robust control laws for robot manipulators. Part 1: Non-adaptive case

    NASA Technical Reports Server (NTRS)

    Wen, J. T.; Bayard, D. S.

    1987-01-01

    A new class of exponentially stabilizing control laws for joint level control of robot arms is introduced. It has been recently recognized that the nonlinear dynamics associated with robotic manipulators have certain inherent passivity properties. More specifically, the derivation of the robotic dynamic equations from the Hamilton's principle gives rise to natural Lyapunov functions for control design based on total energy considerations. Through a slight modification of the energy Lyapunov function and the use of a convenient lemma to handle third order terms in the Lyapunov function derivatives, closed loop exponential stability for both the set point and tracking control problem is demonstrated. The exponential convergence property also leads to robustness with respect to frictions, bounded modeling errors and instrument noise. In one new design, the nonlinear terms are decoupled from real-time measurements which completely removes the requirement for on-line computation of nonlinear terms in the controller implementation. In general, the new class of control laws offers alternatives to the more conventional computed torque method, providing tradeoffs between robustness, computation and convergence properties. Furthermore, these control laws have the unique feature that they can be adapted in a very simple fashion to achieve asymptotically stable adaptive control.

  4. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

    PubMed Central

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

  5. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images.

    PubMed

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

  6. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images.

    PubMed

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms.

  7. Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

    NASA Technical Reports Server (NTRS)

    Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.

    1996-01-01

    Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

  8. Reversible adapting layer produces robust single-crystal electrocatalyst for oxygen evolution

    PubMed Central

    Tung, Ching-Wei; Hsu, Ying-Ya; Shen, Yen-Ping; Zheng, Yixin; Chan, Ting-Shan; Sheu, Hwo-Shuenn; Cheng, Yuan-Chung; Chen, Hao Ming

    2015-01-01

    Electrochemically converting water into oxygen/hydrogen gas is ideal for high-density renewable energy storage in which robust electrocatalysts for efficient oxygen evolution play crucial roles. To date, however, electrocatalysts with long-term stability have remained elusive. Here we report that single-crystal Co3O4 nanocube underlay with a thin CoO layer results in a high-performance and high-stability electrocatalyst in oxygen evolution reaction. An in situ X-ray diffraction method is developed to observe a strong correlation between the initialization of the oxygen evolution and the formation of active metal oxyhydroxide phase. The lattice of skin layer adapts to the structure of the active phase, which enables a reversible facile structural change that facilitates the chemical reactions without breaking the scaffold of the electrocatalysts. The single-crystal nanocube electrode exhibits stable, continuous oxygen evolution for >1,000 h. This robust stability is attributed to the complementary nature of defect-free single-crystal electrocatalyst and the reversible adapting layer. PMID:26315066

  9. Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Chung, E. S.

    2014-12-01

    This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

  10. Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system.

    PubMed

    Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai

    2009-06-01

    In this paper, a robust dynamic sliding mode control system (RDSMC) using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a magnetic levitation system considering the uncertainties. First, a dynamic model of the magnetic levitation system is derived. Then, a proportional-integral-derivative (PID)-type sliding-mode control system (SMC) is adopted for tracking of the reference trajectories. Moreover, a new PID-type dynamic sliding-mode control system (DSMC) is proposed to reduce the chattering phenomenon. However, due to the hardware being limited and the uncertainty bound being unknown of the switching function for the DSMC, an RDSMC is proposed to improve the control performance and further increase the robustness of the magnetic levitation system. In the RDSMC, an RENN estimator is used to estimate an unknown nonlinear function of lumped uncertainty online and replace the switching function in the hitting control of the DSMC directly. The adaptive learning algorithms that trained the parameters of the RENN online are derived using Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher order terms in Taylor series. Finally, some experimental results of tracking the various periodic trajectories demonstrate the validity of the proposed RDSMC for practical applications. PMID:19423437

  11. Robust adaptive feedforward control and achievable tracking for systems with time delays

    NASA Astrophysics Data System (ADS)

    Buehner, Michael R.; Young, Peter M.

    2015-04-01

    A feedback/feedforward controller architecture is developed that characterises the achievable reference tracking of real time inputs for both minimum phase and non-minimum phase systems with time delays, when there are no modelling errors or external disturbances. This characterisation is obtained by factoring the plant into its minimum phase, non-minimum phase, and time delay components, which are used to design two feedforward controllers that inject signals into two points of the feedback loop. Design constraints are provided that determine both the types of signals that may be achieved, and the feedforward controllers that will generate that output. Of course, in practice, both modelling errors and external disturbances will be present. In this case, we develop robust analysis tools that both guide the feedback controller design process, and provide rigorous robust tracking performance that guarantees for the overall resulting closed-loop system. Robust methods for designing the feedforward controllers are presented, and numerical examples are provided. The performance of this architecture depends strongly on the choice of design parameters, and the accuracy of the plant model used. Hence, the use of adaptation methods is also considered, and it is shown that they can readily be employed to improve the performance of this control methodology.

  12. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

    NASA Astrophysics Data System (ADS)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

    2011-12-01

    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  13. A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

    NASA Astrophysics Data System (ADS)

    Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

    2013-05-01

    This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

  14. Robust adaptive control of spacecraft proximity maneuvers under dynamic coupling and uncertainty

    NASA Astrophysics Data System (ADS)

    Sun, Liang; Huo, Wei

    2015-11-01

    This paper provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results.

  15. Robust adaptive neural control for a class of uncertain MIMO nonlinear systems

    NASA Astrophysics Data System (ADS)

    Wang, Chenliang; Lin, Yan

    2015-08-01

    In this paper, a novel robust adaptive neural control scheme is proposed for a class of uncertain multi-input multi-output nonlinear systems. The proposed scheme has the following main features: (1) a kind of Hurwitz condition is introduced to handle the state-dependent control gain matrix and some assumptions in existing schemes are relaxed; (2) by introducing a novel matrix normalisation technique, it is shown that all bound restrictions imposed on the control gain matrix in existing schemes can be removed; (3) the singularity problem is avoided without any extra effort, which makes the control law quite simple. Besides, with the aid of the minimal learning parameter technique, only one parameter needs to be updated online regardless of the system input-output dimension and the number of neural network nodes. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

  16. Robust adaptive relative position and attitude control for spacecraft autonomous proximity.

    PubMed

    Sun, Liang; Huo, Wei; Jiao, Zongxia

    2016-07-01

    This paper provides new results of the dynamical modeling and controller designing for autonomous close proximity phase during rendezvous and docking in the presence of kinematic couplings and model uncertainties. A globally defined relative motion mechanical model for close proximity operations is introduced firstly. Then, in spite of the kinematic couplings and thrust misalignment between relative rotation and relative translation, robust adaptive relative position and relative attitude controllers are designed successively. Finally, stability of the overall system is proved that the relative position and relative attitude are uniformly ultimately bounded, and the size of the ultimate bound can be regulated small enough by control system parameters. Performance of the controlled overall system is demonstrated via a representative numerical example. PMID:26993103

  17. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    NASA Astrophysics Data System (ADS)

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-05-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  18. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    PubMed

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical.

  19. Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

    NASA Astrophysics Data System (ADS)

    Tryfonidis, Michail

    It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that

  20. Structural and functional robustness of the adaptive-sorting signaling network

    NASA Astrophysics Data System (ADS)

    Pang, Ning-Ning

    2016-06-01

    A major task of study on ligand discrimination by T cells is the construction of a mechanistic model to account for threshold setting in response to variant ligands interacting with the same T-cell receptors. Recently, Lalanne and Francois in a seminal paper (2013 Phys. Rev. Lett. 110 218102) have addressed this question by constructing minimal core circuits such that the biological outputs can satisfy the essential properties of early T-cell activation. To make this core set of network topology a valuable tool for synthetic biologists to robustly engineer biological circuits, we are motivated to ask a general question: is adaptive response encoded by the proposed circuit topology structurally stable, regardless of the values of the kinetic parameters? This has particularly relevant effects for the network reliability, since failures in ligand discrimination result in either infection or autoimmune diseases. To the best of our knowledge, a rigorous and complete mathematical proof of this issue is still lacking in the literature. In this paper, by giving a rigorous mathematical proof, we have shown that this regulatory circuitry is appropriately designed and the existence, uniqueness, and globally asymptotic attractiveness of the steady state are preserved. Moreover, we further generalize the adaptive sorting module and undertake an extensive analysis on the trade-off between antagonism and sensitivity of T-cell ligand discrimination in various cellular conditions. Notably, the optimal phosphorylation step in which to place the regulatory motif is analytically obtained and numerically confirmed. Finally, relevant experimental facts and biological implications are discussed.

  1. Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection.

    PubMed

    Su, Hai; Xing, Fuyong; Yang, Lin

    2016-06-01

    Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96.

  2. 6-DOF robust adaptive terminal sliding mode control for spacecraft formation flying

    NASA Astrophysics Data System (ADS)

    Wang, Jianying; Sun, Zhaowei

    2012-04-01

    This paper addresses the tracking control problem of the leader-follower spacecraft formation, by which we mean that the relative motion between the leader and the follower is required to track a desired time-varying trajectory given in advance. Using dual number, the six-degree-of-freedom motion of the follower spacecraft relative to the leader spacecraft is modeled, where the coupling effect between the translational motion and the rotational one is accounted. A robust adaptive terminal sliding mode control law, including the adaptive algorithms, is proposed to ensure the finite time convergence of the relative motion tracking errors despite the presence of model uncertainties and external disturbances, based on which a modified controller is furthermore developed to solve the dual-equilibrium problem caused by dual quaternion representation. In addition, to alleviate the chattering, hyperbolic tangent function is adopted to substitute for the sign function. And by theoretical analysis, it is proved that the tracking error in such case will converge to a neighborhood of the origin in finite time. Finally, numerical simulations are performed to demonstrate the validity of the proposed approaches.

  3. Robust adaptive control for a hybrid solid oxide fuel cell system

    NASA Astrophysics Data System (ADS)

    Snyder, Steven

    2011-12-01

    Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.

  4. An Investigation of the Robustness of a Partial Credit Model-Based Computerized Adaptive Test to Misfitting Items.

    ERIC Educational Resources Information Center

    De Ayala, R. J.; And Others

    The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated…

  5. Robust adaptive control for a class of uncertain non-affine nonlinear systems using affine-type neural networks

    NASA Astrophysics Data System (ADS)

    Zhao, Shitie; Gao, Xianwen

    2016-08-01

    A robust adaptive control is proposed for a class of single-input single-output non-affine nonlinear systems. In order to approximate the unknown nonlinear function, a novel affine-type neural network is used, and then to compensate the approximation error and external disturbance a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proved that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given out based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method.

  6. Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

    NASA Astrophysics Data System (ADS)

    Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

    2016-03-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

  7. Region of interest based robust watermarking scheme for adaptation in small displays

    NASA Astrophysics Data System (ADS)

    Vivekanandhan, Sapthagirivasan; K. B., Kishore Mohan; Vemula, Krishna Manohar

    2010-02-01

    Now-a-days Multimedia data can be easily replicated and the copyright is not legally protected. Cryptography does not allow the use of digital data in its original form and once the data is decrypted, it is no longer protected. Here we have proposed a new double protected digital image watermarking algorithm, which can embed the watermark image blocks into the adjacent regions of the host image itself based on their blocks similarity coefficient which is robust to various noise effects like Poisson noise, Gaussian noise, Random noise and thereby provide double security from various noises and hackers. As instrumentation application requires a much accurate data, the watermark image which is to be extracted back from the watermarked image must be immune to various noise effects. Our results provide better extracted image compared to the present/existing techniques and in addition we have done resizing the same for various displays. Adaptive resizing for various size displays is being experimented wherein we crop the required information in a frame, zoom it for a large display or resize for a small display using a threshold value and in either cases background is not given much importance but it is only the fore-sight object which gains importance which will surely be helpful in performing surgeries.

  8. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

    NASA Astrophysics Data System (ADS)

    Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

    2016-04-01

    Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects

  9. Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

    NASA Astrophysics Data System (ADS)

    Kun, David William

    Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external

  10. Observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems with unknown dead-zone input.

    PubMed

    Liu, Yan-Jun; Zhou, Ning

    2010-10-01

    Based on the universal approximation property of the fuzzy-neural networks, an adaptive fuzzy-neural observer design algorithm is studied for a class of nonlinear SISO systems with both a completely unknown function and an unknown dead-zone input. The fuzzy-neural networks are used to approximate the unknown nonlinear function. Because it is assumed that the system states are unmeasured, an observer needs to be designed to estimate those unmeasured states. In the previous works with the observer design based on the universal approximator, when the dead-zone input appears it is ignored and the stability of the closed-loop system will be affected. In this paper, the proposed algorithm overcomes the affections of dead-zone input for the stability of the systems. Moreover, the dead-zone parameters are assumed to be unknown and will be adjusted adaptively as well as the sign function being introduced to compensate the dead-zone. With the aid of the Lyapunov analysis method, the stability of the closed-loop system is proven. A simulation example is provided to illustrate the feasibility of the control algorithm presented in this paper.

  11. Design and Experimental Evaluation of a Robust Position Controller for an Electrohydrostatic Actuator Using Adaptive Antiwindup Sliding Mode Scheme

    PubMed Central

    Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

    2013-01-01

    A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. PMID:23983640

  12. Design and experimental evaluation of a robust position controller for an electrohydrostatic actuator using adaptive antiwindup sliding mode scheme.

    PubMed

    Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

    2013-01-01

    A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities.

  13. Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

    PubMed

    Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

    2014-11-01

    This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system. PMID:25330468

  14. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques.

    PubMed

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2016-04-21

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  15. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    NASA Astrophysics Data System (ADS)

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E.; Lo, Yeh-Chi

    2016-04-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  16. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques.

    PubMed

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2016-04-21

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. PMID:27008349

  17. Towards a robust methodology to assess coastal impacts and adaptation policies for Europe

    NASA Astrophysics Data System (ADS)

    Vousdoukas, Michalis; Voukouvalas, Evangelos; Mentaschi, Lorenzo; Feyen, Luc

    2016-04-01

    The present contribution aims to present preliminary results from efforts towards (i) the development of the integrated risk assessment tool LISCoAsT for Europe (Large scale Integrated Sea-level and Coastal Assessment Tool); (ii) the assessment of coastal risk along the European coastline in view of climate change; and (iii) the development and application of a robust methodology to evaluate adaptation options for the European coastline under climate change scenarios. The overall approach builds on the disaster risk methodology proposed by the IPCC SREX (2012) report, defining risk as the combination of hazard, exposure and vulnerability. Substantial effort has been put in all the individual components of the risk assessment chain, including: (1) the development of dynamic scenarios of catastrophic coastal hazards (e.g., storm surges, sea-level rise) in view of climate change; (2) quantification, mapping and forecasting exposure and vulnerability in coastal areas; (3) carrying out a bottom-up, highly disaggregated assessment of climate impacts on coastal areas in Europe in view of global warming; (4) estimating the costs and assessing the effectiveness of different adaptation options. Projections indicate that, by the end of this century, sea levels in Europe will rise on average between 45 and 70 cm; while projections of coastal hazard showed that for some European regions, the increased storminess can be an additional significant driver of further risk. Projections of increasing extreme storm surge levels (SSL) were even more pronounced under the business-as-usual RCP8.5 concentration pathway, in particular along the Northern Europe coastline. The above are also reflected in the coastal impact projections, which show a significant increase in the expected annual damage (EAD) from coastal flooding. The present EAD for Europe of 800 million €/year is projected to increase up to 2.4 and 3.2 billion €/year by 2040 under RCP 4.5 and 8.5, respectively, and to 11

  18. A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

    NASA Astrophysics Data System (ADS)

    Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

    This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

  19. Finite time-Lyapunov based approach for robust adaptive control of wind-induced oscillations in power transmission lines

    NASA Astrophysics Data System (ADS)

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2016-06-01

    Large amplitude oscillation of the power transmission lines, which is also known as galloping phenomenon, has hazardous consequences such as short circuiting and failure of transmission line. In this article, to suppress the undesirable vibrations of the transmission lines, first the governing equations of transmission line are derived via mode summation technique. Then, due to the occurrence of large amplitude vibrations, nonlinear quadratic and cubic terms are included in the derived linear equations. To suppress the vibrations, arbitrary number of the piezoelectric actuators is assumed to exert the actuation forces. Afterwards, a Lyapunov based approach is proposed for the robust adaptive suppression of the undesirable vibrations in the finite time. To compensate the supposed parametric uncertainties with unknown bands, proper adaption laws are introduced. To avoid the vibration devastating consequences as quickly as possible, appropriate control laws are designed. The vibration suppression in the finite time with supposed adaption and control laws is mathematically proved via Lyapunov finite time stability theory. Finally, to illustrate and validate the efficiency and robustness of the proposed finite time control scheme, a parametric case study with three piezoelectric actuators is performed. It is observed that the proposed active control strategy is more efficient and robust than the passive control methods.

  20. Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier.

    PubMed

    Lai, Guanyu; Liu, Zhi; Zhang, Yun; Chen, C L Philip

    2016-01-01

    This paper presents a novel adaptive controller for controlling an autonomous helicopter with unknown inertial matrix to asymptotically track the desired trajectory. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Using the NNs to compensate the unknown aerodynamic forces online and the robust adaptive mechanism to cancel the combination of the overlarge NNs compensation error and the external disturbances, the new robust neural identifier exhibits a better identification performance in the complex flight environment. Moreover, an optimized algorithm is included in the NNs mechanism to alleviate the burdensome online computation. By the strict Lyapunov argument, the asymptotic convergence of the inertial matrix identification error, position tracking error, and attitude tracking error to arbitrarily small neighborhood of the origin is proved. The simulation and implementation results are provided to evaluate the performance of the proposed controller. PMID:25794402

  1. A Fast and Robust Poisson-Boltzmann Solver Based on Adaptive Cartesian Grids.

    PubMed

    Boschitsch, Alexander H; Fenley, Marcia O

    2011-05-10

    An adaptive Cartesian grid (ACG) concept is presented for the fast and robust numerical solution of the 3D Poisson-Boltzmann Equation (PBE) governing the electrostatic interactions of large-scale biomolecules and highly charged multi-biomolecular assemblies such as ribosomes and viruses. The ACG offers numerous advantages over competing grid topologies such as regular 3D lattices and unstructured grids. For very large biological molecules and multi-biomolecule assemblies, the total number of grid-points is several orders of magnitude less than that required in a conventional lattice grid used in the current PBE solvers thus allowing the end user to obtain accurate and stable nonlinear PBE solutions on a desktop computer. Compared to tetrahedral-based unstructured grids, ACG offers a simpler hierarchical grid structure, which is naturally suited to multigrid, relieves indirect addressing requirements and uses fewer neighboring nodes in the finite difference stencils. Construction of the ACG and determination of the dielectric/ionic maps are straightforward, fast and require minimal user intervention. Charge singularities are eliminated by reformulating the problem to produce the reaction field potential in the molecular interior and the total electrostatic potential in the exterior ionic solvent region. This approach minimizes grid-dependency and alleviates the need for fine grid spacing near atomic charge sites. The technical portion of this paper contains three parts. First, the ACG and its construction for general biomolecular geometries are described. Next, a discrete approximation to the PBE upon this mesh is derived. Finally, the overall solution procedure and multigrid implementation are summarized. Results obtained with the ACG-based PBE solver are presented for: (i) a low dielectric spherical cavity, containing interior point charges, embedded in a high dielectric ionic solvent - analytical solutions are available for this case, thus allowing rigorous

  2. Robustness and adaptation reveal plausible cell cycle controlling subnetwork in Saccharomyces cerevisiae.

    PubMed

    Huang, Jiun-Yan; Huang, Chi-Wei; Kao, Kuo-Ching; Lai, Pik-Yin

    2013-04-10

    Biological systems are often organized spatially and temporally by multi-scale functional subsystems (modules). A specific subcellular process often corresponds to a subsystem composed of some of these interconnected modules. Accurate identification of system-level modularity organization from the large scale networks can provide valuable information on subsystem models of subcellular processes or physiological phenomena. Computational identification of functional modules from the large scale network is the key approach to solve the complexity of modularity in the past decade, but the overlapping and multi-scale nature of modules often renders unsatisfactory results in these methods. Most current methods for modularity detection are optimization-based and suffered from the drawback of size resolution limit. It is difficult to trace the origin of the unsatisfactory results, which may be due to poor data, inappropriate objective function selection or simply resulted from natural evolution, and hence no system-level accurate modular models for subcellular processes can be offered. Motivated by the idea of evolution with robustness and adaption as guiding principles, we propose a novel approach that can identify significant multi-scale overlapping modules that are sufficiently accurate at the system and subsystem levels, giving biological insights for subcellular processes. The success of our evolution strategy method is demonstrated by applying to the yeast protein-protein interaction network. Functional subsystems of important physiological phenomena can be revealed. In particular, the cell cycle controlling network is selected for detailed discussion. The cell cycle subcellular processes in yeast can be successfully dissected into functional modules of cell cycle control, cell size check point, spindle assembly checkpoint, and DNA damage check point in G2/M and S phases. The interconnections between check points and cell cycle control modules provide clues on the

  3. Robust image transmission using a new joint source channel coding algorithm and dual adaptive OFDM

    NASA Astrophysics Data System (ADS)

    Farshchian, Masoud; Cho, Sungdae; Pearlman, William A.

    2004-01-01

    In this paper we consider the problem of robust image coding and packetization for the purpose of communications over slow fading frequency selective channels and channels with a shaped spectrum like those of digital subscribe lines (DSL). Towards this end, a novel and analytically based joint source channel coding (JSCC) algorithm to assign unequal error protection is presented. Under a block budget constraint, the image bitstream is de-multiplexed into two classes with different error responses. The algorithm assigns unequal error protection (UEP) in a way to minimize the expected mean square error (MSE) at the receiver while minimizing the probability of catastrophic failure. In order to minimize the expected mean square error at the receiver, the algorithm assigns unequal protection to the value bit class (VBC) stream. In order to minimizes the probability of catastrophic error which is a characteristic of progressive image coders, the algorithm assigns more protection to the location bit class (LBC) stream than the VBC stream. Besides having the advantage of being analytical and also numerically solvable, the algorithm is based on a new formula developed to estimate the distortion rate (D-R) curve for the VBC portion of SPIHT. The major advantage of our technique is that the worst case instantaneous minimum peak signal to noise ratio (PSNR) does not differ greatly from the averge MSE while this is not the case for the optimal single stream (UEP) system. Although both average PSNR of our method and the optimal single stream UEP are about the same, our scheme does not suffer erratic behavior because we have made the probability of catastrophic error arbitarily small. The coded image is sent via orthogonal frequency division multiplexing (OFDM) which is a known and increasing popular modulation scheme to combat ISI (Inter Symbol Interference) and impulsive noise. Using dual adaptive energy OFDM, we use the minimum energy necessary to send each bit stream at a

  4. Simple robust control laws for robot manipulators. Part 2: Adaptive case

    NASA Technical Reports Server (NTRS)

    Bayard, D. S.; Wen, J. T.

    1987-01-01

    A new class of asymptotically stable adaptive control laws is introduced for application to the robotic manipulator. Unlike most applications of adaptive control theory to robotic manipulators, this analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and utilizes a parameterization based on physical (time-invariant) quantities. This approach is made possible by using energy-like Lyapunov functions which retain the nonlinear character and structure of the dynamics, rather than simple quadratic forms which are ubiquitous to the adaptive control literature, and which have bound the theory tightly to linear systems with unknown parameters. It is a unique feature of these results that the adaptive forms arise by straightforward certainty equivalence adaptation of their nonadaptive counterparts found in the companion to this paper (i.e., by replacing unknown quantities by their estimates) and that this simple approach leads to asymptotically stable closed-loop adaptive systems. Furthermore, it is emphasized that this approach does not require convergence of the parameter estimates (i.e., via persistent excitation), invertibility of the mass matrix estimate, or measurement of the joint accelerations.

  5. A Robust and Scalable Software Library for Parallel Adaptive Refinement on Unstructured Meshes

    NASA Technical Reports Server (NTRS)

    Lou, John Z.; Norton, Charles D.; Cwik, Thomas A.

    1999-01-01

    The design and implementation of Pyramid, a software library for performing parallel adaptive mesh refinement (PAMR) on unstructured meshes, is described. This software library can be easily used in a variety of unstructured parallel computational applications, including parallel finite element, parallel finite volume, and parallel visualization applications using triangular or tetrahedral meshes. The library contains a suite of well-designed and efficiently implemented modules that perform operations in a typical PAMR process. Among these are mesh quality control during successive parallel adaptive refinement (typically guided by a local-error estimator), parallel load-balancing, and parallel mesh partitioning using the ParMeTiS partitioner. The Pyramid library is implemented in Fortran 90 with an interface to the Message-Passing Interface (MPI) library, supporting code efficiency, modularity, and portability. An EM waveguide filter application, adaptively refined using the Pyramid library, is illustrated.

  6. Robust projective lag synchronization in drive-response dynamical networks via adaptive control

    NASA Astrophysics Data System (ADS)

    Al-mahbashi, G.; Noorani, M. S. Md; Bakar, S. A.; Al-sawalha, M. M.

    2016-02-01

    This paper investigates the problem of projective lag synchronization behavior in drive-response dynamical networks (DRDNs) with identical and non-identical nodes. An adaptive control method is designed to achieve projective lag synchronization with fully unknown parameters and unknown bounded disturbances. These parameters were estimated by adaptive laws obtained by Lyapunov stability theory. Furthermore, sufficient conditions for synchronization are derived analytically using the Lyapunov stability theory and adaptive control. In addition, the unknown bounded disturbances are also overcome by the proposed control. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Simulation results show the effectiveness of the proposed method.

  7. Robust vibration suppression of an adaptive circular composite plate for satellite thrust vector control

    NASA Astrophysics Data System (ADS)

    Yan, Su; Ma, Kougen; Ghasemi-Nejhad, Mehrdad N.

    2008-03-01

    In this paper, a novel application of adaptive composite structures, a University of Hawaii at Manoa (UHM) smart composite platform, is developed for the Thrust Vector Control (TVC) of satellites. The device top plate of the UHM platform is an adaptive circular composite plate (ACCP) that utilizes integrated sensors/actuators and controllers to suppress low frequency vibrations during the thruster firing as well as to potentially isolate dynamic responses from the satellite structure bus. Since the disturbance due to the satellite thruster firing can be estimated, a combined strategy of an adaptive disturbance observer (DOB) and feed-forward control is proposed for vibration suppression of the ACCP with multi-sensors and multi-actuators. Meanwhile, the effects of the DOB cut-off frequency and the relative degree of the low-pass filter on the DOB performance are investigated. Simulations and experimental results show that higher relative degree of the low-pass filter with the required cut-off frequency will enhance the DOB performance for a high-order system control. Further, although the increase of the filter cut-off frequency can guarantee a sufficient stability margin, it may cause an undesirable increase of the control bandwidth. The effectiveness of the proposed adaptive DOB with feed-forward control strategy is verified through simulations and experiments using the ACCP system.

  8. Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

    NASA Astrophysics Data System (ADS)

    Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

    2009-10-01

    A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.

  9. Multiobjective control design including performance robustness for gust alleviation of a wing with adaptive material actuators

    NASA Astrophysics Data System (ADS)

    Layton, Jeffrey B.

    1997-06-01

    The goal of this paper is to examine the use of covariance control to directly design reduced-order multi-objective controllers for gust alleviation using adaptive materials as the control effector. It will use piezoelectric actuators as control effectors in a finite element model of a full-size wing model. More precisely, the finite element model is of the F-16 Agile Falcon/Active Flexible Wing that is modified to use piezoelectric actuators as control effectors. The paper will also examine the interacting roles of important control design constraints and objectives for designing an aeroservoelastic system. The paper will also present some results of multiobjective control design for the model, illustrating the benefits and complexity of modern practical control design for aeroservoelastic systems that use adaptive materials for actuation.

  10. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    PubMed

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed. PMID:26606851

  11. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    PubMed

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed.

  12. A fast converging robust controller using adaptive second order sliding mode.

    PubMed

    Mondal, Sanjoy; Mahanta, Chitralekha

    2012-11-01

    This paper proposes an adaptive second order sliding mode (SOSM) controller with a nonlinear sliding surface. The nonlinear sliding surface consists of a gain matrix having a variable damping ratio. Initially the sliding surface uses a low value of damping ratio to get a quick system response. As the closed loop system approaches the desired reference, the value of the damping ratio gets increased with an aim to reducing the overshoot and the settling time. The time derivative of the control signal is used to design the controller. The actual control input obtained by integrating the derivative control signal is smooth and chattering free. The adaptive tuning law used by the proposed controller eliminates the need of prior knowledge about the upper bound of system uncertainties. Simulation results demonstrate the effectiveness of the proposed control strategy.

  13. Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

    NASA Astrophysics Data System (ADS)

    Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

    2014-07-01

    Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This

  14. Robust Adaptive 3-D Segmentation of Vessel Laminae From Fluorescence Confocal Microscope Images and Parallel GPU Implementation

    PubMed Central

    Narayanaswamy, Arunachalam; Dwarakapuram, Saritha; Bjornsson, Christopher S.; Cutler, Barbara M.; Shain, William

    2010-01-01

    This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8× speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.1–1.6) voxels per mesh face for peak signal-to-noise ratios from (110–28 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively. PMID:20199906

  15. Multibeam echosounder data cleaning through a hierarchic adaptive and robust local surfacing

    NASA Astrophysics Data System (ADS)

    Debese, Nathalie; Moitié, Rodéric; Seube, Nicolas

    2012-09-01

    Multibeam echo sounders (MBES) datasets generally contain sporadic outlier points. The huge volumes of MBES datasets in a hydrographic framework require the use of semi-automatic techniques. In very shallow waters depth, data cleaning becomes a challenging task when potential dangers to navigation have to be carefully checked. The aim of our paper is to attempt this goal by combining two well-known techniques. The seafloor is constructed as an assemblage of surface elements with the help of a robust statistical approach. The local parameters model is a priori chosen, its scale is driven through a quadtree descending approach using subdivision rules based on both statistical and spatio-temporal inferences. Our multi resolution approach provides, with the algorithm outputs, a classification map that notes areas of concern.

  16. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    NASA Astrophysics Data System (ADS)

    Rossant, Florence; Bloch, Isabelle

    2006-12-01

    This paper describes a system for optical music recognition (OMR) in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  17. Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

    PubMed Central

    Wang, Ruliang; Li, Jie; Zhang, Shanshan; Gao, Dongmei; Sun, Huanlong

    2013-01-01

    We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme. PMID:23853544

  18. Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

    PubMed Central

    Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

    2015-01-01

    Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

  19. An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles.

    PubMed

    Johansson, A Torbjorn; White, Paul R

    2011-08-01

    This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances. PMID:21877804

  20. Demonstration of a 17 cm robust carbon fiber deformable mirror for adaptive optics

    SciTech Connect

    Ammons, S M; Hart, M; Coughenour, B; Romeo, R; Martin, R; Rademacher, M

    2011-09-12

    Carbon-fiber reinforced polymer (CFRP) composite is an attractive material for fabrication of optics due to its high stiffness-to-weight ratio, robustness, zero coefficient of thermal expansion (CTE), and the ability to replicate multiple optics from the same mandrel. We use 8 and 17 cm prototype CFRP thin-shell deformable mirrors to show that residual CTE variation may be addressed with mounted actuators for a variety of mirror sizes. We present measurements of surface quality at a range of temperatures characteristic of mountaintop observatories. For the 8 cm piece, the figure error of the Al-coated reflective surface under best actuator correction is {approx}43 nm RMS. The 8 cm mirror has a low surface error internal to the outer ring of actuators (17 nm RMS at 20 C and 33 nm RMS at -5 C). Surface roughness is low (< 3 nm P-V) at a variety of temperatures. We present new figure quality measurements of the larger 17 cm mirror, showing that the intra-actuator figure error internal to the outer ring of actuators (38 nm RMS surface with one-third the actuator density of the 8 cm mirror) does not scale sharply with mirror diameter.

  1. Robust adaptive integrated translation and rotation control of a rigid spacecraft with control saturation and actuator misalignment

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guangren

    2013-05-01

    This paper handles the integrated translation and rotation tracking control problem of a rigid spacecraft with unknown mass property, actuator misalignment and control saturation. In view of the system natural coupling, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment is taken into account. By using anti-windup technique and backstepping philosophy, a robust adaptive integrated control scheme is proposed such that the spacecraft is able to track the command position and attitude signals in the presence of external disturbance, unknown mass property, thruster misalignment and control saturation. Within the Lyapunov framework, the uniformly ultimate boundedness of the system states is guaranteed. In particular, given the nominal case, the asymptotic convergence of the system states can be further ensured by the proposed control scheme. Finally, numerical simulation demonstrates the effect of the designed control strategy.

  2. An experimental comparison of proportional-integral, sliding mode, and robust adaptive control for piezo-actuated nanopositioning stages.

    PubMed

    Gu, Guo-Ying; Zhu, Li-Min

    2014-05-01

    This paper presents a comparative study of the proportional-integral (PI) control, sliding mode control (SMC), and robust adaptive control (RAC) for applications to piezo-actuated nanopositioning stages without the inverse hysteresis construction. For a fair comparison, the control parameters of the SMC and RAC are selected on the basis of the well-tuned parameters of the PI controller under same desired trajectories and sampling frequencies. The comparative results show that the RAC improves the tracking performance by 17 and 37 times than the PI controller in terms of the maximum tracking error e(m) and the root mean tracking error e(rms), respectively, while the RAC improves the tracking performance by 7 and 9 times than the SMC in terms of e(m) and e(rms), respectively.

  3. Investigation of the robustness of adaptive neuro-fuzzy inference system for tracking moving tumors in external radiotherapy.

    PubMed

    Torshabi, Ahmad Esmaili

    2014-12-01

    In external radiotherapy of dynamic targets such as lung and breast cancers, accurate correlation models are utilized to extract real time tumor position by means of external surrogates in correlation with the internal motion of tumors. In this study, a correlation method based on the neuro-fuzzy model is proposed to correlate the input external motion data with internal tumor motion estimation in real-time mode, due to its robustness in motion tracking. An initial test of the performance of this model was reported in our previous studies. In this work by implementing some modifications it is resulted that ANFIS is still robust to track tumor motion more reliably by reducing the motion estimation error remarkably. After configuring new version of our ANFIS model, its performance was retrospectively tested over ten patients treated with Synchrony Cyberknife system. In order to assess the performance of our model, the predicted tumor motion as model output was compared with respect to the state of the art model. Final analyzed results show that our adaptive neuro-fuzzy model can reduce tumor tracking errors more significantly, as compared with ground truth database and even tumor tracking methods presented in our previous works. PMID:25412886

  4. Robust semi-automatic segmentation of single- and multichannel MRI volumes through adaptable class-specific representation

    NASA Astrophysics Data System (ADS)

    Nielsen, Casper F.; Passmore, Peter J.

    2002-05-01

    Segmentation of MRI volumes is complicated by noise, inhomogeneity and partial volume artefacts. Fully or semi-automatic methods often require time consuming or unintuitive initialization. Adaptable Class-Specific Representation (ACSR) is a semi-automatic segmentation framework implemented by the Path Growing Algorithm (PGA), which reduces artefacts near segment boundaries. The user visually defines the desired segment classes through the selection of class templates and the following segmentation process is fully automatic. Good results have previously been achieved with color cryo section segmentation and ACSR has been developed further for the MRI modality. In this paper we present two optimizations for robust ACSR segmentation of MRI volumes. Automatic template creation based on an initial segmentation step using Learning Vector Quantization is applied for higher robustness to noise. Inhomogeneity correction is added as a pre-processing step, comparing the EQ and N3 algorithms. Results based on simulated T1-weighed and multispectral (T1 and T2) MRI data from the BrainWeb database and real data from the Internet Brain Segmentation Repository are presented. We show that ACSR segmentation compares favorably to previously published results on the same volumes and discuss the pros and cons of using quantitative ground truth evaluation compared to qualitative visual assessment.

  5. Biologically-inspired robust and adaptive multi-sensor fusion and active control

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Dow, Paul A.; Huber, David J.

    2009-04-01

    In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space; (2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them; and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt- zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs.

  6. Adapting to a Changing Colorado River: Making Future Water Deliveries More Reliable Through Robust Management Strategies

    NASA Astrophysics Data System (ADS)

    Groves, D.; Bloom, E.; Fischbach, J. R.; Knopman, D.

    2013-12-01

    The U.S. Bureau of Reclamation and water management agencies representing the seven Colorado River Basin States initiated the Colorado River Basin Study in January 2010 to evaluate the resiliency of the Colorado River system over the next 50 years and compare different options for ensuring successful management of the river's resources. RAND was asked to join this Basin Study Team in January 2012 to help develop an analytic approach to identify key vulnerabilities in managing the Colorado River basin over the coming decades and to evaluate different options that could reduce this vulnerability. Using a quantitative approach for planning under uncertainty called Robust Decision Making (RDM), the RAND team assisted the Basin Study by: identifying future vulnerable conditions that could lead to imbalances that could cause the basin to be unable to meet its water delivery objectives; developing a computer-based tool to define 'portfolios' of management options reflecting different strategies for reducing basin imbalances; evaluating these portfolios across thousands of future scenarios to determine how much they could improve basin outcomes; and analyzing the results from the system simulations to identify key tradeoffs among the portfolios. This talk will describe RAND's contribution to the Basin Study, focusing on the methodologies used to to identify vulnerabilities for Upper Basin and Lower Basin water supply reliability and to compare portfolios of options. Several key findings emerged from the study. Future Streamflow and Climate Conditions Are Key: - Vulnerable conditions arise in a majority of scenarios where streamflows are lower than historical averages and where drought conditions persist for eight years or more. - Depending where the shortages occur, problems will arise for delivery obligations for the upper river basin and the lower river basin. The lower river basin is vulnerable to a broader range of plausible future conditions. Additional Investments in

  7. Robust fundamental frequency estimation in sustained vowels: Detailed algorithmic comparisons and information fusion with adaptive Kalman filtering

    PubMed Central

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.

    2014-01-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269

  8. Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model.

    PubMed

    Maindal, Helle Terkildsen; Kayser, Lars; Norgaard, Ole; Bo, Anne; Elsworth, Gerald R; Osborne, Richard H

    2016-01-01

    Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

  9. Robust fundamental frequency estimation in sustained vowels: detailed algorithmic comparisons and information fusion with adaptive Kalman filtering.

    PubMed

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A; Fox, Cynthia; Ramig, Lorraine O; Clifford, Gari D

    2014-05-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F(0)) of speech signals. This study examines ten F(0) estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F(0) in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F(0) estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F(0) estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F(0) estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F(0) estimation is required. PMID:24815269

  10. Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model.

    PubMed

    Maindal, Helle Terkildsen; Kayser, Lars; Norgaard, Ole; Bo, Anne; Elsworth, Gerald R; Osborne, Richard H

    2016-01-01

    Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes. PMID:27536516

  11. Science-society collaboration for robust adaptation planning in water management - The Maipo River Basin in Chile

    NASA Astrophysics Data System (ADS)

    Ocampo Melgar, Anahí; Vicuña, Sebastián; Gironás, Jorge

    2015-04-01

    The Metropolitan Region (M.R.) in Chile is populated by over 6 million people and supplied by the Maipo River and its large number of irrigation channels. Potential environmental alterations caused by global change will extremely affect managers and users of water resources in this semi-arid basin. These hydro-climatological impacts combined with demographic and economic changes will be particularly complex in the city of Santiago, due to the diverse, counterpoised and equally important existing activities and demands. These challenges and complexities request the implementation of flexible plans and actions to adapt policies, institutions, infrastructure and behaviors to a new future with climate change. Due to the inherent uncertainties in the future, a recent research project entitled MAPA (Maipo Adaptation Plan for its initials in Spanish) has formed a collaborative science-society platform to generate insights into the vulnerabilities, challenges and possible mitigation measures that would be necessary to deal with the potential changes in the M.R. This large stakeholder platform conformed by around 30 public, private and civil society organizations, both at the local and regional level and guided by a Robust Decision Making Framework (RDMF) has identified vulnerabilities, future scenarios, performance indicators and mitigation measures for the Maipo River basin. The RDMF used in this project is the XLRM framework (Lempert et al. 2006) that incorporates policy levers (L), exogenous uncertainties (X), measures of performance standards (M) and relationships (R) in an interlinked process. Both stakeholders' expertise and computational capabilities have been used to create hydrological models for the urban, rural and highland sectors supported also by the Water Evaluation and Planning system software (WEAP). The identification of uncertainties and land use transition trends was used to develop future development scenarios to explore possible water management

  12. A model of the effects of authority on consensus formation in adaptive networks: Impact on network topology and robustness

    NASA Astrophysics Data System (ADS)

    Prettejohn, Brenton J.; Berryman, Matthew J.; McDonnell, Mark D.

    2013-02-01

    Opinions of individuals in real social networks are arguably strongly influenced by external determinants, such as the opinions of those perceived to have the highest levels of authority. In order to model this, we have extended an existing model of consensus formation in an adaptive network by the introduction of a parameter representing each agent’s level of ‘authority’, based on their opinion relative to the overall opinion distribution. We found that introducing this model, along with a randomly varying opinion convergence factor, significantly impacts the final state of converged opinions and the number of interactions required to reach that state. We also determined the relationship between initial and final network topologies for this model, and whether the final topology is robust to node removals. Our results indicate firstly that the process of consensus formation with a model of authority consistently transforms the network from an arbitrary initial topology to one with distinct measurements in mean shortest path, clustering coefficient, and degree distribution. Secondly, we found that subsequent to the consensus formation process, the mean shortest path and clustering coefficient are less affected by both random and targeted node disconnection. Speculation on the relevance of these results to real world applications is provided.

  13. Image copy-move forgery detection based on sped-up robust features descriptor and adaptive minimal-maximal suppression

    NASA Astrophysics Data System (ADS)

    Yang, Bin; Sun, Xingming; Xin, Xiangyang; Hu, Weifeng; Wu, Youxin

    2015-11-01

    Region duplication is a simple and effective operation to create digital image forgeries, where a continuous portion of pixels in an image is copied and pasted to a different location in the same image. Many prior copy-move forgery detection methods suffer from their inability to detect the duplicated region, which is subjected to various geometric transformations. A keypoint-based approach is proposed to detect the copy-move forgery in an image. Our method starts by extracting the keypoints through a fast Hessian detector. Then the adaptive minimal-maximal suppression (AMMS) strategy is developed for distributing the keypoints evenly throughout an image. By using AMMS and a sped-up robust feature descriptor, the proposed method is able to deal with the problem of insufficient keypoints in the almost uniform area. Finally, the geometric transformation performed in cloning is recovered by using the maximum likelihood estimation of the homography. Experimental results show the efficacy of this technique in detecting copy-move forgeries and estimating the geometric transformation parameters. Compared with the state of the art, our approach obtains a higher true positive rate and a lower false positive rate.

  14. Energy Landscape Reveals That the Budding Yeast Cell Cycle Is a Robust and Adaptive Multi-stage Process

    PubMed Central

    Lv, Cheng; Li, Xiaoguang; Li, Fangting; Li, Tiejun

    2015-01-01

    Quantitatively understanding the robustness, adaptivity and efficiency of cell cycle dynamics under the influence of noise is a fundamental but difficult question to answer for most eukaryotic organisms. Using a simplified budding yeast cell cycle model perturbed by intrinsic noise, we systematically explore these issues from an energy landscape point of view by constructing an energy landscape for the considered system based on large deviation theory. Analysis shows that the cell cycle trajectory is sharply confined by the ambient energy barrier, and the landscape along this trajectory exhibits a generally flat shape. We explain the evolution of the system on this flat path by incorporating its non-gradient nature. Furthermore, we illustrate how this global landscape changes in response to external signals, observing a nice transformation of the landscapes as the excitable system approaches a limit cycle system when nutrients are sufficient, as well as the formation of additional energy wells when the DNA replication checkpoint is activated. By taking into account the finite volume effect, we find additional pits along the flat cycle path in the landscape associated with the checkpoint mechanism of the cell cycle. The difference between the landscapes induced by intrinsic and extrinsic noise is also discussed. In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems. PMID:25794282

  15. Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

    PubMed

    Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

    2014-09-01

    This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy.

  16. Evaluating the need for integrated land use and land cover analysis for robust assessment of climate adaptation and mitigation strategies

    NASA Astrophysics Data System (ADS)

    Di Vittorio, Alan; Mao, Jiafu; Shi, Xiaoying

    2016-04-01

    LULCC scenarios in earth system simulations to provide robust historical and future projections of carbon and climate, especially when incorporating climate feedbacks on human and environmental systems. More accurate LULCC scenarios will also improve impact and resource sustainability analyses in the context of climate adaptation and mitigation strategies. These new scenarios will need to be developed and implemented as an integrated process with interdependent land use and land cover to adequately incorporate human and environmental drivers of LULCC.

  17. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    NASA Astrophysics Data System (ADS)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  18. Observer-Based Magnetic Bearing Controller Developed for Aerospace Flywheels

    NASA Technical Reports Server (NTRS)

    Le, Dzu K.; Provenza, Andrew J.

    2002-01-01

    -axis position input data. Actual flywheel tests of this observer-based controller (developed entirely in-house) at the NASA Glenn Research Center showed that the model correctly predicted the rotor orbit growth as a function of rotational speed, and it demonstrated the capability of gain adjustments to arrest this growth. Data from these tests on an actual flywheel module spun to 26,000 rpm proved that the controller was able to contain the shaft motion to within much less than 0.5 mils of radial excursion with axis currents less than 300 mA in root-mean-square estimate. The test speed range was limited because of thermal expansion concerns for this particular flywheel unit, not because of any deficiency in the controller. Simulations for this unit indicated that the controller should be robust up to its top operating speed of 60,000 rpm. Aside from these important achievements, and most significantly, it took less than 1 week to adapt this controller from the simple test rig to the actual flywheel and to demonstrate full five-axis levitation and control. This demonstration showed that both the controller and the model-based development and tuning framework are easily adaptable to a wide range of rotors and bearing configurations and, hence, are capable of reducing design risks and costs for many future flywheel technology developments.

  19. Adaptive marker-free registration using a multiple point strategy for real-time and robust endoscope electromagnetic navigation.

    PubMed

    Luo, Xiongbiao; Wan, Ying; He, Xiangjian; Mori, Kensaku

    2015-02-01

    Registration of pre-clinical images to physical space is indispensable for computer-assisted endoscopic interventions in operating rooms. Electromagnetically navigated endoscopic interventions are increasingly performed at current diagnoses and treatments. Such interventions use an electromagnetic tracker with a miniature sensor that is usually attached at an endoscope distal tip to real time track endoscope movements in a pre-clinical image space. Spatial alignment between the electromagnetic tracker (or sensor) and pre-clinical images must be performed to navigate the endoscope to target regions. This paper proposes an adaptive marker-free registration method that uses a multiple point selection strategy. This method seeks to address an assumption that the endoscope is operated along the centerline of an intraluminal organ which is easily violated during interventions. We introduce an adaptive strategy that generates multiple points in terms of sensor measurements and endoscope tip center calibration. From these generated points, we adaptively choose the optimal point, which is the closest to its assigned the centerline of the hollow organ, to perform registration. The experimental results demonstrate that our proposed adaptive strategy significantly reduced the target registration error from 5.32 to 2.59 mm in static phantoms validation, as well as from at least 7.58 mm to 4.71 mm in dynamic phantom validation compared to current available methods.

  20. Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

    PubMed

    Bagheri, Pedram; Sun, Qiao

    2016-07-01

    In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers.

  1. Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

    PubMed

    Bagheri, Pedram; Sun, Qiao

    2016-07-01

    In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. PMID:27157849

  2. Robust DTC Based on Adaptive Fuzzy Control of Double Star Synchronous Machine Drive with Fixed Switching Frequency

    NASA Astrophysics Data System (ADS)

    Boudana, Djamel; Nezli, Lazhari; Tlemçani, Abdelhalim; Mahmoudi, Mohand Oulhadj; Tadjine, Mohamed

    2012-05-01

    The double star synchronous machine (DSSM) is widely used for high power traction drives. It possesses several advantages over the conventional three phase machine. To reduce the torque ripple the DSSM are supplied with source voltage inverter (VSI). The model of the system DSSM-VSI is high order, multivariable and nonlinear. Further, big harmonic currents are generated. The aim of this paper is to develop a new direct torque adaptive fuzzy logic control in order to control DSSM and minimize the harmonics currents. Simulations results are given to show the effectiveness of our approach.

  3. Sterile inflammation induced by Carbopol elicits robust adaptive immune responses in the absence of pathogen-associated molecular patterns

    PubMed Central

    Gartlan, Kate H.; Krashias, George; Wegmann, Frank; Hillson, William R.; Scherer, Erin M.; Greenberg, Philip D.; Eisenbarth, Stephanie C.; Moghaddam, Amin E.; Sattentau, Quentin J.

    2016-01-01

    Carbopol is a polyanionic carbomer used in man for topical application and drug delivery purposes. However parenteral administration of Carbopol in animal models results in systemic adjuvant activity including strong pro-inflammatory type-1 T-cell (Th1) polarization. Here we investigated potential pathways of immune activation by Carbopol by comparison with other well-characterized adjuvants. Carbopol administration triggered rapid and robust leukocyte recruitment, pro-inflammatory cytokine secretion and antigen capture largely by inflammatory monocytes. The induction of antigen specific Th1 cells by Carbopol was found to occur via a non-canonical pathway, independent of MyD88/TRIF signaling and in the absence of pattern-recognition-receptor (PRR) activation typically associated with Th1/Ig2a induction. Using multispectral fluorescence imaging (Imagestream) and electron microscopy we demonstrated that phagocytic uptake of Carbopol particles followed by entry into the phagosomal/lysosomal pathway elicited conformational changes to the polymer and reactive oxygen species (ROS) production. We therefore conclude that Carbopol may mediate its adjuvant activity via novel mechanisms of antigen presenting cell activation and Th1 induction, leading to enhanced IgG2a responses independent of microbial pattern recognition. PMID:27005810

  4. Robustness and strategies of adaptation among farmer varieties of African Rice (Oryza glaberrima) and Asian Rice (Oryza sativa) across West Africa.

    PubMed

    Mokuwa, Alfred; Nuijten, Edwin; Okry, Florent; Teeken, Béla; Maat, Harro; Richards, Paul; Struik, Paul C

    2013-01-01

    This study offers evidence of the robustness of farmer rice varieties (Oryza glaberrima and O. sativa) in West Africa. Our experiments in five West African countries showed that farmer varieties were tolerant of sub-optimal conditions, but employed a range of strategies to cope with stress. Varieties belonging to the species Oryza glaberrima - solely the product of farmer agency - were the most successful in adapting to a range of adverse conditions. Some of the farmer selections from within the indica and japonica subspecies of O. sativa also performed well in a range of conditions, but other farmer selections from within these two subspecies were mainly limited to more specific niches. The results contradict the rather common belief that farmer varieties are only of local value. Farmer varieties should be considered by breeding programmes and used (alongside improved varieties) in dissemination projects for rural food security.

  5. Robust adaptive integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guang-Ren

    2014-05-01

    This paper tackles the problem of integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property. Due to the system natural couplings, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment and unknown mass property are taken into account. By solving an equivalent designated trajectory tracking problem via backstepping philosophy, a robust adaptive integrated finite-time control scheme is proposed to enable the spacecraft track command position and attitude in a pre-determined time, despite of external disturbance, unknown mass property and thruster misalignment. The finite-time closed-loop stability is guaranteed within the Lyapunov framework. Two scenario numerical simulations demonstrate the effect of the designed controller.

  6. Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

    PubMed

    Bagherpoor, H M; Salmasi, Farzad R

    2015-07-01

    In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance.

  7. Case of Yellow Fever Vaccine–Associated Viscerotropic Disease with Prolonged Viremia, Robust Adaptive Immune Responses, and Polymorphisms in CCR5 and RANTES Genes

    PubMed Central

    Pulendran, Bali; Miller, Joseph; Querec, Troy D.; Akondy, Rama; Moseley, Nelson; Laur, Oscar; Glidewell, John; Monson, Nathan; Zhu, Tuofu; Zhu, Haiying; Staprans, Sylvija; Lee, David; Brinton, Margo A.; Perelygin, Andrey A.; Vellozzi, Claudia; Brachman, Philip; Lalor, Susan; Teuwen, Dirk; Eidex, Rachel B.; Cetron, Marty; Priddy, Frances; del Rio, Carlos; Altman, John; Ahmed, Rafi

    2013-01-01

    Background The live attenuated yellow fever vaccine 17D (YF-17D) is one of the most effective vaccines. Despite its excellent safety record, some cases of viscerotropic adverse events develop, which are sometimes fatal. The mechanisms underlying such events remain a mystery. Here, we present an analysis of the immunologic and genetic factors driving disease in a 64-year-old male who developed viscerotropic symptoms. Methods We obtained clinical, serologic, virologic, immunologic and genetic data on this case patient. Results Viral RNA was detected in the blood 33 days after vaccination, in contrast to the expected clearance of virus by day 7 after vaccination in healthy vaccinees. Vaccination induced robust antigen-specific T and B cell responses, which suggested that persistent virus was not due to adaptive immunity of suboptimal magnitude. The genes encoding OAS1, OAS2, TLR3, and DC-SIGN, which mediate antiviral innate immunity, were wild type. However, there were heterozygous genetic polymorphisms in chemokine receptor CCR5, and its ligand RANTES, which influence the migration of effector T cells and CD14+CD16bright monocytes to tissues. Consistent with this, there was a 200-fold increase in the number of CD14+CD16bright monocytes in the blood during viremia and even several months after virus clearance. Conclusion; In this patient, viscerotropic disease was not due to the impaired magnitude of adaptive immunity but instead to anomalies in the innate immune system and a possible disruption of the CCR5-RANTES axis. PMID:18598196

  8. An adaptable pentaloop defines a robust neomycin-B RNA aptamer with conditional ligand-bound structures

    PubMed Central

    Ilgu, Muslum; Fulton, D. Bruce; Yennamalli, Ragothaman M.; Lamm, Monica H.; Sen, Taner Z.; Nilsen-Hamilton, Marit

    2014-01-01

    Aptamers can be highly specific for their targets, which implies precise molecular recognition between aptamer and target. However, as small polymers, their structures are more subject to environmental conditions than the more constrained longer RNAs such as those that constitute the ribosome. To understand the balance between structural and environmental factors in establishing ligand specificity of aptamers, we examined the RNA aptamer (NEO1A) previously reported as specific for neomycin-B. We show that NEO1A can recognize other aminoglycosides with similar affinities as for neomycin-B and its aminoglycoside specificity is strongly influenced by ionic strength and buffer composition. NMR and 2-aminopurine (2AP) fluorescence studies of the aptamer identified a flexible pentaloop and a stable binding pocket. Consistent with a well-structured binding pocket, docking analysis results correlated with experimental measures of the binding energy for most ligands. Steady state fluorescence studies of 2AP-substituted aptamers confirmed that A16 moves to a more solvent accessible position upon ligand binding while A14 moves to a less solvent accessible position, which is most likely a base stack. Analysis of binding affinities of NEO1A sequence variants showed that the base in position 16 interacts differently with each ligand and the interaction is a function of the buffer constituents. Our results show that the pentaloop provides NEO1A with the ability to adapt to external influences on its structure, with the critical base at position 16 adjusting to incorporate each ligand into a stable pocket by hydrophobic interactions and/or hydrogen bonds depending on the ligand and the ionic environment. PMID:24757168

  9. Robust Adaptation? Assessing the sensitivity of safety margins in flood defences to uncertainty in future simulations - a case study from Ireland.

    NASA Astrophysics Data System (ADS)

    Murphy, Conor; Bastola, Satish; Sweeney, John

    2013-04-01

    Climate change impact and adaptation assessments have traditionally adopted a 'top-down' scenario based approach, where information from different Global Climate Models (GCMs) and emission scenarios are employed to develop impacts led adaptation strategies. Due to the tradeoffs in the computational cost and need to include a wide range of GCMs for fuller characterization of uncertainties, scenarios are better used for sensitivity testing and adaptation options appraisal. One common approach to adaptation that has been defined as robust is the use of safety margins. In this work the sensitivity of safety margins that have been adopted by the agency responsible for flood risk management in Ireland, to the uncertainty in future projections are examined. The sensitivity of fluvial flood risk to climate change is assessed for four Irish catchments using a large number of GCMs (17) forced with three emissions scenarios (SRES A1B, A2, B1) as input to four hydrological models. Both uncertainty within and between hydrological models is assessed using the GLUE framework. Regionalisation is achieved using a change factor method to infer changes in the parameters of a weather generator using monthly output from the GCMs, while flood frequency analysis is conducted using the method of probability weighted moments to fit the Generalised Extreme Value distribution to ~20,000 annual maxima series. The sensitivity of design margins to the uncertainty space considered is visualised using risk response surfaces. The hydrological sensitivity is measured as the percentage change in flood peak for specified recurrence intervals. Results indicate that there is a considerable residual risk associated with allowances of +20% when uncertainties are accounted for and that the risk of exceedence of design allowances is greatest for more extreme, low frequency events with considerable implication for critical infrastructure, e.g., culverts, bridges, flood defences whose designs are normally

  10. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  11. Robust control of accelerators

    SciTech Connect

    Johnson, W.J.D. ); Abdallah, C.T. )

    1990-01-01

    The problem of controlling the variations in the rf power system can be effectively cast as an application of modern control theory. Two components of this theory are obtaining a model and a feedback structure. The model inaccuracies influence the choice of a particular controller structure. Because of the modeling uncertainty, one has to design either a variable, adaptive controller or a fixed, robust controller to achieve the desired objective. The adaptive control scheme usually results in very complex hardware; and, therefore, shall not be pursued in this research. In contrast, the robust control methods leads to simpler hardware. However, robust control requires a more accurate mathematical model of the physical process than is required by adaptive control. Our research at the Los Alamos National Laboratory (LANL) and the University of New Mexico (UNM) has led to the development and implementation of a new robust rf power feedback system. In this paper, we report on our research progress. In section one, the robust control problem for the rf power system and the philosophy adopted for the beginning phase of our research is presented. In section two, the results of our proof-of-principle experiments are presented. In section three, we describe the actual controller configuration that is used in LANL FEL physics experiments. The novelty of our approach is that the control hardware is implemented directly in rf without demodulating, compensating, and then remodulating.

  12. Observer-based monitoring of heat exchangers.

    PubMed

    Astorga-Zaragoza, Carlos-Manuel; Alvarado-Martínez, Víctor-Manuel; Zavala-Río, Arturo; Méndez-Ocaña, Rafael-Maxim; Guerrero-Ramírez, Gerardo-Vicente

    2008-01-01

    The goal of this work is to provide a method for monitoring performance degradation in counter-flow double-pipe heat exchangers. The overall heat transfer coefficient is estimated by an adaptive observer and monitored in order to infer when the heat exchanger needs preventive or corrective maintenance. A simplified mathematical model is used to synthesize the adaptive observer and a more complex model is used for simulation. The reliability of the proposed method was demonstrated via numerical simulations and laboratory experiments with a bench-scale pilot plant. PMID:17706652

  13. Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

    PubMed

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2015-09-01

    To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. PMID:25983065

  14. Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

    PubMed

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2015-09-01

    To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

  15. Modeling and control of nonlinear systems using novel fuzzy wavelet networks: The output adaptive control approach

    NASA Astrophysics Data System (ADS)

    Mousavi, Seyyed Hossein; Noroozi, Navid; Safavi, Ali Akbar; Ebadat, Afrooz

    2011-09-01

    This paper proposes an observer based self-structuring robust adaptive fuzzy wave-net (FWN) controller for a class of nonlinear uncertain multi-input multi-output systems. The control signal is comprised of two parts. The first part arises from an adaptive fuzzy wave-net based controller that approximates the system structural uncertainties. The second part comes from a robust H∞ based controller that is used to attenuate the effect of function approximation error and disturbance. Moreover, a new self structuring algorithm is proposed to determine the location of basis functions. Simulation results are provided for a two DOF robot to show the effectiveness of the proposed method.

  16. Mechanisms of mutational robustness in transcriptional regulation

    PubMed Central

    Payne, Joshua L.; Wagner, Andreas

    2015-01-01

    Robustness is the invariance of a phenotype in the face of environmental or genetic change. The phenotypes produced by transcriptional regulatory circuits are gene expression patterns that are to some extent robust to mutations. Here we review several causes of this robustness. They include robustness of individual transcription factor binding sites, homotypic clusters of such sites, redundant enhancers, transcription factors, redundant transcription factors, and the wiring of transcriptional regulatory circuits. Such robustness can either be an adaptation by itself, a byproduct of other adaptations, or the result of biophysical principles and non-adaptive forces of genome evolution. The potential consequences of such robustness include complex regulatory network topologies that arise through neutral evolution, as well as cryptic variation, i.e., genotypic divergence without phenotypic divergence. On the longest evolutionary timescales, the robustness of transcriptional regulation has helped shape life as we know it, by facilitating evolutionary innovations that helped organisms such as flowering plants and vertebrates diversify. PMID:26579194

  17. Robust Regression.

    PubMed

    Huang, Dong; Cabral, Ricardo; De la Torre, Fernando

    2016-02-01

    Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose estimation from images. These methods typically map image features ( X) to continuous (e.g., pose) or discrete (e.g., object category) values. A major drawback of existing discriminative methods is that samples are directly projected onto a subspace and hence fail to account for outliers common in realistic training sets due to occlusion, specular reflections or noise. It is important to notice that existing discriminative approaches assume the input variables X to be noise free. Thus, discriminative methods experience significant performance degradation when gross outliers are present. Despite its obvious importance, the problem of robust discriminative learning has been relatively unexplored in computer vision. This paper develops the theory of robust regression (RR) and presents an effective convex approach that uses recent advances on rank minimization. The framework applies to a variety of problems in computer vision including robust linear discriminant analysis, regression with missing data, and multi-label classification. Several synthetic and real examples with applications to head pose estimation from images, image and video classification and facial attribute classification with missing data are used to illustrate the benefits of RR. PMID:26761740

  18. Robust acoustic object detection

    NASA Astrophysics Data System (ADS)

    Amit, Yali; Koloydenko, Alexey; Niyogi, Partha

    2005-10-01

    We consider a novel approach to the problem of detecting phonological objects like phonemes, syllables, or words, directly from the speech signal. We begin by defining local features in the time-frequency plane with built in robustness to intensity variations and time warping. Global templates of phonological objects correspond to the coincidence in time and frequency of patterns of the local features. These global templates are constructed by using the statistics of the local features in a principled way. The templates have clear phonetic interpretability, are easily adaptable, have built in invariances, and display considerable robustness in the face of additive noise and clutter from competing speakers. We provide a detailed evaluation of the performance of some diphone detectors and a word detector based on this approach. We also perform some phonetic classification experiments based on the edge-based features suggested here.

  19. Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

    NASA Astrophysics Data System (ADS)

    Shabani, Hikma; Mohamud Ahmed, Musse; Khan, Sheroz; Hameed, Shahab Ahmed; Hadi Habaebi, Mohamed

    2013-12-01

    A smart grid refers to a modernization of the electricity system that brings intelligence, reliability, efficiency and optimality to the power grid. To provide an automated and widely distributed energy delivery, the smart grid will be branded by a two-way flow of electricity and information system between energy suppliers and their customers. Thus, the smart grid is a power grid that integrates data communication networks which provide the collected and analysed data at all levels in real time. Therefore, the performance of communication systems is so vital for the success of smart grid. Merit to the ZigBee/IEEE802.15.4std low cost, low power, low data rate, short range, simplicity and free licensed spectrum that makes wireless sensor networks (WSNs) the most suitable wireless technology for smart grid applications. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In order to improve the performance of communication systems, this paper proposes an optimal throughput and self-adaptability of ZigBee/IEEE802.15.4std for smart grid.

  20. A robust estimation of the exponent function in the Gompertz law

    NASA Astrophysics Data System (ADS)

    Ibarra-Junquera, V.; Monsivais, M. P.; Rosu, H. C.; López-Sandoval, R.

    2006-08-01

    The estimation of the solution of a system of two differential equations introduced by Norton et al. [Predicting the course of Gompertzian growth, Nature 264 (1976) 542-544] that is equivalent to the famous Gompertz growth law is performed by means of the recent adaptive scheme of Besançon and collaborators [High gain observer based state and parameter estimation in nonlinear systems, paper 204, the sixth IFAC Symposium, Stuttgart Symposium on Nonlinear Control Systems (NOLCOS), 2004, available at ]. Results of computer simulations illustrate the robustness of the approach.

  1. How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

    NASA Astrophysics Data System (ADS)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2015-04-01

    In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the

  2. Robust automated knowledge capture.

    SciTech Connect

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  3. Observer-based controller for nonlinear analytical systems

    NASA Astrophysics Data System (ADS)

    Elloumi, S.; Belhouane, M. M.; Benhadj Braiek, N.

    2016-06-01

    In this paper, we propose to design a polynomial observer-based control for nonlinear systems and to determine sufficient linear matrix inequality (LMI) global stabilisation conditions of the polynomial controlled system augmented by its observer. The design of the observer-based control leverages some notations from the Kronecker product and the power of matrices properties for the state space description of polynomial systems. The stability study of the polynomial controlled system augmented by its observer is based on the Lyapunov stability direct method. Intensive simulations are performed to illustrate the validity and the effectiveness of the polynomial approach used to design the control.

  4. Robust multiplatform RF emitter localization

    NASA Astrophysics Data System (ADS)

    Al Issa, Huthaifa; Ordóñez, Raúl

    2012-06-01

    In recent years, position based services has increase. Thus, recent developments in communications and RF technology have enabled system concept formulations and designs for low-cost radar systems using state-of-the-art software radio modules. This research is done to investigate a novel multi-platform RF emitter localization technique denoted as Position-Adaptive RF Direction Finding (PADF). The formulation is based on the investigation of iterative path-loss (i.e., Path Loss Exponent, or PLE) metrics estimates that are measured across multiple platforms in order to autonomously adapt (i.e. self-adjust) of the location of each distributed/cooperative platform. Experiments conducted at the Air-Force Research laboratory (AFRL) indicate that this position-adaptive approach exhibits potential for accurate emitter localization in challenging embedded multipath environments such as in urban environments. The focus of this paper is on the robustness of the distributed approach to RF-based location tracking. In order to localize the transmitter, we use the Received Signal Strength Indicator (RSSI) data to approximate distance from the transmitter to the revolving receivers. We provide an algorithm for on-line estimation of the Path Loss Exponent (PLE) that is used in modeling the distance based on Received Signal Strength (RSS) measurements. The emitter position estimation is calculated based on surrounding sensors RSS values using Least-Square Estimation (LSE). The PADF has been tested on a number of different configurations in the laboratory via the design and implementation of four IRIS wireless sensor nodes as receivers and one hidden sensor as a transmitter during the localization phase. The robustness of detecting the transmitters position is initiated by getting the RSSI data through experiments and then data manipulation in MATLAB will determine the robustness of each node and ultimately that of each configuration. The parameters that are used in the functions are

  5. Fast robust correlation.

    PubMed

    Fitch, Alistair J; Kadyrov, Alexander; Christmas, William J; Kittler, Josef

    2005-08-01

    A new, fast, statistically robust, exhaustive, translational image-matching technique is presented: fast robust correlation. Existing methods are either slow or non-robust, or rely on optimization. Fast robust correlation works by expressing a robust matching surface as a series of correlations. Speed is obtained by computing correlations in the frequency domain. Computational cost is analyzed and the method is shown to be fast. Speed is comparable to conventional correlation and, for large images, thousands of times faster than direct robust matching. Three experiments demonstrate the advantage of the technique over standard correlation.

  6. Robustness: confronting lessons from physics and biology.

    PubMed

    Lesne, Annick

    2008-11-01

    The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems. PMID:18823391

  7. Environmental change makes robust ecological networks fragile

    PubMed Central

    Strona, Giovanni; Lafferty, Kevin D.

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers' tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems. PMID:27511722

  8. Environmental change makes robust ecological networks fragile.

    PubMed

    Strona, Giovanni; Lafferty, Kevin D

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers' tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host-parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems. PMID:27511722

  9. Environmental change makes robust ecological networks fragile

    USGS Publications Warehouse

    Strona, Giovanni; Lafferty, Kevin D.

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.

  10. Biological Robustness: Paradigms, Mechanisms, and Systems Principles

    PubMed Central

    Whitacre, James Michael

    2012-01-01

    Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior. PMID:22593762

  11. Biological robustness: paradigms, mechanisms, and systems principles.

    PubMed

    Whitacre, James Michael

    2012-01-01

    Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior. PMID:22593762

  12. Robust Multiobjective Controllability of Complex Neuronal Networks.

    PubMed

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

    2016-01-01

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

  13. Robust Software Architecture for Robots

    NASA Technical Reports Server (NTRS)

    Aghazanian, Hrand; Baumgartner, Eric; Garrett, Michael

    2009-01-01

    Robust Real-Time Reconfigurable Robotics Software Architecture (R4SA) is the name of both a software architecture and software that embodies the architecture. The architecture was conceived in the spirit of current practice in designing modular, hard, realtime aerospace systems. The architecture facilitates the integration of new sensory, motor, and control software modules into the software of a given robotic system. R4SA was developed for initial application aboard exploratory mobile robots on Mars, but is adaptable to terrestrial robotic systems, real-time embedded computing systems in general, and robotic toys.

  14. Generalized projective synchronization of chaotic systems with unknown dead-zone input: observer-based approach.

    PubMed

    Hung, Yung-Ching; Hwang, Chi-Chuan; Liao, Teh-Lu; Yan, Jun-Juh

    2006-09-01

    In this paper we investigate the synchronization problem of drive-response chaotic systems with a scalar coupling signal. By using the scalar transmitted signal from the drive chaotic system, an observer-based response chaotic system with dead-zone nonlinear input is designed. An output feedback control technique is derived to achieve generalized projective synchronization between the drive system and the response system. Furthermore, an adaptive control law is established that guarantees generalized projective synchronization without the knowledge of system nonlinearity, and/or system parameters as well as that of parameters in dead-zone input nonlinearity. Two illustrative examples are given to demonstrate the effectiveness of the proposed synchronization scheme.

  15. Adaptive output feedback control of flexible systems

    NASA Astrophysics Data System (ADS)

    Yang, Bong-Jun

    Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in

  16. Mechanisms for Robust Cognition

    ERIC Educational Resources Information Center

    Walsh, Matthew M.; Gluck, Kevin A.

    2015-01-01

    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

  17. Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget

    NASA Technical Reports Server (NTRS)

    Rodell, Matthew; McWilliams, Eric B.; Famiglietti, James S.; Beaudoing, Hiroko K.; Nigro, Joseph

    2011-01-01

    Evapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground-based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation-based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment satellite mission. We demonstrate that while uncertainty in the water budget-based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget-based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite-based ET retrieval optimization.

  18. Disturbance observer based control system design for inertially stabilized platform

    NASA Astrophysics Data System (ADS)

    Wu, Chunnan; Lin, Zhe

    2012-09-01

    Inertially stabilized platform (ISP) is indispensable for various imaging systems to segregate the base angular movement and achieve high LOS (Line-Of-Sight) stability. The disturbance rejection ratio and command following performance are of primary concern in designing ISP control systems. In this paper, the redundant gimbals ISP system is considered and it is shown to experience complex disturbance and parameter variation during operation. To meet advanced LOS stabilization requirement, a disturbance observer based (DOB) dual-loop controller design for ISP is proposed of which the DOB is the internal-loop. Using a nominal plant model and a low-pass filter, the disturbance signal is estimated and used as a cancellation input added to the current command of torque motor. If the DOB works well, the disturbance torque and mismatch between nominal plant and actual plant will be compensated and the internal-loop will behave as nominal model parameters. On the other hand, the external-loop will be designed for nominal model parameters to meet stabilization requirements. This paper will mainly focus on the DOB design method. Since the low-pass filter of DOB determines the sensitivity and complementary sensitivity function as will be shown in this paper, designing the filter is the most important consideration. In this paper, an optimal low-pass filter design method is proposed. The method is intuitive, simple to implement and allows on-line tuning. Simulation results show the performance enhancement of our control structure in the presence of disturbance and measurement noise.

  19. Observer-based state feedback for enhanced insulin control of type 'i' diabetic patients.

    PubMed

    Hariri, Ali; Wang, Le Yi

    2011-01-01

    During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type 'I' diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink.

  20. Observer-Based State Feedback for Enhanced Insulin Control of Type ‘I’ Diabetic Patients

    PubMed Central

    Hariri, Ali; Wang, Le Yi

    2011-01-01

    During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type ‘I’ diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink. PMID:22276077

  1. Robust Methods in Qsar

    NASA Astrophysics Data System (ADS)

    Walczak, Beata; Daszykowski, Michał; Stanimirova, Ivana

    A large progress in the development of robust methods as an efficient tool for processing of data contaminated with outlying objects has been made over the last years. Outliers in the QSAR studies are usually the result of an improper calculation of some molecular descriptors and/or experimental error in determining the property to be modelled. They influence greatly any least square model, and therefore the conclusions about the biological activity of a potential component based on such a model are misleading. With the use of robust approaches, one can solve this problem building a robust model describing the data majority well. On the other hand, the proper identification of outliers may pinpoint a new direction of a drug development. The outliers' assessment can exclusively be done with robust methods and these methods are to be described in this chapter

  2. Robustness of airline alliance route networks

    NASA Astrophysics Data System (ADS)

    Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

    2015-05-01

    The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

  3. Efficient infill sampling for unconstrained robust optimization problems

    NASA Astrophysics Data System (ADS)

    Rehman, Samee Ur; Langelaar, Matthijs

    2016-08-01

    A novel infill sampling criterion is proposed for efficient estimation of the global robust optimum of expensive computer simulation based problems. The algorithm is especially geared towards addressing problems that are affected by uncertainties in design variables and problem parameters. The method is based on constructing metamodels using Kriging and adaptively sampling the response surface via a principle of expected improvement adapted for robust optimization. Several numerical examples and an engineering case study are used to demonstrate the ability of the algorithm to estimate the global robust optimum using a limited number of expensive function evaluations.

  4. Parallel Anisotropic Tetrahedral Adaptation

    NASA Technical Reports Server (NTRS)

    Park, Michael A.; Darmofal, David L.

    2008-01-01

    An adaptive method that robustly produces high aspect ratio tetrahedra to a general 3D metric specification without introducing hybrid semi-structured regions is presented. The elemental operators and higher-level logic is described with their respective domain-decomposed parallelizations. An anisotropic tetrahedral grid adaptation scheme is demonstrated for 1000-1 stretching for a simple cube geometry. This form of adaptation is applicable to more complex domain boundaries via a cut-cell approach as demonstrated by a parallel 3D supersonic simulation of a complex fighter aircraft. To avoid the assumptions and approximations required to form a metric to specify adaptation, an approach is introduced that directly evaluates interpolation error. The grid is adapted to reduce and equidistribute this interpolation error calculation without the use of an intervening anisotropic metric. Direct interpolation error adaptation is illustrated for 1D and 3D domains.

  5. Costs and benefits of mutational robustness in RNA viruses.

    PubMed

    Stern, Adi; Bianco, Simone; Yeh, Ming Te; Wright, Caroline; Butcher, Kristin; Tang, Chao; Nielsen, Rasmus; Andino, Raul

    2014-08-21

    The accumulation of mutations in RNA viruses is thought to facilitate rapid adaptation to changes in the environment. However, most mutations have deleterious effects on fitness, especially for viruses. Thus, tolerance to mutations should determine the nature and extent of genetic diversity that can be maintained in the population. Here, we combine population genetics theory, computer simulation, and experimental evolution to examine the advantages and disadvantages of tolerance to mutations, also known as mutational robustness. We find that mutational robustness increases neutral diversity and, as expected, can facilitate adaptation to a new environment. Surprisingly, under certain conditions, robustness may also be an impediment for viral adaptation, if a highly diverse population contains a large proportion of previously neutral mutations that are deleterious in the new environment. These findings may inform therapeutic strategies that cause extinction of otherwise robust viral populations.

  6. FPGA implementation of robust Capon beamformer

    NASA Astrophysics Data System (ADS)

    Guan, Xin; Zmuda, Henry; Li, Jian; Du, Lin; Sheplak, Mark

    2012-03-01

    The Capon Beamforming algorithm is an optimal spatial filtering algorithm used in various signal processing applications where excellent interference rejection performance is required, such as Radar and Sonar systems, Smart Antenna systems for wireless communications. Its lack of robustness, however, means that it is vulnerable to array calibration errors and other model errors. To overcome this problem, numerous robust Capon Beamforming algorithms have been proposed, which are much more promising for practical applications. In this paper, an FPGA implementation of a robust Capon Beamforming algorithm is investigated and presented. This realization takes an array output with 4 channels, computes the complex-valued adaptive weight vectors for beamforming with an 18 bit fixed-point representation and runs at a 100 MHz clock on Xilinx V4 FPGA. This work will be applied in our medical imaging project for breast cancer detection.

  7. Robustness of spatial micronetworks

    NASA Astrophysics Data System (ADS)

    McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.

    2015-04-01

    Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

  8. Doubly robust survival trees.

    PubMed

    Steingrimsson, Jon Arni; Diao, Liqun; Molinaro, Annette M; Strawderman, Robert L

    2016-09-10

    Estimating a patient's mortality risk is important in making treatment decisions. Survival trees are a useful tool and employ recursive partitioning to separate patients into different risk groups. Existing 'loss based' recursive partitioning procedures that would be used in the absence of censoring have previously been extended to the setting of right censored outcomes using inverse probability censoring weighted estimators of loss functions. In this paper, we propose new 'doubly robust' extensions of these loss estimators motivated by semiparametric efficiency theory for missing data that better utilize available data. Simulations and a data analysis demonstrate strong performance of the doubly robust survival trees compared with previously used methods. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27037609

  9. Observability-based sampling and estimation of flowfields using multi-sensor systems

    NASA Astrophysics Data System (ADS)

    DeVries, Levi D.

    The long-term goal of this research is to optimize estimation of an unknown flowfield using an autonomous multi-vehicle or multi-sensor system. The specific research objective is to provide theoretically justified, nonlinear control, estimation, and optimization techniques enabling a group of sensors to coordinate their motion to target measurements that improve observability of the surrounding environment, even when the environment is unknown. Measures of observability provide an optimization metric for multi-agent control algorithms that avoid spatial regions of the domain prone to degraded or ill-conditioned estimation performance, thereby improving closed-loop control performance when estimated quantities are used in feedback control. The control, estimation, and optimization framework is applied to three applications of multi-agent flowfield sensing including (1) environmental sampling of strong flowfields using multiple autonomous unmanned vehicles, (2) wake sensing and observability-based optimal control for two-aircraft formation flight, and (3) bio-inspired flow sensing and control of an autonomous unmanned underwater vehicle. For environmental sampling, this dissertation presents an adaptive sampling algorithm steering a multi-vehicle system to sampling formations that improve flowfield observability while simultaneously estimating the flow for use in feedback control, even in strong flows where vehicle motion is hindered. The resulting closed-loop trajectories provide more informative measurements, improving estimation performance. For formation flight, this dissertation uses lifting-line theory to represent a two-aircraft formation and derives optimal control strategies steering the follower aircraft to a desired position relative to the leader while simultaneously optimizing the observability of the leader's relative position. The control algorithms guide the follower aircraft to a desired final position along trajectories that maintain adequate

  10. Robust reinforcement learning.

    PubMed

    Morimoto, Jun; Doya, Kenji

    2005-02-01

    This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H(infinity) control, we consider a differential game in which a "disturbing" agent tries to make the worst possible disturbance while a "control" agent tries to make the best control input. The problem is formulated as finding a min-max solution of a value function that takes into account the amount of the reward and the norm of the disturbance. We derive online learning algorithms for estimating the value function and for calculating the worst disturbance and the best control in reference to the value function. We tested the paradigm, which we call robust reinforcement learning (RRL), on the control task of an inverted pendulum. In the linear domain, the policy and the value function learned by online algorithms coincided with those derived analytically by the linear H(infinity) control theory. For a fully nonlinear swing-up task, RRL achieved robust performance with changes in the pendulum weight and friction, while a standard reinforcement learning algorithm could not deal with these changes. We also applied RRL to the cart-pole swing-up task, and a robust swing-up policy was acquired.

  11. Robust vibration control of flexible linkage mechanisms using piezoelectric films

    NASA Astrophysics Data System (ADS)

    Liao, Wen-Hwei; Chou, Jyh-Horng; Horng, Ing-Rong

    1997-08-01

    Based on the state space model of the flexible linkage mechanism equipped with piezoelectric films, a robust control methodology for suppressing elastodynamic responses of the high-speed flexible linkage mechanism with linear time-varying parameter perturbations by employing an observer-based feedback controller is presented. The instability caused by the linear time-varying parameter perturbations and the instability caused by the combined effect of control and observation spillover are investigated and carefully prevented by two robust stability criteria proposed in this paper. Numerical simulation of a slider - crank mechanism example is performed to evaluate the improvement of the elastodynamic responses.

  12. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    PubMed

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations.

  13. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    PubMed

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations. PMID:25104646

  14. On the Robustness Properties of M-MRAC

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram

    2012-01-01

    The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.

  15. Measure of robustness for complex networks

    NASA Astrophysics Data System (ADS)

    Youssef, Mina Nabil

    to the spread of susceptible/infected/recovered (SIR) epidemics. To compute VCSIR, we propose a novel individual-based approach to model the spread of SIR epidemics in networks, which captures the infection size for a given effective infection rate. Thus, VCSIR quantitatively integrates the infection strength with the corresponding infection size. To optimize the VCSIR metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation

  16. Robust Systems Test Framework

    2003-01-01

    The Robust Systems Test Framework (RSTF) provides a means of specifying and running test programs on various computation platforms. RSTF provides a level of specification above standard scripting languages. During a set of runs, standard timing information is collected. The RSTF specification can also gather job-specific information, and can include ways to classify test outcomes. All results and scripts can be stored into and retrieved from an SQL database for later data analysis. RSTF alsomore » provides operations for managing the script and result files, and for compiling applications and gathering compilation information such as optimization flags.« less

  17. Robust quantum spatial search

    NASA Astrophysics Data System (ADS)

    Tulsi, Avatar

    2016-07-01

    Quantum spatial search has been widely studied with most of the study focusing on quantum walk algorithms. We show that quantum walk algorithms are extremely sensitive to systematic errors. We present a recursive algorithm which offers significant robustness to certain systematic errors. To search N items, our recursive algorithm can tolerate errors of size O(1{/}√{ln N}) which is exponentially better than quantum walk algorithms for which tolerable error size is only O(ln N{/}√{N}). Also, our algorithm does not need any ancilla qubit. Thus our algorithm is much easier to implement experimentally compared to quantum walk algorithms.

  18. Robust Kriged Kalman Filtering

    SciTech Connect

    Baingana, Brian; Dall'Anese, Emiliano; Mateos, Gonzalo; Giannakis, Georgios B.

    2015-11-11

    Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

  19. Robust Systems Test Framework

    SciTech Connect

    Ballance, Robert A.

    2003-01-01

    The Robust Systems Test Framework (RSTF) provides a means of specifying and running test programs on various computation platforms. RSTF provides a level of specification above standard scripting languages. During a set of runs, standard timing information is collected. The RSTF specification can also gather job-specific information, and can include ways to classify test outcomes. All results and scripts can be stored into and retrieved from an SQL database for later data analysis. RSTF also provides operations for managing the script and result files, and for compiling applications and gathering compilation information such as optimization flags.

  20. Robust telescope scheduling

    NASA Technical Reports Server (NTRS)

    Swanson, Keith; Bresina, John; Drummond, Mark

    1994-01-01

    This paper presents a technique for building robust telescope schedules that tend not to break. The technique is called Just-In-Case (JIC) scheduling and it implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes a scheduler to generate a contingent schedule for each highly probable break case, and produces a 'multiply contingent' schedule. The technique was developed for an automatic telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.

  1. Robust Photon Locking

    SciTech Connect

    Bayer, T.; Wollenhaupt, M.; Sarpe-Tudoran, C.; Baumert, T.

    2009-01-16

    We experimentally demonstrate a strong-field coherent control mechanism that combines the advantages of photon locking (PL) and rapid adiabatic passage (RAP). Unlike earlier implementations of PL and RAP by pulse sequences or chirped pulses, we use shaped pulses generated by phase modulation of the spectrum of a femtosecond laser pulse with a generalized phase discontinuity. The novel control scenario is characterized by a high degree of robustness achieved via adiabatic preparation of a state of maximum coherence. Subsequent phase control allows for efficient switching among different target states. We investigate both properties by photoelectron spectroscopy on potassium atoms interacting with the intense shaped light field.

  2. Robust control for uncertain structures

    NASA Technical Reports Server (NTRS)

    Douglas, Joel; Athans, Michael

    1991-01-01

    Viewgraphs on robust control for uncertain structures are presented. Topics covered include: robust linear quadratic regulator (RLQR) formulas; mismatched LQR design; RLQR design; interpretations of RLQR design; disturbance rejection; and performance comparisons: RLQR vs. mismatched LQR.

  3. Robust control algorithms for Mars aerobraking

    NASA Technical Reports Server (NTRS)

    Shipley, Buford W., Jr.; Ward, Donald T.

    1992-01-01

    Four atmospheric guidance concepts have been adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. The first two offer improvements to the Analytic Predictor Corrector (APC) to increase its robustness to density variations. The second two are variations of a new Liapunov tracking exit phase algorithm, developed to guide the vehicle along a reference trajectory. These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. MARSGRAM is used to develop realistic atmospheres for the study. When square wave density pulses perturb the atmosphere all four controllers are successful. The algorithms are tested against atmospheres where the inbound and outbound density functions are different. Square wave density pulses are again used, but only for the outbound leg of the trajectory. Additionally, sine waves are used to perturb the density function. The new algorithms are found to be more robust than any previously tested and a Liapunov controller is selected as the most robust control algorithm overall examined.

  4. Robust omniphobic surfaces

    PubMed Central

    Tuteja, Anish; Choi, Wonjae; Mabry, Joseph M.; McKinley, Gareth H.; Cohen, Robert E.

    2008-01-01

    Superhydrophobic surfaces display water contact angles greater than 150° in conjunction with low contact angle hysteresis. Microscopic pockets of air trapped beneath the water droplets placed on these surfaces lead to a composite solid-liquid-air interface in thermodynamic equilibrium. Previous experimental and theoretical studies suggest that it may not be possible to form similar fully-equilibrated, composite interfaces with drops of liquids, such as alkanes or alcohols, that possess significantly lower surface tension than water (γlv = 72.1 mN/m). In this work we develop surfaces possessing re-entrant texture that can support strongly metastable composite solid-liquid-air interfaces, even with very low surface tension liquids such as pentane (γlv = 15.7 mN/m). Furthermore, we propose four design parameters that predict the measured contact angles for a liquid droplet on a textured surface, as well as the robustness of the composite interface, based on the properties of the solid surface and the contacting liquid. These design parameters allow us to produce two different families of re-entrant surfaces— randomly-deposited electrospun fiber mats and precisely fabricated microhoodoo surfaces—that can each support a robust composite interface with essentially any liquid. These omniphobic surfaces display contact angles greater than 150° and low contact angle hysteresis with both polar and nonpolar liquids possessing a wide range of surface tensions. PMID:19001270

  5. Blink detection robust to various facial poses.

    PubMed

    Lee, Won Oh; Lee, Eui Chul; Park, Kang Ryoung

    2010-11-30

    Applications based on eye-blink detection have increased, as a result of which it is essential for eye-blink detection to be robust and non-intrusive irrespective of the changes in the user's facial pose. However, most previous studies on camera-based blink detection have the disadvantage that their performances were affected by the facial pose. They also focused on blink detection using only frontal facial images. To overcome these disadvantages, we developed a new method for blink detection, which maintains its accuracy despite changes in the facial pose of the subject. This research is novel in the following four ways. First, the face and eye regions are detected by using both the AdaBoost face detector and a Lucas-Kanade-Tomasi (LKT)-based method, in order to achieve robustness to facial pose. Secondly, the determination of the state of the eye (being open or closed), needed for blink detection, is based on two features: the ratio of height to width of the eye region in a still image, and the cumulative difference of the number of black pixels of the eye region using an adaptive threshold in successive images. These two features are robustly extracted irrespective of the lighting variations by using illumination normalization. Thirdly, the accuracy of determining the eye state - open or closed - is increased by combining the above two features on the basis of the support vector machine (SVM). Finally, the SVM classifier for determining the eye state is adaptively selected according to the facial rotation. Experimental results using various databases showed that the blink detection by the proposed method is robust to various facial poses. PMID:20826183

  6. Transformational adaptation when incremental adaptations to climate change are insufficient

    PubMed Central

    Kates, Robert W.; Travis, William R.; Wilbanks, Thomas J.

    2012-01-01

    All human–environment systems adapt to climate and its natural variation. Adaptation to human-induced change in climate has largely been envisioned as increments of these adaptations intended to avoid disruptions of systems at their current locations. In some places, for some systems, however, vulnerabilities and risks may be so sizeable that they require transformational rather than incremental adaptations. Three classes of transformational adaptations are those that are adopted at a much larger scale, that are truly new to a particular region or resource system, and that transform places and shift locations. We illustrate these with examples drawn from Africa, Europe, and North America. Two conditions set the stage for transformational adaptation to climate change: large vulnerability in certain regions, populations, or resource systems; and severe climate change that overwhelms even robust human use systems. However, anticipatory transformational adaptation may be difficult to implement because of uncertainties about climate change risks and adaptation benefits, the high costs of transformational actions, and institutional and behavioral actions that tend to maintain existing resource systems and policies. Implementing transformational adaptation requires effort to initiate it and then to sustain the effort over time. In initiating transformational adaptation focusing events and multiple stresses are important, combined with local leadership. In sustaining transformational adaptation, it seems likely that supportive social contexts and the availability of acceptable options and resources for actions are key enabling factors. Early steps would include incorporating transformation adaptation into risk management and initiating research to expand the menu of innovative transformational adaptations. PMID:22509036

  7. Transformational adaptation when incremental adaptations to climate change are insufficient.

    PubMed

    Kates, Robert W; Travis, William R; Wilbanks, Thomas J

    2012-05-01

    All human-environment systems adapt to climate and its natural variation. Adaptation to human-induced change in climate has largely been envisioned as increments of these adaptations intended to avoid disruptions of systems at their current locations. In some places, for some systems, however, vulnerabilities and risks may be so sizeable that they require transformational rather than incremental adaptations. Three classes of transformational adaptations are those that are adopted at a much larger scale, that are truly new to a particular region or resource system, and that transform places and shift locations. We illustrate these with examples drawn from Africa, Europe, and North America. Two conditions set the stage for transformational adaptation to climate change: large vulnerability in certain regions, populations, or resource systems; and severe climate change that overwhelms even robust human use systems. However, anticipatory transformational adaptation may be difficult to implement because of uncertainties about climate change risks and adaptation benefits, the high costs of transformational actions, and institutional and behavioral actions that tend to maintain existing resource systems and policies. Implementing transformational adaptation requires effort to initiate it and then to sustain the effort over time. In initiating transformational adaptation focusing events and multiple stresses are important, combined with local leadership. In sustaining transformational adaptation, it seems likely that supportive social contexts and the availability of acceptable options and resources for actions are key enabling factors. Early steps would include incorporating transformation adaptation into risk management and initiating research to expand the menu of innovative transformational adaptations.

  8. Evolving Robust Gene Regulatory Networks

    PubMed Central

    Noman, Nasimul; Monjo, Taku; Moscato, Pablo; Iba, Hitoshi

    2015-01-01

    Design and implementation of robust network modules is essential for construction of complex biological systems through hierarchical assembly of ‘parts’ and ‘devices’. The robustness of gene regulatory networks (GRNs) is ascribed chiefly to the underlying topology. The automatic designing capability of GRN topology that can exhibit robust behavior can dramatically change the current practice in synthetic biology. A recent study shows that Darwinian evolution can gradually develop higher topological robustness. Subsequently, this work presents an evolutionary algorithm that simulates natural evolution in silico, for identifying network topologies that are robust to perturbations. We present a Monte Carlo based method for quantifying topological robustness and designed a fitness approximation approach for efficient calculation of topological robustness which is computationally very intensive. The proposed framework was verified using two classic GRN behaviors: oscillation and bistability, although the framework is generalized for evolving other types of responses. The algorithm identified robust GRN architectures which were verified using different analysis and comparison. Analysis of the results also shed light on the relationship among robustness, cooperativity and complexity. This study also shows that nature has already evolved very robust architectures for its crucial systems; hence simulation of this natural process can be very valuable for designing robust biological systems. PMID:25616055

  9. Robust high-performance control for robotic manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1989-01-01

    A robust control scheme to accomplish accurate trajectory tracking for an integrated system of manipulator-plus-actuators is proposed. The control scheme comprises a feedforward and a feedback controller. The feedforward controller contains any known part of the manipulator dynamics that can be used for online control. The feedback controller consists of adaptive position and velocity feedback gains and an auxiliary signal which is simply generated by a fixed-gain proportional/integral/derivative controller. The feedback controller is updated by very simple adaptation laws which contain both proportional and integral adaptation terms. By introduction of a simple sigma modification to the adaptation laws, robustness is guaranteed in the presence of unmodeled dynamics and disturbances.

  10. Robustness in Digital Hardware

    NASA Astrophysics Data System (ADS)

    Woods, Roger; Lightbody, Gaye

    The growth in electronics has probably been the equivalent of the Industrial Revolution in the past century in terms of how much it has transformed our daily lives. There is a great dependency on technology whether it is in the devices that control travel (e.g., in aircraft or cars), our entertainment and communication systems, or our interaction with money, which has been empowered by the onset of Internet shopping and banking. Despite this reliance, there is still a danger that at some stage devices will fail within the equipment's lifetime. The purpose of this chapter is to look at the factors causing failure and address possible measures to improve robustness in digital hardware technology and specifically chip technology, giving a long-term forecast that will not reassure the reader!

  11. Robust springback compensation

    NASA Astrophysics Data System (ADS)

    Carleer, Bart; Grimm, Peter

    2013-12-01

    Springback simulation and springback compensation are more and more applied in productive use of die engineering. In order to successfully compensate a tool accurate springback results are needed as well as an effective compensation approach. In this paper a methodology has been introduce in order to effectively compensate tools. First step is the full process simulation meaning that not only the drawing operation will be simulated but also all secondary operations like trimming and flanging. Second will be the verification whether the process is robust meaning that it obtains repeatable results. In order to effectively compensate a minimum clamping concept will be defined. Once these preconditions are fulfilled the tools can be compensated effectively.

  12. Robust reflective pupil slicing technology

    NASA Astrophysics Data System (ADS)

    Meade, Jeffrey T.; Behr, Bradford B.; Cenko, Andrew T.; Hajian, Arsen R.

    2014-07-01

    Tornado Spectral Systems (TSS) has developed the High Throughput Virtual Slit (HTVSTM), robust all-reflective pupil slicing technology capable of replacing the slit in research-, commercial- and MIL-SPEC-grade spectrometer systems. In the simplest configuration, the HTVS allows optical designers to remove the lossy slit from pointsource spectrometers and widen the input slit of long-slit spectrometers, greatly increasing throughput without loss of spectral resolution or cross-dispersion information. The HTVS works by transferring etendue between image plane axes but operating in the pupil domain rather than at a focal plane. While useful for other technologies, this is especially relevant for spectroscopic applications by performing the same spectral narrowing as a slit without throwing away light on the slit aperture. HTVS can be implemented in all-reflective designs and only requires a small number of reflections for significant spectral resolution enhancement-HTVS systems can be efficiently implemented in most wavelength regions. The etendueshifting operation also provides smooth scaling with input spot/image size without requiring reconfiguration for different targets (such as different seeing disk diameters or different fiber core sizes). Like most slicing technologies, HTVS provides throughput increases of several times without resolution loss over equivalent slitbased designs. HTVS technology enables robust slit replacement in point-source spectrometer systems. By virtue of pupilspace operation this technology has several advantages over comparable image-space slicer technology, including the ability to adapt gracefully and linearly to changing source size and better vertical packing of the flux distribution. Additionally, this technology can be implemented with large slicing factors in both fast and slow beams and can easily scale from large, room-sized spectrometers through to small, telescope-mounted devices. Finally, this same technology is directly

  13. Adaptive control with aerospace applications

    NASA Astrophysics Data System (ADS)

    Gadient, Ross

    Robust and adaptive control techniques have a rich history of theoretical development with successful application. Despite the accomplishments made, attempts to combine the best elements of each approach into robust adaptive systems has proven challenging, particularly in the area of application to real world aerospace systems. In this research, we investigate design methods for general classes of systems that may be applied to representative aerospace dynamics. By combining robust baseline control design with augmentation designs, our work aims to leverage the advantages of each approach. This research contributes the development of robust model-based control design for two classes of dynamics: 2nd order cascaded systems, and a more general MIMO framework. We present a theoretically justified method for state limiting via augmentation of a robust baseline control design. Through the development of adaptive augmentation designs, we are able to retain system performance in the presence of uncertainties. We include an extension that combines robust baseline design with both state limiting and adaptive augmentations. In addition we develop an adaptive augmentation design approach for a class of dynamic input uncertainties. We present formal stability proofs and analyses for all proposed designs in the research. Throughout the work, we present real world aerospace applications using relevant flight dynamics and flight test results. We derive robust baseline control designs with application to both piloted and unpiloted aerospace system. Using our developed methods, we add a flight envelope protecting state limiting augmentation for piloted aircraft applications and demonstrate the efficacy of our approach via both simulation and flight test. We illustrate our adaptive augmentation designs via application to relevant fixed-wing aircraft dynamics. Both a piloted example combining the state limiting and adaptive augmentation approaches, and an unpiloted example with

  14. 3D robust digital image correlation for vibration measurement.

    PubMed

    Chen, Zhong; Zhang, Xianmin; Fatikow, Sergej

    2016-03-01

    Discrepancies of speckle images under dynamic measurement due to the different viewing angles will deteriorate the correspondence in 3D digital image correlation (3D-DIC) for vibration measurement. Facing this kind of bottleneck, this paper presents two types of robust 3D-DIC methods for vibration measurement, SSD-robust and SWD-robust, which use a sum of square difference (SSD) estimator plus a Geman-McClure regulating term and a Welch estimator plus a Geman-McClure regulating term, respectively. Because the regulating term with an adaptive rejecting bound can lessen the influence of the abnormal pixel data in the dynamical measuring process, the robustness of the algorithm is enhanced. The robustness and precision evaluation experiments using a dual-frequency laser interferometer are implemented. The experimental results indicate that the two presented robust estimators can suppress the effects of the abnormality in the speckle images and, meanwhile, keep higher precision in vibration measurement in contrast with the traditional SSD method; thus, the SWD-robust and SSD-robust methods are suitable for weak image noise and strong image noise, respectively. PMID:26974624

  15. Robust Nonlinear Neural Codes

    NASA Astrophysics Data System (ADS)

    Yang, Qianli; Pitkow, Xaq

    2015-03-01

    Most interesting natural sensory stimuli are encoded in the brain in a form that can only be decoded nonlinearly. But despite being a core function of the brain, nonlinear population codes are rarely studied and poorly understood. Interestingly, the few existing models of nonlinear codes are inconsistent with known architectural features of the brain. In particular, these codes have information content that scales with the size of the cortical population, even if that violates the data processing inequality by exceeding the amount of information entering the sensory system. Here we provide a valid theory of nonlinear population codes by generalizing recent work on information-limiting correlations in linear population codes. Although these generalized, nonlinear information-limiting correlations bound the performance of any decoder, they also make decoding more robust to suboptimal computation, allowing many suboptimal decoders to achieve nearly the same efficiency as an optimal decoder. Although these correlations are extremely difficult to measure directly, particularly for nonlinear codes, we provide a simple, practical test by which one can use choice-related activity in small populations of neurons to determine whether decoding is suboptimal or optimal and limited by correlated noise. We conclude by describing an example computation in the vestibular system where this theory applies. QY and XP was supported by a grant from the McNair foundation.

  16. Automated Grid Disruption Response System: Robust Adaptive Topology Control (RATC)

    SciTech Connect

    2012-03-01

    GENI Project: The RATC research team is using topology control as a mechanism to improve system operations and manage disruptions within the electric grid. The grid is subject to interruption from cascading faults caused by extreme operating conditions, malicious external attacks, and intermittent electricity generation from renewable energy sources. The RATC system is capable of detecting, classifying, and responding to grid disturbances by reconfiguring the grid in order to maintain economically efficient operations while guaranteeing reliability. The RATC system would help prevent future power outages, which account for roughly $80 billion in losses for businesses and consumers each year. Minimizing the time it takes for the grid to respond to expensive interruptions will also make it easier to integrate intermittent renewable energy sources into the grid.

  17. The robustness of complex networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2002-03-01

    Many complex networks display a surprising degree of tolerance against errors. For example, organisms and ecosystems exhibit remarkable robustness to large variations in temperature, moisture, and nutrients, and communication networks continue to function despite local failures. This presentation will explore the effects of the network topology on its robust functioning. First, we will consider the topological integrity of several networks under node disruption. Then we will focus on the functional robustness of biological signaling networks, and the decisive role played by the network topology in this robustness.

  18. Gearbox design for uncertain load requirements using active robust optimization

    NASA Astrophysics Data System (ADS)

    Salomon, Shaul; Avigad, Gideon; Purshouse, Robin C.; Fleming, Peter J.

    2016-04-01

    Design and optimization of gear transmissions have been intensively studied, but surprisingly the robustness of the resulting optimal design to uncertain loads has never been considered. Active Robust (AR) optimization is a methodology to design products that attain robustness to uncertain or changing environmental conditions through adaptation. In this study the AR methodology is utilized to optimize the number of transmissions, as well as their gearing ratios, for an uncertain load demand. The problem is formulated as a bi-objective optimization problem where the objectives are to satisfy the load demand in the most energy efficient manner and to minimize production cost. The results show that this approach can find a set of robust designs, revealing a trade-off between energy efficiency and production cost. This can serve as a useful decision-making tool for the gearbox design process, as well as for other applications.

  19. Robust, Optimal Subsonic Airfoil Shapes

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan

    2014-01-01

    A method has been developed to create an airfoil robust enough to operate satisfactorily in different environments. This method determines a robust, optimal, subsonic airfoil shape, beginning with an arbitrary initial airfoil shape, and imposes the necessary constraints on the design. Also, this method is flexible and extendible to a larger class of requirements and changes in constraints imposed.

  20. Robust Understanding of Statistical Variation

    ERIC Educational Resources Information Center

    Peters, Susan A.

    2011-01-01

    This paper presents a framework that captures the complexity of reasoning about variation in ways that are indicative of robust understanding and describes reasoning as a blend of design, data-centric, and modeling perspectives. Robust understanding is indicated by integrated reasoning about variation within each perspective and across…

  1. Robust image segmentation using local robust statistics and correntropy-based K-means clustering

    NASA Astrophysics Data System (ADS)

    Huang, Chencheng; Zeng, Li

    2015-03-01

    It is an important work to segment the real world images with intensity inhomogeneity such as magnetic resonance (MR) and computer tomography (CT) images. In practice, such images are often polluted by noise which make them difficult to be segmented by traditional level set based segmentation models. In this paper, we propose a robust level set image segmentation model combining local with global fitting energies to segment noised images. In the proposed model, the local fitting energy is based on the local robust statistics (LRS) information of an input image, which can efficiently reduce the effects of the noise, and the global fitting energy utilizes the correntropy-based K-means (CK) method, which can adaptively emphasize the samples that are close to their corresponding cluster centers. By integrating the advantages of global information and local robust statistics characteristics, the proposed model can efficiently segment images with intensity inhomogeneity and noise. Then, a level set regularization term is used to avoid re-initialization procedures in the process of curve evolution. In addition, the Gaussian filter is utilized to keep the level set smoothing in the curve evolution process. The proposed model first appeared as a two-phase model and then extended to a multi-phase one. Experimental results show the advantages of our model in terms of accuracy and robustness to the noise. In particular, our method has been applied on some synthetic and real images with desirable results.

  2. Facial symmetry in robust anthropometrics.

    PubMed

    Kalina, Jan

    2012-05-01

    Image analysis methods commonly used in forensic anthropology do not have desirable robustness properties, which can be ensured by robust statistical methods. In this paper, the face localization in images is carried out by detecting symmetric areas in the images. Symmetry is measured between two neighboring rectangular areas in the images using a new robust correlation coefficient, which down-weights regions in the face violating the symmetry. Raw images of faces without usual preliminary transformations are considered. The robust correlation coefficient based on the least weighted squares regression yields very promising results also in the localization of such faces, which are not entirely symmetric. Standard methods of statistical machine learning are applied for comparison. The robust correlation analysis can be applicable to other problems of forensic anthropology.

  3. A Robust Biomarker

    NASA Technical Reports Server (NTRS)

    Westall, F.; Steele, A.; Toporski, J.; Walsh, M. M.; Allen, C. C.; Guidry, S.; McKay, D. S.; Gibson, E. K.; Chafetz, H. S.

    2000-01-01

    containing fossil biofilm, including the 3.5 b.y..-old carbonaceous cherts from South Africa and Australia. As a result of the unique compositional, structural and "mineralisable" properties of bacterial polymer and biofilms, we conclude that bacterial polymers and biofilms constitute a robust and reliable biomarker for life on Earth and could be a potential biomarker for extraterrestrial life.

  4. Efficient and robust gradient enhanced Kriging emulators.

    SciTech Connect

    Dalbey, Keith R.

    2013-08-01

    %E2%80%9CNaive%E2%80%9D or straight-forward Kriging implementations can often perform poorly in practice. The relevant features of the robustly accurate and efficient Kriging and Gradient Enhanced Kriging (GEK) implementations in the DAKOTA software package are detailed herein. The principal contribution is a novel, effective, and efficient approach to handle ill-conditioning of GEK's %E2%80%9Ccorrelation%E2%80%9D matrix, RN%CC%83, based on a pivoted Cholesky factorization of Kriging's (not GEK's) correlation matrix, R, which is a small sub-matrix within GEK's RN%CC%83 matrix. The approach discards sample points/equations that contribute the least %E2%80%9Cnew%E2%80%9D information to RN%CC%83. Since these points contain the least new information, they are the ones which when discarded are both the easiest to predict and provide maximum improvement of RN%CC%83's conditioning. Prior to this work, handling ill-conditioned correlation matrices was a major, perhaps the principal, unsolved challenge necessary for robust and efficient GEK emulators. Numerical results demonstrate that GEK predictions can be significantly more accurate when GEK is allowed to discard points by the presented method. Numerical results also indicate that GEK can be used to break the curse of dimensionality by exploiting inexpensive derivatives (such as those provided by automatic differentiation or adjoint techniques), smoothness in the response being modeled, and adaptive sampling. Development of a suitable adaptive sampling algorithm was beyond the scope of this work; instead adaptive sampling was approximated by omitting the cost of samples discarded by the presented pivoted Cholesky approach.

  5. Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.

    PubMed

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

    2016-07-01

    This paper considers incipient sensor fault detection issue for a class of nonlinear systems with "observer unmatched" uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes. PMID:27156675

  6. Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device.

    PubMed

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

    2016-07-01

    This paper considers incipient sensor fault detection issue for a class of nonlinear systems with "observer unmatched" uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes.

  7. Observer-based H(infinity) control for networked nonlinear systems with random packet losses.

    PubMed

    Li, Jian Guo; Yuan, Jing Qi; Lu, Jun Guo

    2010-01-01

    This paper investigates the observer-based H(infinity) control problem of networked nonlinear systems with global Lipschitz nonlinearities and random communication packet losses. The random packet loss is modelled as a Bernoulli distributed white sequence with a known conditional probability distribution. In the presence of random packet losses, sufficient conditions for the existence of an observer-based feedback controller are derived, such that the closed-loop networked nonlinear system is exponentially stable in the mean-square sense, and a prescribed H(infinity) disturbance-rejection-attenuation performance is also achieved. Then a linear matrix inequality (LMI) approach for designing such an observer-based H(infinity) controller is presented. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.

  8. Robust and intelligent bearing estimation

    SciTech Connect

    Claassen, J.P.

    1998-07-01

    As the monitoring thresholds of global and regional networks are lowered, bearing estimates become more important to the processes which associate (sparse) detections and which locate events. Current methods of estimating bearings from observations by 3-component stations and arrays lack both accuracy and precision. Methods are required which will develop all the precision inherently available in the arrival, determine the measurability of the arrival, provide better estimates of the bias induced by the medium, permit estimates at lower SNRs, and provide physical insight into the effects of the medium on the estimates. Initial efforts have focused on 3-component stations since the precision is poorest there. An intelligent estimation process for 3-component stations has been developed and explored. The method, called SEE for Search, Estimate, and Evaluation, adaptively exploits all the inherent information in the arrival at every step of the process to achieve optimal results. In particular, the approach uses a consistent and robust mathematical framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, and to withdraw metrics helpful in choosing the best estimate(s) or admitting that the bearing is immeasurable. The approach is conceptually superior to current methods, particular those which rely on real values signals. The method has been evaluated to a considerable extent in a seismically active region and has demonstrated remarkable utility by providing not only the best estimates possible but also insight into the physical processes affecting the estimates. It has been shown, for example, that the best frequency at which to make an estimate seldom corresponds to the frequency having the best detection SNR and sometimes the best time interval is not at the onset of the signal. The method is capable of measuring bearing dispersion, thereby withdrawing the bearing bias as a function of frequency

  9. Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

    NASA Technical Reports Server (NTRS)

    Burken, John J.

    2005-01-01

    This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

  10. RSRE: RNA structural robustness evaluator.

    PubMed

    Shu, Wenjie; Bo, Xiaochen; Zheng, Zhiqiang; Wang, Shengqi

    2007-07-01

    Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/.

  11. Adaptive Management

    EPA Science Inventory

    Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive managem...

  12. Pervasive robustness in biological systems.

    PubMed

    Félix, Marie-Anne; Barkoulas, Michalis

    2015-08-01

    Robustness is characterized by the invariant expression of a phenotype in the face of a genetic and/or environmental perturbation. Although phenotypic variance is a central measure in the mapping of the genotype and environment to the phenotype in quantitative evolutionary genetics, robustness is also a key feature in systems biology, resulting from nonlinearities in quantitative relationships between upstream and downstream components. In this Review, we provide a synthesis of these two lines of investigation, converging on understanding how variation propagates across biological systems. We critically assess the recent proliferation of studies identifying robustness-conferring genes in the context of the nonlinearity in biological systems. PMID:26184598

  13. Population genetics of translational robustness.

    PubMed

    Wilke, Claus O; Drummond, D Allan

    2006-05-01

    Recent work has shown that expression level is the main predictor of a gene's evolutionary rate and that more highly expressed genes evolve slower. A possible explanation for this observation is selection for proteins that fold properly despite mistranslation, in short selection for translational robustness. Translational robustness leads to the somewhat paradoxical prediction that highly expressed genes are extremely tolerant to missense substitutions but nevertheless evolve very slowly. Here, we study a simple theoretical model of translational robustness that allows us to gain analytic insight into how this paradoxical behavior arises.

  14. Robustness of airline route networks

    NASA Astrophysics Data System (ADS)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

    2016-03-01

    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  15. Robust Optimization of Biological Protocols

    PubMed Central

    Flaherty, Patrick; Davis, Ronald W.

    2015-01-01

    When conducting high-throughput biological experiments, it is often necessary to develop a protocol that is both inexpensive and robust. Standard approaches are either not cost-effective or arrive at an optimized protocol that is sensitive to experimental variations. We show here a novel approach that directly minimizes the cost of the protocol while ensuring the protocol is robust to experimental variation. Our approach uses a risk-averse conditional value-at-risk criterion in a robust parameter design framework. We demonstrate this approach on a polymerase chain reaction protocol and show that our improved protocol is less expensive than the standard protocol and more robust than a protocol optimized without consideration of experimental variation. PMID:26417115

  16. RESEARCH NOTE FROM COLLABORATION: Adaptive vertex fitting

    NASA Astrophysics Data System (ADS)

    Waltenberger, Wolfgang; Frühwirth, Rudolf; Vanlaer, Pascal

    2007-12-01

    Vertex fitting frequently has to deal with both mis-associated tracks and mis-measured track errors. A robust, adaptive method is presented that is able to cope with contaminated data. The method is formulated as an iterative re-weighted Kalman filter. Annealing is introduced to avoid local minima in the optimization. For the initialization of the adaptive filter a robust algorithm is presented that turns out to perform well in a wide range of applications. The tuning of the annealing schedule and of the cut-off parameter is described using simulated data from the CMS experiment. Finally, the adaptive property of the method is illustrated in two examples.

  17. Robust controls with structured perturbations

    NASA Technical Reports Server (NTRS)

    Keel, Leehyun

    1993-01-01

    This final report summarizes the recent results obtained by the principal investigator and his coworkers on the robust stability and control of systems containing parametric uncertainty. The starting point is a generalization of Kharitonov's theorem obtained in 1989, and its generalization to the multilinear case, the singling out of extremal stability subsets, and other ramifications now constitutes an extensive and coherent theory of robust parametric stability that is summarized in the results contained here.

  18. Fireplace adapters

    SciTech Connect

    Hunt, R.L.

    1983-12-27

    An adapter is disclosed for use with a fireplace. The stove pipe of a stove standing in a room to be heated may be connected to the flue of the chimney so that products of combustion from the stove may be safely exhausted through the flue and outwardly of the chimney. The adapter may be easily installed within the fireplace by removing the damper plate and fitting the adapter to the damper frame. Each of a pair of bolts has a portion which hooks over a portion of the damper frame and a threaded end depending from the hook portion and extending through a hole in the adapter. Nuts are threaded on the bolts and are adapted to force the adapter into a tight fit with the adapter frame.

  19. Designing robust control laws using genetic algorithms

    NASA Technical Reports Server (NTRS)

    Marrison, Chris

    1994-01-01

    The purpose of this research is to create a method of finding practical, robust control laws. The robustness of a controller is judged by Stochastic Robustness metrics and the level of robustness is optimized by searching for design parameters that minimize a robustness cost function.

  20. Robust image hashing based on random Gabor filtering and dithered lattice vector quantization.

    PubMed

    Li, Yuenan; Lu, Zheming; Zhu, Ce; Niu, Xiamu

    2012-04-01

    In this paper, we propose a robust-hash function based on random Gabor filtering and dithered lattice vector quantization (LVQ). In order to enhance the robustness against rotation manipulations, the conventional Gabor filter is adapted to be rotation invariant, and the rotation-invariant filter is randomized to facilitate secure feature extraction. Particularly, a novel dithered-LVQ-based quantization scheme is proposed for robust hashing. The dithered-LVQ-based quantization scheme is well suited for robust hashing with several desirable features, including better tradeoff between robustness and discrimination, higher randomness, and secrecy, which are validated by analytical and experimental results. The performance of the proposed hashing algorithm is evaluated over a test image database under various content-preserving manipulations. The proposed hashing algorithm shows superior robustness and discrimination performance compared with other state-of-the-art algorithms, particularly in the robustness against rotations (of large degrees).

  1. On the possible role of robustness in the evolution of infectious diseases

    NASA Astrophysics Data System (ADS)

    Ogbunugafor, C. Brandon; Pease, James B.; Turner, Paul E.

    2010-06-01

    Robustness describes the capacity for a biological system to remain canalized despite perturbation. Genetic robustness affords maintenance of phenotype despite mutational input, necessarily involving the role of epistasis. Environmental robustness is phenotypic constancy in the face of environmental variation, where epistasis may be uninvolved. Here we discuss genetic and environmental robustness, from the standpoint of infectious disease evolution, and suggest that robustness may be a unifying principle for understanding how different disease agents evolve. We focus especially on viruses with RNA genomes due to their importance in the evolution of emerging diseases and as model systems to test robustness theory. We present new data on adaptive constraints for a model RNA virus challenged to evolve in response to UV radiation. We also draw attention to other infectious disease systems where robustness theory may prove useful for bridging evolutionary biology and biomedicine, especially the evolution of antibiotic resistance in bacteria, immune evasion by influenza, and malaria parasite infections.

  2. Adaptive vehicle motion estimation and prediction

    NASA Astrophysics Data System (ADS)

    Zhao, Liang; Thorpe, Chuck E.

    1999-01-01

    Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

  3. Scientific performance estimation of robustness and threat

    NASA Astrophysics Data System (ADS)

    Hoffman, John R.; Sorensen, Eric; Stelzig, Chad A.; Mahler, Ronald P. S.; El-Fallah, Adel I.; Alford, Mark G.

    2002-07-01

    For the last three years at this conference we have been describing the implementation of a unified, scientific approach to performance estimation for various aspects of data fusion: multitarget detection, tracking, and identification algorithms; sensor management algorithms; and adaptive data fusion algorithms. The proposed approach is based on finite-set statistics (FISST), a generalization of conventional statistics to multisource, multitarget problems. Finite-set statistics makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems in such a way that information can be defined and measured even though any given end-user may have conflicting or even subjective definitions of what informative means. In this presentation, we will show how to extend our previous results to two new problems. First, that of evaluating the robustness of multisensor, multitarget algorithms. Second, that of evaluating the performance of multisource-multitarget threat assessment algorithms.

  4. Robust quantum receivers for coherent state discrimination

    NASA Astrophysics Data System (ADS)

    Becerra, Francisco Elohim

    2014-05-01

    Quantum state discrimination is a central task for quantum information and is a fundamental problem in quantum mechanics. Nonorthogonal states, such as coherent states which have intrinsic quantum noise, cannot be discriminated with total certainty because of their intrinsic overlap. This nonorthogonality is at the heart of quantum key distribution for ensuring absolute secure communications between a transmitter and a receiver, and can enable many quantum information protocols based on coherent states. At the same time, while coherent states are used for communications because of their robustness to loss and simplicity of generation and detection, their nonorthogonality inherently produces errors in the process of decoding the information. The minimum error probability in the discrimination of nonorthogonal coherent states measured by an ideal lossless and noiseless conventional receiver is given by the standard quantum limit (SQL). This limit sets strict bounds on the ultimate performance of coherent communications and many coherent-state-based quantum information protocols. However, measurement strategies based on the quantum properties of these states can allow for better measurements that surpass the SQL and approach the ultimate measurement limits allowed by quantum mechanics. These measurement strategies can allow for optimally extracting information encoded in these states for coherent and quantum communications. We present the demonstration of a receiver based on adaptive measurements and single-photon counting that unconditionally discriminates multiple nonorthogonal coherent states below the SQL. We also discuss the potential of photon-number-resolving detection to provide robustness and high sensitivity under realistic conditions for an adaptive coherent receiver with detectors with finite photon-number resolution.

  5. A robust multilevel simultaneous eigenvalue solver

    NASA Technical Reports Server (NTRS)

    Costiner, Sorin; Taasan, Shlomo

    1993-01-01

    Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

  6. The complexity and robustness of metro networks

    NASA Astrophysics Data System (ADS)

    Derrible, Sybil; Kennedy, Christopher

    2010-09-01

    Transportation systems, being real-life examples of networks, are particularly interesting to analyze from the viewpoint of the new and rapidly emerging field of network science. Two particular concepts seem to be particularly relevant: scale-free patterns and small-worlds. By looking at 33 metro systems in the world, this paper adapts network science methodologies to the transportation literature, and offers one application to the robustness of metros; here, metro refers to urban rail transit with exclusive right-of-way, whether it is underground, at grade or elevated. We find that most metros are indeed scale-free (with scaling factors ranging from 2.10 to 5.52) and small-worlds; they show atypical behaviors, however, with increasing size. In particular, the presence of transfer-hubs (stations hosting more than three lines) results in relatively large scaling factors. The analysis provides insights/recommendations for increasing the robustness of metro networks. Smaller networks should focus on creating transfer stations, thus generating cycles to offer alternative routes. For larger networks, few stations seem to detain a certain monopole on transferring, it is therefore important to create additional transfers, possibly at the periphery of city centers; the Tokyo system seems to remarkably incorporate these properties.

  7. Robustness to Resilience: Transforming Hydrologic Risk

    NASA Astrophysics Data System (ADS)

    Karlovits, G. S.

    2014-12-01

    Risk management in water resources has relied on reducing randomness and smoothing variability. Watersheds are engineered to avoid small but frequent flood events or water shortages - this is the hallmark of a robust system. However, the artificial reduction of natural variability in hydrology creates an increasingly fragile watershed. Invisible risk accumulates each year that the system performs within its design capacity, as development expands into hazard areas and community preparedness and consciousness for the hazard is reduced in its absence. While the benefits of these behaviors are immediate and visible, exposure to catastrophic risk grows invisibly under the surface. We consider risk as the probability of an adverse event and its consequence. Increasing exposure to risk in engineered watersheds is typically driven by increasing the consequences for equally probable events, as the same magnitude flood causes more damage. However, changing climate and land use alters hydrology such that large flooding is more probable. Uncertainty in assessing the probability or consequence of these events is increased by anthropogenic change. Robust systems with a fixed capacity become less reliable in a changing environment. Communities will require resilient, adaptable measures for reducing current and future potential risk exposure. Resilient measures - such as floodplain management and integrated water resources management - will require some amount of concession to damage from small but frequent detrimental events in order to reduce the risk of catastrophe.

  8. Robust hashing for 3D models

    NASA Astrophysics Data System (ADS)

    Berchtold, Waldemar; Schäfer, Marcel; Rettig, Michael; Steinebach, Martin

    2014-02-01

    3D models and applications are of utmost interest in both science and industry. With the increment of their usage, their number and thereby the challenge to correctly identify them increases. Content identification is commonly done by cryptographic hashes. However, they fail as a solution in application scenarios such as computer aided design (CAD), scientific visualization or video games, because even the smallest alteration of the 3D model, e.g. conversion or compression operations, massively changes the cryptographic hash as well. Therefore, this work presents a robust hashing algorithm for 3D mesh data. The algorithm applies several different bit extraction methods. They are built to resist desired alterations of the model as well as malicious attacks intending to prevent correct allocation. The different bit extraction methods are tested against each other and, as far as possible, the hashing algorithm is compared to the state of the art. The parameters tested are robustness, security and runtime performance as well as False Acceptance Rate (FAR) and False Rejection Rate (FRR), also the probability calculation of hash collision is included. The introduced hashing algorithm is kept adaptive e.g. in hash length, to serve as a proper tool for all applications in practice.

  9. Adaptive Algebraic Multigrid Methods

    SciTech Connect

    Brezina, M; Falgout, R; MacLachlan, S; Manteuffel, T; McCormick, S; Ruge, J

    2004-04-09

    Our ability to simulate physical processes numerically is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black-box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to assumptions made on the near-null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. The principles which guide the adaptivity are highlighted, as well as their application to algebraic multigrid solution of certain symmetric positive-definite linear systems.

  10. Adaptive SPECT

    PubMed Central

    Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.

    2008-01-01

    Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485

  11. Adaptive Computing.

    ERIC Educational Resources Information Center

    Harrell, William

    1999-01-01

    Provides information on various adaptive technology resources available to people with disabilities. (Contains 19 references, an annotated list of 129 websites, and 12 additional print resources.) (JOW)

  12. Contour adaptation.

    PubMed

    Anstis, Stuart

    2013-01-01

    It is known that adaptation to a disk that flickers between black and white at 3-8 Hz on a gray surround renders invisible a congruent gray test disk viewed afterwards. This is contrast adaptation. We now report that adapting simply to the flickering circular outline of the disk can have the same effect. We call this "contour adaptation." This adaptation does not transfer interocularly, and apparently applies only to luminance, not color. One can adapt selectively to only some of the contours in a display, making only these contours temporarily invisible. For instance, a plaid comprises a vertical grating superimposed on a horizontal grating. If one first adapts to appropriate flickering vertical lines, the vertical components of the plaid disappears and it looks like a horizontal grating. Also, we simulated a Cornsweet (1970) edge, and we selectively adapted out the subjective and objective contours of a Kanisza (1976) subjective square. By temporarily removing edges, contour adaptation offers a new technique to study the role of visual edges, and it demonstrates how brightness information is concentrated in edges and propagates from them as it fills in surfaces.

  13. Intermittent observer-based consensus control for multi-agent systems with switching topologies

    NASA Astrophysics Data System (ADS)

    Xu, Xiaole; Gao, Lixin

    2016-06-01

    In this paper, we focus on the consensus problem for leaderless and leader-followers multi-agent systems with periodically intermittent control. The dynamics of each agent in the system is a linear system, and the interconnection topology among the agents is assumed to be switching. We assume that each agent can only share the outputs with its neighbours. Therefore, a class of distributed intermittent observer-based consensus protocols are proposed for each agent. First, in order to solve this problem, a parameter-dependent common Lyapunov function is constructed. Using this function, we prove that all agents can access a prescribed value, under the designed intermittent controller and observer, if there are suitable conditions on communication. Second, based on the investigation of the leader-following consensus problem, we design a new distributed intermittent observer-based protocol for each following agent. Finally, we provide an illustrative example to verify the effectiveness of the proposed approach.

  14. Observationally-Based Data/Model Metrics from the Southern Ocean Climate Model Atlas

    NASA Astrophysics Data System (ADS)

    Abell, J.; Russell, J. L.; Goodman, P. J.

    2015-12-01

    The Southern Ocean Climate Model Atlas makes available observationally-based standardized data/model metrics of the latest simulations of climate and projections of climate change from available climate models. Global climate model simulations differ greatly in the Southern Ocean, so the development of consistent, observationally-based metrics, by which to assess the fidelity of model simulations is essential. We will present metrics showing and quantifying the results of the modern day climate simulations over the Southern Ocean from models submitted as part of the CMIP5/IPCC-AR5 process. Our analysis will focus on the simulations of the temperature, salinity and carbon at various depths and along significant hydrographic sections. The models exhibit different skill levels with various metrics between models and also within individual models.

  15. Observer-based H∞ resilient control for a class of switched LPV systems and its application

    NASA Astrophysics Data System (ADS)

    Yang, Dong; Zhao, Jun

    2016-11-01

    This paper deals with the issue of observer-based H∞ resilient control for a class of switched linear parameter-varying (LPV) systems by utilising a multiple parameter-dependent Lyapunov functions method. First, attention is focused upon the design of a resilient observer, an observer-based resilient controller and a parameter and estimate state-dependent switching signal, which can stabilise and achieve the disturbance attenuation for the given systems. Then, a solvability condition of the H∞ resilient control problem is given in terms of matrix inequality for the switched LPV systems. This condition allows the H∞ resilient control problem for each individual subsystem to be unsolvable. The observer, controller, and switching signal are explicitly computed by solving linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed control scheme is illustrated by its application to a turbofan engine, which can hardly be handled by the existing approaches.

  16. On the optimal minimum order observer-based compensator and the limited state variable feedback controller

    NASA Technical Reports Server (NTRS)

    Llorens-Ortiz, B.

    1976-01-01

    Four design problems are considered: two on the optimal minimum order observer-based compensator design and two on the optimal limited state variable feedback controller. The problem of designing an optimal discrete time linear time-invariant observer-based compensator for the regulation of an n dimensional linear discrete time time-invariant plant with m independent outputs is considered. This is a stochastic design problem to the extent that the initial plant state is assumed to be a random vector with known first and second order statistics. The compensator parameters are obtained by minimizing the expectation, with respect to the initial conditions, of the standard cost, quadratic in the state and control vectors with the inclusion of cross terms.

  17. Robust human motion detection via fuzzy set based image understanding

    NASA Astrophysics Data System (ADS)

    Li, Qin; You, Jane

    2006-02-01

    This paper presents an image understanding approach to monitor human movement and identify the abnormal circumstance by robust motion detection for the care of the elderly in a home-based environment. In contrast to the conventional approaches which apply either a single feature extraction scheme or a fixed object model for motion detection and tracking, we introduce a multiple feature extraction scheme for robust motion detection. The proposed algorithms include 1) multiple image feature extraction including the fuzzy compactness based detection of interesting points and fuzzy blobs, 2) adaptive image segmentation via multiple features, 3) Hierarchical motion detection, 4) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 5) Fuzzy decision making via multiple features.

  18. Real-time location of coherent sound sources by the observer-based array algorithm

    NASA Astrophysics Data System (ADS)

    Huang, Xun

    2011-06-01

    Acoustic arrays have become an important tool in noise identification for aerospace measurement applications, and the conventional beamforming algorithm has been adopted as a processing technique of choice. In most practical cases the beamforming computations have to be conducted off-line due to extensive computational time requirements. An alternative algorithm with real-time capability has been proposed. The algorithm has a form similar to a classical observer whilst working in the frequency domain for the array processing. The performance of this observer-based algorithm is studied here in a simulation case and in an experimental case by comparing it to a conventional beamforming method. In this paper it is shown that the observer-based algorithm could release the coherence restriction between the background noise and the signal of interest. The proposed observer-based algorithm also has the capability of operating over sampling blocks recursively. The convergence rate of this recursive algorithm is also satisfactory for the simulation case. As a result, a great deal of experimental time could be saved as any testing defects could be revealed instantaneously and corrected on-site. In addition, this innovative approach provides an alternative perspective from which many techniques already in use could be extended to this new application area of array processing.

  19. Robust control of hypersonic aircraft

    NASA Astrophysics Data System (ADS)

    Fan, Yong-hua; Yang, Jun; Zhang, Yu-zhuo

    2007-11-01

    Design of a robust controller for the longitudinal dynamics of a hypersonic aircraft by using parameter space method is present. The desirable poles are mapped to the parameter space of the controller using pole placement approach in this method. The intersection of the parameter space is the common controller for the multiple mode system. This controller can meet the need of the different phases of aircraft. It has been proved by simulation that the controller has highly performance of precision and robustness for the disturbance caused by separation, cowl open, fuel on and fuel off and perturbation caused by unknown dynamics.

  20. Robust Sparse Blind Source Separation

    NASA Astrophysics Data System (ADS)

    Chenot, Cecile; Bobin, Jerome; Rapin, Jeremy

    2015-11-01

    Blind Source Separation is a widely used technique to analyze multichannel data. In many real-world applications, its results can be significantly hampered by the presence of unknown outliers. In this paper, a novel algorithm coined rGMCA (robust Generalized Morphological Component Analysis) is introduced to retrieve sparse sources in the presence of outliers. It explicitly estimates the sources, the mixing matrix, and the outliers. It also takes advantage of the estimation of the outliers to further implement a weighting scheme, which provides a highly robust separation procedure. Numerical experiments demonstrate the efficiency of rGMCA to estimate the mixing matrix in comparison with standard BSS techniques.

  1. Robust Burg estimation of stationary autoregressive mixtures covariance

    NASA Astrophysics Data System (ADS)

    Decurninge, Alexis; Barbaresco, Frédéric

    2015-01-01

    Burg estimators are classically used for the estimation of the autocovariance of a stationary autoregressive process. We propose to consider scale mixtures of stationary autoregressive processes, a non-Gaussian extension of the latter. The traces of such processes are Spherically Invariant Random Vectors (SIRV) with a constraint on the scatter matrix due to the autoregressive model. We propose adaptations of the Burg estimators to the considered models and their associated robust versions based on geometrical considerations.

  2. Climate adaptation

    NASA Astrophysics Data System (ADS)

    Kinzig, Ann P.

    2015-03-01

    This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.

  3. Adaptive Controller Effects on Pilot Behavior

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  4. Network Robustness: the whole story

    NASA Astrophysics Data System (ADS)

    Longjas, A.; Tejedor, A.; Zaliapin, I. V.; Ambroj, S.; Foufoula-Georgiou, E.

    2014-12-01

    A multitude of actual processes operating on hydrological networks may exhibit binary outcomes such as clean streams in a river network that may become contaminated. These binary outcomes can be modeled by node removal processes (attacks) acting in a network. Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. However, the current definition of robustness is only accounting for the connectivity of the nodes unaffected by the attack. Here, we put forward the idea that the connectivity of the affected nodes can play a crucial role in proper evaluation of the overall network robustness and its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and the efficiency of building-up the IN. This approach is motivated by concrete applied problems, since, for example, if we study the dynamics of contamination in river systems, it is necessary to know both the connectivity of the healthy and contaminated parts of the river to assess its ecological functionality. We show that trade-offs between the efficiency of the Active and Idle network dynamics give rise to surprising crossovers and re-ranking of different attack strategies, pointing to significant implications for decision making.

  5. Robust Sliding Window Synchronizer Developed

    NASA Technical Reports Server (NTRS)

    Chun, Kue S.; Xiong, Fuqin; Pinchak, Stanley

    2004-01-01

    The development of an advanced robust timing synchronization scheme is crucial for the support of two NASA programs--Advanced Air Transportation Technologies and Aviation Safety. A mobile aeronautical channel is a dynamic channel where various adverse effects--such as Doppler shift, multipath fading, and shadowing due to precipitation, landscape, foliage, and buildings--cause the loss of symbol timing synchronization.

  6. Mental Models: A Robust Definition

    ERIC Educational Resources Information Center

    Rook, Laura

    2013-01-01

    Purpose: The concept of a mental model has been described by theorists from diverse disciplines. The purpose of this paper is to offer a robust definition of an individual mental model for use in organisational management. Design/methodology/approach: The approach adopted involves an interdisciplinary literature review of disciplines, including…

  7. Robust Portfolio Optimization Using Pseudodistances

    PubMed Central

    2015-01-01

    The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

  8. Robust design of dynamic observers

    NASA Technical Reports Server (NTRS)

    Bhattacharyya, S. P.

    1974-01-01

    The two (identity) observer realizations z = Mz + Ky and z = transpose of Az + transpose of K(y - transpose of Cz), respectively called the open loop and closed loop realizations, for the linear system x = Ax, y = Cx are analyzed with respect to the requirement of robustness; i.e., the requirement that the observer continue to regulate the error x - z satisfactorily despite small variations in the observer parameters from the projected design values. The results show that the open loop realization is never robust, that robustness requires a closed loop implementation, and that the closed loop realization is robust with respect to small perturbations in the gains transpose of K if and only if the observer can be built to contain an exact replica of the unstable and underdamped dynamics of the system being observed. These results clarify the stringent accuracy requirements on both models and hardware that must be met before an observer can be considered for use in a control system.

  9. Observer-based output feedback control of discrete-time linear systems with input and output delays

    NASA Astrophysics Data System (ADS)

    Zhou, Bin

    2014-11-01

    In this paper, we study observer-based output feedback control of discrete-time linear systems with both multiple input and output delays. By generalising our recently developed truncated predictor feedback approach for state feedback stabilisation of discrete-time time-delay systems to the design of observer-based output feedback, two types of observer-based output feedback controllers, one being memory and the other memoryless, are constructed. Both full-order and reduced-order observer-based controllers are established in both the memory and memoryless schemes. It is shown that the separation principle holds for the memory observer-based output feedback controllers, but does not hold for the memoryless ones. We further show that the proposed observer-based output feedback controllers solve both the l2 and l∞ semi-global stabilisation problems. A numerical example is given to illustrate the effectiveness of the proposed approaches.

  10. S-system-based analysis of the robust properties common to many biochemical network models.

    PubMed

    Matsuoka, Yu; Jahan, Nusrat; Kurata, Hiroyuki

    2016-05-01

    Robustness is a key feature to characterize the adaptation of organisms to changes in their internal and external environments. A broad range of kinetic or dynamic models of biochemical systems have been developed. Robustness analyses are attractive for exploring some common properties of many biochemical models. To reveal such features, we transform different types of mathematical equations into a standard or intelligible formula and use the multiple parameter sensitivity (MPS) to identify some factors critically responsible for the total robustness to many perturbations. The MPS would be determined by the top quarter of the highly sensitive parameters rather than the single parameter with the maximum sensitivity. The MPS did not show any correlation to the network size. The MPS is closely related to the standard deviation of the sensitivity profile. A decrease in the standard deviation enhanced the total robustness, which shows the hallmark of distributed robustness that many factors (pathways) involve the total robustness.

  11. Observer-based H∞ controller for 2-D T-S fuzzy model

    NASA Astrophysics Data System (ADS)

    Li, Lizhen

    2016-10-01

    This paper develops a method of fuzzy observer-based H∞ controller design for two-dimensional (2-D) discrete Takagi-Sugeno (T-S) fuzzy systems. By reformulating the system, a linear matrix inequality (LMI)-based sufficient condition is derived. Then the fuzzy controller and the fuzzy observer can be independently designed, which guarantee an H∞ noise attenuation γ of the whole system. Owing to the introduction of free matrices, the presented design method has a wider range of application and can guarantee a better H∞ performance of the closed-loop fuzzy control system. Simulation results have demonstrated the effectiveness of the proposed method.

  12. A New Earth Observation Based Geographic Ecosystem Monitoring And Assessment Service

    NASA Astrophysics Data System (ADS)

    Haas, E.; Lyon, D.; Eyre, C. C.; Hoffmann, C.; Hedley, J.; Bondo, T.; Ledwith, M.

    2013-12-01

    Earth observation based mapping of the physical and social landscape can improve the understanding of the economic and societal benefits arising from specific ecosystems. The European Space Agency (ESA) G- ECO-MON - Geographic Ecosystem Monitoring and Assessment Service project is intended to show that Earth Observation (EO) applications are neither costly nor complex and are globally accessible. Therefore they are ideally suited for ecosystem service monitoring and assessment. By supporting better understanding of ecosystem services, EO applications support the sustainable management of natural capital and the wider environment. EO can thus make an important contribution both to organisations and to the environment, as well as society at large.

  13. Catalase activity as a biomarker for mild-stress-induced robustness in Bacillus weihenstephanensis.

    PubMed

    den Besten, Heidy M W; Effraimidou, Styliani; Abee, Tjakko

    2013-01-01

    Microorganisms are able to survive and grow in changing environments by activating stress adaptation mechanisms which may enhance bacterial robustness. Stress-induced enhanced robustness complicates the predictability of microbial inactivation. Using psychrotolerant Bacillus weihenstephanensis strain KBAB4 as a model, we investigated the impact of the culturing temperature on mild-oxidative-stress-induced (cross-)protection toward multiple stresses, including severe oxidative, heat, and acid stresses. Culturing at a refrigeration temperature (7°C) compared to the optimal growth temperature (30°C) affected both the robustness level of B. weihenstephanensis and the oxidative stress adaptive response. Scavengers of reactive oxygen species have a crucial role in adaptation to oxidative stresses, and this points to a possible predictive role in mild-oxidative-stress-induced robustness. Therefore, the catalase activity was determined upon mild oxidative stress treatment and was demonstrated to be significantly correlated with the robustness level of mild-stress-treated cells toward severe oxidative and heat stresses but not toward severe acid stress for cells grown at both refrigeration and optimal temperatures. The quantified correlations supported the predictive quality of catalase activity as a biomarker and also underlined that the predictive quality is stress specific. Biomarkers that are able to predict stress-induced enhanced robustness can be used to better understand stress adaptation mechanisms and might allow the design of effective combinations of hurdles to control microbial behavior.

  14. Predictor-Based Model Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2009-01-01

    This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.

  15. Development of a novel disturbance observer based fractional order PD controller for a gun control system.

    PubMed

    Gao, Qiang; Zheng, Liang; Chen, Jilin; Wang, Li; Hou, Yuanlong

    2014-01-01

    Motion control of gun barrels is an ongoing topic for the development of gun control equipment (GCE) with excellent performances. In this paper, a novel disturbance observer (DOB) based fractional order PD (FOPD) control strategy is proposed for the GCE. By adopting the DOB, the control system behaves as if it were the nominal closed-loop system in the absence of disturbances and uncertainties. The optimal control parameters of the FOPD are determined from the loop-shaping perspective, and the Q-filter of the DOB is deliberately designed with consideration of system robustness. The linear frame of the proposed control system will enable the analysis process more convenient. The disturbance rejection properties and the tracking performances of the control system are investigated by both numerical and experimental tests, the results demonstrate that the proposed DOB based FOPD control system is of more robustness, and it is much more suitable for the gun control system with strong nonlinearity and disturbance.

  16. Toothbrush Adaptations.

    ERIC Educational Resources Information Center

    Exceptional Parent, 1987

    1987-01-01

    Suggestions are presented for helping disabled individuals learn to use or adapt toothbrushes for proper dental care. A directory lists dental health instructional materials available from various organizations. (CB)

  17. Observation-based global biospheric excess radiocarbon inventory 1963-2005

    NASA Astrophysics Data System (ADS)

    Naegler, Tobias; Levin, Ingeborg

    2009-09-01

    For the very first time, we present an observation-based estimate of the temporal development of the biospheric excess radiocarbon (14C) inventory IB14,E, i.e., the change in the biospheric 14C inventory relative to prebomb times (1940s). IB14,E was calculated for the period 1963-2005 with a simple budget approach as the difference between the accumulated excess 14C production by atmospheric nuclear bomb tests and the nuclear industry and observation-based reconstructions of the excess 14C inventories in the atmosphere and the ocean. IB14,E increased from the late 1950s onward to maximum values between 126 and 177 × 1026 atoms 14C between 1981 and 1985. In the early 1980s, the biosphere turned from a sink to a source of excess 14C. Consequently, IB14,E decreased to values of 108-167 × 1026 atoms 14C in 2005. The uncertainty of IB14,E is dominated by uncertainties in the total bomb 14C production and the oceanic excess 14C inventory. Unfortunately, atmospheric Δ14CO2 from the early 1980s lack the necessary precision to reveal the expected small change in the amplitude and phase of atmospheric Δ14C seasonal cycle due to the sign flip in the biospheric net 14C flux during that time.

  18. Algebraic connectivity and graph robustness.

    SciTech Connect

    Feddema, John Todd; Byrne, Raymond Harry; Abdallah, Chaouki T.

    2009-07-01

    Recent papers have used Fiedler's definition of algebraic connectivity to show that network robustness, as measured by node-connectivity and edge-connectivity, can be increased by increasing the algebraic connectivity of the network. By the definition of algebraic connectivity, the second smallest eigenvalue of the graph Laplacian is a lower bound on the node-connectivity. In this paper we show that for circular random lattice graphs and mesh graphs algebraic connectivity is a conservative lower bound, and that increases in algebraic connectivity actually correspond to a decrease in node-connectivity. This means that the networks are actually less robust with respect to node-connectivity as the algebraic connectivity increases. However, an increase in algebraic connectivity seems to correlate well with a decrease in the characteristic path length of these networks - which would result in quicker communication through the network. Applications of these results are then discussed for perimeter security.

  19. Robust dynamic mitigation of instabilities

    NASA Astrophysics Data System (ADS)

    Kawata, S.; Karino, T.

    2015-04-01

    A dynamic mitigation mechanism for instability growth was proposed and discussed in the paper [S. Kawata, Phys. Plasmas 19, 024503 (2012)]. In the present paper, the robustness of the dynamic instability mitigation mechanism is discussed further. The results presented here show that the mechanism of the dynamic instability mitigation is rather robust against changes in the phase, the amplitude, and the wavelength of the wobbling perturbation applied. Generally, instability would emerge from the perturbation of the physical quantity. Normally, the perturbation phase is unknown so that the instability growth rate is discussed. However, if the perturbation phase is known, the instability growth can be controlled by a superposition of perturbations imposed actively: If the perturbation is induced by, for example, a driving beam axis oscillation or wobbling, the perturbation phase could be controlled, and the instability growth is mitigated by the superposition of the growing perturbations.

  20. Robust dynamic mitigation of instabilities

    SciTech Connect

    Kawata, S.; Karino, T.

    2015-04-15

    A dynamic mitigation mechanism for instability growth was proposed and discussed in the paper [S. Kawata, Phys. Plasmas 19, 024503 (2012)]. In the present paper, the robustness of the dynamic instability mitigation mechanism is discussed further. The results presented here show that the mechanism of the dynamic instability mitigation is rather robust against changes in the phase, the amplitude, and the wavelength of the wobbling perturbation applied. Generally, instability would emerge from the perturbation of the physical quantity. Normally, the perturbation phase is unknown so that the instability growth rate is discussed. However, if the perturbation phase is known, the instability growth can be controlled by a superposition of perturbations imposed actively: If the perturbation is induced by, for example, a driving beam axis oscillation or wobbling, the perturbation phase could be controlled, and the instability growth is mitigated by the superposition of the growing perturbations.

  1. Preservation of genetic and regulatory robustness in ancient gene duplicates of Saccharomyces cerevisiae

    PubMed Central

    Keane, Orla M.; Toft, Christina; Carretero-Paulet, Lorenzo; Jones, Gary W.

    2014-01-01

    Biological systems remain robust against certain genetic and environmental challenges. Robustness allows the exploration of ecological adaptations. It is unclear what factors contribute to increasing robustness. Gene duplication has been considered to increase genetic robustness through functional redundancy, accelerating the evolution of novel functions. However, recent findings have questioned the link between duplication and robustness. In particular, it remains elusive whether ancient duplicates still bear potential for innovation through preserved redundancy and robustness. Here we have investigated this question by evolving the yeast Saccharomyces cerevisiae for 2200 generations under conditions allowing the accumulation of deleterious mutations, and we put mechanisms of mutational robustness to a test. S. cerevisiae declined in fitness along the evolution experiment, but this decline decelerated in later passages, suggesting functional compensation of mutated genes. We resequenced 28 genomes from experimentally evolved S. cerevisiae lines and found more mutations in duplicates—mainly small-scale duplicates—than in singletons. Genetically interacting duplicates evolved similarly and fixed more amino acid–replacing mutations than expected. Regulatory robustness of the duplicates was supported by a larger enrichment for mutations at the promoters of duplicates than at those of singletons. Analyses of yeast gene expression conditions showed a larger variation in the duplicates’ expression than that of singletons under a range of stress conditions, sparking the idea that regulatory robustness allowed a wider range of phenotypic responses to environmental stresses, hence faster adaptations. Our data support the persistence of genetic and regulatory robustness in ancient duplicates and its role in adaptations to stresses. PMID:25149527

  2. Robust, optimal subsonic airfoil shapes

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan (Inventor)

    2008-01-01

    Method system, and product from application of the method, for design of a subsonic airfoil shape, beginning with an arbitrary initial airfoil shape and incorporating one or more constraints on the airfoil geometric parameters and flow characteristics. The resulting design is robust against variations in airfoil dimensions and local airfoil shape introduced in the airfoil manufacturing process. A perturbation procedure provides a class of airfoil shapes, beginning with an initial airfoil shape.

  3. Robust flight control of rotorcraft

    NASA Astrophysics Data System (ADS)

    Pechner, Adam Daniel

    With recent design improvement in fixed wing aircraft, there has been a considerable interest in the design of robust flight control systems to compensate for the inherent instability necessary to achieve desired performance. Such systems are designed for maximum available retention of stability and performance in the presence of significant vehicle damage or system failure. The rotorcraft industry has shown similar interest in adopting these reconfigurable flight control schemes specifically because of their ability to reject disturbance inputs and provide a significant amount of robustness for all but the most catastrophic of situations. The research summarized herein focuses on the extension of the pseudo-sliding mode control design procedure interpreted in the frequency domain. Application of the technique is employed and simulated on two well known helicopters, a simplified model of a hovering Sikorsky S-61 and the military's Black Hawk UH-60A also produced by Sikorsky. The Sikorsky helicopter model details are readily available and was chosen because it can be limited to pitch and roll motion reducing the number of degrees of freedom and yet contains two degrees of freedom, which is the minimum requirement in proving the validity of the pseudo-sliding control technique. The full order model of a hovering Black Hawk system was included both as a comparison to the S-61 helicopter design system and as a means to demonstrate the scaleability and effectiveness of the control technique on sophisticated systems where design robustness is of critical concern.

  4. Designing for Damage: Robust Flight Control Design using Sliding Mode Techniques

    NASA Technical Reports Server (NTRS)

    Vetter, T. K.; Wells, S. R.; Hess, Ronald A.; Bacon, Barton (Technical Monitor); Davidson, John (Technical Monitor)

    2002-01-01

    A brief review of sliding model control is undertaken, with particular emphasis upon the effects of neglected parasitic dynamics. Sliding model control design is interpreted in the frequency domain. The inclusion of asymptotic observers and control 'hedging' is shown to reduce the effects of neglected parasitic dynamics. An investigation into the application of observer-based sliding mode control to the robust longitudinal control of a highly unstable is described. The sliding mode controller is shown to exhibit stability and performance robustness superior to that of a classical loop-shaped design when significant changes in vehicle and actuator dynamics are employed to model airframe damage.

  5. Reciprocity Between Robustness of Period and Plasticity of Phase in Biological Clocks

    NASA Astrophysics Data System (ADS)

    Hatakeyama, Tetsuhiro S.; Kaneko, Kunihiko

    2015-11-01

    Circadian clocks exhibit the robustness of period and plasticity of phase against environmental changes such as temperature and nutrient conditions. Thus far, however, it is unclear how both are simultaneously achieved. By investigating distinct models of circadian clocks, we demonstrate reciprocity between robustness and plasticity: higher robustness in the period implies higher plasticity in the phase, where changes in period and in phase follow a linear relationship with a negative coefficient. The robustness of period is achieved by the adaptation on the limit cycle via a concentration change of a buffer molecule, whose temporal change leads to a phase shift following a shift of the limit-cycle orbit in phase space. Generality of reciprocity in clocks with the adaptation mechanism is confirmed with theoretical analysis of simple models, while biological significance is discussed.

  6. Robust Optimization Model and Algorithm for Railway Freight Center Location Problem in Uncertain Environment

    PubMed Central

    He, Shi-wei; Song, Rui; Sun, Yang; Li, Hao-dong

    2014-01-01

    Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable. PMID:25435867

  7. Observer-based clutch disengagement control during gear shift process of automated manual transmission

    NASA Astrophysics Data System (ADS)

    Gao, Bingzhao; Lei, Yulong; Ge, Anlin; Chen, Hong; Sanada, Kazushi

    2011-05-01

    A clutch disengagement strategy is proposed for the shift control of automated manual transmissions. The control strategy is based on a drive shaft torque observer. With the estimated drive shaft torque, the clutch can be disengaged as fast as possible without large driveline oscillations, which contributes to the reduction of total shift time and shift shock. The proposed control strategy is tested on a complete powertrain simulation model. It is verified that the system is robust to the variations of driving conditions, such as vehicle mass and road grade. It is also demonstrated that the revised system with switched gain can provide satisfactory performance even under large estimation error of the engine torque.

  8. National-level progress on adaptation

    NASA Astrophysics Data System (ADS)

    Lesnikowski, Alexandra; Ford, James; Biesbroek, Robbert; Berrang-Ford, Lea; Heymann, S. Jody

    2016-03-01

    It is increasingly evident that adaptation will figure prominently in the post-2015 United Nations climate change agreement. As adaptation obligations under the United Nations Framework Convention on Climate Change evolve, more rigorous approaches to measuring adaptation progress among parties will be critical. In this Letter we elaborate on an emerging area of research referred to as `adaptation tracking’, which has potential to inform development of a global adaptation monitoring framework. We evaluate this potential by presenting evidence on policy change for 41 high-income countries between 2010 and 2014. We examine whether countries that were in early stages of adaptation planning in 2010 are making progress to close adaptation gaps, and how the landscape of adaptation in these countries has evolved. In total we find an 87% increase in reported adaptation policies and measures, and evidence that implementation of concrete adaptation initiatives is growing. Reflecting on the strengths and challenges of this early methodology, we further discuss how adaptation tracking practices could guide development of a robust framework for monitoring global adaptation progress and inform future research on policy change across countries.

  9. Disturbance observer based pitch control of wind turbines for disturbance rejection

    NASA Astrophysics Data System (ADS)

    Yuan, Yuan; Chen, Xu; Tang, Jiong

    2016-04-01

    In this research, a disturbance observer based (DOB) control scheme is illustrated to reject the unknown low frequency disturbances to wind turbines. Specifically, we aim at maintaining the constant output power but achieving better generator speed regulation when the wind turbine is operated at time-varying and turbulent wind field. The disturbance observer combined with a filter is designed to asymptotically reject the persistent unknown time-varying disturbances. The proposed algorithm is tested in both linearized and nonlinear NREL offshore 5-MW baseline wind turbine. The application of this DOB pitch controller achieves improved power and speed regulation in Region 3 compared with a baseline gain scheduling PID collective controller both in linearized and nonlinear plant.

  10. Observer based output feedback tuning for underwater remotely operated vehicle based on linear quadratic performance

    NASA Astrophysics Data System (ADS)

    Aras, Mohd Shahrieel Mohd; Abdullah, Shahrum Shah; Kamarudin, Muhammad Nizam; Rahman, Ahmad Fadzli Nizam Abdul; Azis, Fadilah Abd; Jaafar, Hazriq Izzuan

    2015-05-01

    This paper describes the effectiveness of observer-based output feedback for Unmanned Underwater Vehicle (UUV) with Linear Quadratic Regulation (LQR) performance. Tuning of observer parameters is crucial for tracking purpose. Prior to tuning facility, the ranges of observer and LQR parameters are obtained via system output cum error. The validation of this technique using unmanned underwater vehicles called Remotely Operated Vehicle (ROV) modelling helps to improve steady state performance of system response. The ROV modeling is focused for depth control using ROV 1 developed by the Underwater Technology Research Group (UTeRG). The results are showing that this technique improves steady state performances in term of overshoot and settling time of the system response.

  11. Observer-based approximate optimal tracking control for time-delay systems with external disturbances

    NASA Astrophysics Data System (ADS)

    Su, Hao; Tang, Gong-You

    2016-09-01

    This paper proposes a successive approximation design approach of observer-based optimal tracking controllers for time-delay systems with external disturbances. To solve a two-point boundary value problem with time-delay and time-advance terms and obtain the optimal tracking control law, two sequences of vector differential equations are constructed first. Second, the convergence of the sequences of the vector differential equations is proved to guarantee the existence and uniqueness of the control law. Third, a design algorithm of the optimal tracking control law is presented and the physically realisable problem is addressed by designing a disturbance state observer and a reference input state observer. An example of an industrial electric heater is given to demonstrate the efficiency of the proposed approach.

  12. A behavior- and observation-based monitoring process for safety management.

    PubMed

    Nascimento, Cesar F; Frutuoso E Melo, Paulo Fernando F

    2010-01-01

    The objective of this paper is to demonstrate that a combination of a behavior-based monitoring process--using an at-risk behavior and unsafe condition observation system--and an observation-based safety adherence monitoring process that can indicate the compliance level with well-defined and agreed safety critical aspects and operational practices and procedures will be an effective safety management tool. This tool herein described represents a particular case, developed by a Praxair Inc. subsidiary in Brazil. Other safety surveillance systems usually adopted in industrial environments can rarely be used on construction sites. They also do not share information, knowledge and skills among the safety staff and other professionals invited to observe, usually covering specific tasks or specific professionals only, not a complete working area, which causes functional observing and monitoring limitations in terms of capturing behaviors and environmental safety issues. This tool also offers a wide range of learning opportunities and continuous improvement.

  13. Observer-based distributed consensus for general nonlinear multi-agent systems with interval control inputs

    NASA Astrophysics Data System (ADS)

    Zhang, Wentao; Liu, Yang

    2016-01-01

    In this paper, observer-based distributed consensus for general nonlinear multi-agent systems with interval control inputs under strongly connected balanced topology is encountered when the relative states of agents are unavailable or undesirable. Theoretical analysis method is further extended to the case of general nonlinear multi-agent systems under switching setting. Moreover, tracking problem on the leader-follower scenario is also explicitly investigated under a mutual assumption that the communication graph, which represents the interaction among agents, contains a directed spanning tree with the leader as its root. It is shown that the consensus for underlying considered multi-agent systems can be desirable as long as the data missing rate does not exceed a certain threshold. Finally, simulation examples are presented to effectively corroborate the analytical findings.

  14. Adaptive Development

    NASA Technical Reports Server (NTRS)

    2005-01-01

    The goal of this research is to develop and demonstrate innovative adaptive seal technologies that can lead to dramatic improvements in engine performance, life, range, and emissions, and enhance operability for next generation gas turbine engines. This work is concentrated on the development of self-adaptive clearance control systems for gas turbine engines. Researchers have targeted the high-pressure turbine (HPT) blade tip seal location for following reasons: Current active clearance control (ACC) systems (e.g., thermal case-cooling schemes) cannot respond to blade tip clearance changes due to mechanical, thermal, and aerodynamic loads. As such they are prone to wear due to the required tight running clearances during operation. Blade tip seal wear (increased clearances) reduces engine efficiency, performance, and service life. Adaptive sealing technology research has inherent impact on all envisioned 21st century propulsion systems (e.g. distributed vectored, hybrid and electric drive propulsion concepts).

  15. Robust Second Order Sliding mode Observer for the Estimation of the Vehicle States

    NASA Astrophysics Data System (ADS)

    Chaibet, A.; Nouveliere, L.; Hima, S.; Mammar, S.

    2008-06-01

    This paper is dedicated to the observation of non measurable variables for automotive systems. A non linear observer, based on a sliding mode approach, is presented for the estimation of the dynamic states of the vehicle. The considered technique is applied to the estimation problem for an automated vehicle following. Both the simulation and the experimental results are addressed to demonstrate the effectiveness of the sliding mode observer for different maneuvers, in terms of performances and robustness.

  16. Adaptive sensor fusion using genetic algorithms

    SciTech Connect

    Fitzgerald, D.S.; Adams, D.G.

    1994-08-01

    Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ``fuzzy`` sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion.

  17. Adaptive management

    USGS Publications Warehouse

    Allen, Craig R.; Garmestani, Ahjond S.

    2015-01-01

    Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive management has explicit structure, including a careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. The process is iterative, and serves to reduce uncertainty, build knowledge and improve management over time in a goal-oriented and structured process.

  18. Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

    This paper addresses the cooperative path-following problem of multiple marine surface vehicles subject to dynamical uncertainties and ocean disturbances induced by unknown wind, wave and ocean current. The control design falls neatly into two parts. One is to steer individual marine surface vehicle to track a predefined path and the other is to synchronise the along-path speed and path variables under the constraints of an underlying communication network. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicles based on backstepping and neural network techniques. Then, a decentralised synchronisation control law is derived by means of consensus on along-path speed and path variables based on graph theory. The distinct feature of this design lies in that synchronised path following can be reached for any undirected connected communication graphs without accurate knowledge of the model. This result is further extended to the output feedback case, where an observer-based cooperative path-following controller is developed without measuring the velocity of each vehicle. For both designs, rigorous theoretical analysis demonstrate that all signals in the closed-loop system are semi-global uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.

  19. Nonlinear robust control of integrated vehicle dynamics

    NASA Astrophysics Data System (ADS)

    He, Zhengyi; Ji, Xuewu

    2012-02-01

    A new methodology to design the vehicle GCC (global chassis control) nonlinear controller is developed in this paper. Firstly, to handle the nonlinear coupling between sprung and unsprung masses, the vehicle is treated as a mechanical system of two-rigid-bodies which has 6 DOF (degree of freedom), including longitudinal, lateral, yaw, vertical, roll and pitch dynamics. The system equation is built in the yaw frame based on Lagrange's method, and it has been proved that the derived system remains the important physical properties of the general mechanical system. Then the GCC design problem is formulated as the trajectory tracking problem for a cascade system, with a Lagrange's system interconnecting with a linear system. The nonlinear robust control design problem of this cascade interconnected system is divided into two H ∞ control problems with respect to the two sub-systems. The parameter uncertainties in the system are tackled by adaptive theory, while the external uncertainties and disturbances are dealt with the H ∞ control theory. And the passivity of the mechanical system is applied to construct the solution of nonlinear H ∞ control problem. Finally, the effectiveness of the proposed controller is validated by simulation results even during the emergency manoeuvre.

  20. Recent Progress toward Robust Photocathodes

    SciTech Connect

    Mulhollan, G. A.; Bierman, J. C.

    2009-08-04

    RF photoinjectors for next generation spin-polarized electron accelerators require photo-cathodes capable of surviving RF gun operation. Free electron laser photoinjectors can benefit from more robust visible light excited photoemitters. A negative electron affinity gallium arsenide activation recipe has been found that diminishes its background gas susceptibility without any loss of near bandgap photoyield. The highest degree of immunity to carbon dioxide exposure was achieved with a combination of cesium and lithium. Activated amorphous silicon photocathodes evince advantageous properties for high current photoinjectors including low cost, substrate flexibility, visible light excitation and greatly reduced gas reactivity compared to gallium arsenide.

  1. Development of a Novel Disturbance Observer Based Fractional Order PD Controller for a Gun Control System

    PubMed Central

    Zheng, Liang; Chen, Jilin; Wang, Li; Hou, Yuanlong

    2014-01-01

    Motion control of gun barrels is an ongoing topic for the development of gun control equipment (GCE) with excellent performances. In this paper, a novel disturbance observer (DOB) based fractional order PD (FOPD) control strategy is proposed for the GCE. By adopting the DOB, the control system behaves as if it were the nominal closed-loop system in the absence of disturbances and uncertainties. The optimal control parameters of the FOPD are determined from the loop-shaping perspective, and the Q-filter of the DOB is deliberately designed with consideration of system robustness. The linear frame of the proposed control system will enable the analysis process more convenient. The disturbance rejection properties and the tracking performances of the control system are investigated by both numerical and experimental tests, the results demonstrate that the proposed DOB based FOPD control system is of more robustness, and it is much more suitable for the gun control system with strong nonlinearity and disturbance. PMID:24616616

  2. On Nonlinear Disturbance Observer Based Tracking Control for Euler-Lagrange Systems

    NASA Astrophysics Data System (ADS)

    Smadi, Issam Abed; Fujimoto, Yasutaka

    The purpose of this paper is to present a general framework for the design of a nonlinear disturbance observer for Euler-Lagrange systems, in particular, for mechanical, electro-mechanical, and power electronic systems. The generalized momentum plays a crucial role in realizing the proposed method, and the global stability is guaranteed under certain conditions. In the absence of parameter variations and/or model uncertainties, the proposed method guarantees global exponential stability. Otherwise, model uncertainties and parameter variations are merged with the input disturbance into a “lumped disturbance term”. Then under boundness assumption on the lumped disturbance term, the observer can asymptotically estimate to any desired accuracy the lumped disturbance. In the sequel of this paper, motivated by the proposed nonlinear disturbance observer, a robust tracking control for robot manipulators is proposed. Again, in the absence of parameter variations and/or model uncertainties, the global stability is guaranteed. Otherwise, using tools from singular perturbation theory, the proposed method ensures arbitrary disturbance attenuation, small tracking error, and boundness of all closed loop signals. The theoretical results are illustrated on friction compensation and robust tracking of two degrees of freedom planer robot manipulator with short comparison with a classical, linear disturbance observer.

  3. Adapting to complexity

    SciTech Connect

    Ruthen, R.

    1993-01-01

    Researchers at Santa Fe and elsewhere are just beginning to think about ways in which this framework and other new insights into complex adaptive systems can be proved. But Kauffman is confident that more robust models and further experiments will support a view of evolution that bridges living and nonliving systems. [open quotes]Every attempt to find something that is being maximized in evolution has always met with failure,[close quotes] Kauffman observes. [open quotes]Yet I have this feeling that there is something very general going on about how far from equilibrium systems have organized themselves. I don't know what that something is yet. But I can taste it.[close quotes

  4. Robust growing neural gas algorithm with application in cluster analysis.

    PubMed

    Qin, A K; Suganthan, P N

    2004-01-01

    We propose a novel robust clustering algorithm within the Growing Neural Gas (GNG) framework, called Robust Growing Neural Gas (RGNG) network.The Matlab codes are available from . By incorporating several robust strategies, such as outlier resistant scheme, adaptive modulation of learning rates and cluster repulsion method into the traditional GNG framework, the proposed RGNG network possesses better robustness properties. The RGNG is insensitive to initialization, input sequence ordering and the presence of outliers. Furthermore, the RGNG network can automatically determine the optimal number of clusters by seeking the extreme value of the Minimum Description Length (MDL) measure during network growing process. The resulting center positions of the optimal number of clusters represented by prototype vectors are close to the actual ones irrespective of the existence of outliers. Topology relationships among these prototypes can also be established. Experimental results have shown the superior performance of our proposed method over the original GNG incorporating MDL method, called GNG-M, in static data clustering tasks on both artificial and UCI data sets. PMID:15555857

  5. Adaptive Thresholds

    SciTech Connect

    Bremer, P. -T.

    2014-08-26

    ADAPT is a topological analysis code that allow to compute local threshold, in particular relevance based thresholds for features defined in scalar fields. The initial target application is vortex detection but the software is more generally applicable to all threshold based feature definitions.

  6. A Robust Design Methodology for Optimal Microscale Secondary Flow Control in Compact Inlet Diffusers

    NASA Technical Reports Server (NTRS)

    Anderson, Bernhard H.; Keller, Dennis J.

    2001-01-01

    It is the purpose of this study to develop an economical Robust design methodology for microscale secondary flow control in compact inlet diffusers. To illustrate the potential of economical Robust Design methodology, two different mission strategies were considered for the subject inlet, namely Maximum Performance and Maximum HCF Life Expectancy. The Maximum Performance mission maximized total pressure recovery while the Maximum HCF Life Expectancy mission minimized the mean of the first five Fourier harmonic amplitudes, i.e., 'collectively' reduced all the harmonic 1/2 amplitudes of engine face distortion. Each of the mission strategies was subject to a low engine face distortion constraint, i.e., DC60<0.10, which is a level acceptable for commercial engines. For each of these missions strategies, an 'Optimal Robust' (open loop control) and an 'Optimal Adaptive' (closed loop control) installation was designed over a twenty degree angle-of-incidence range. The Optimal Robust installation used economical Robust Design methodology to arrive at a single design which operated over the entire angle-of-incident range (open loop control). The Optimal Adaptive installation optimized all the design parameters at each angle-of-incidence. Thus, the Optimal Adaptive installation would require a closed loop control system to sense a proper signal for each effector and modify that effector device, whether mechanical or fluidic, for optimal inlet performance. In general, the performance differences between the Optimal Adaptive and Optimal Robust installation designs were found to be marginal. This suggests, however, that Optimal Robust open loop installation designs can be very competitive with Optimal Adaptive close loop designs. Secondary flow control in inlets is inherently robust, provided it is optimally designed. Therefore, the new methodology presented in this paper, combined array 'Lower Order' approach to Robust DOE, offers the aerodynamicist a very viable and

  7. Adapting agriculture to climate change.

    PubMed

    Howden, S Mark; Soussana, Jean-François; Tubiello, Francesco N; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

    2007-12-11

    The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.

  8. Adapting agriculture to climate change

    PubMed Central

    Howden, S. Mark; Soussana, Jean-François; Tubiello, Francesco N.; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

    2007-01-01

    The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists. PMID:18077402

  9. Robust edge-directed interpolation of magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Mai, Zhenhua; Rajan, Jeny; Verhoye, Marleen; Sijbers, Jan

    2011-11-01

    Image interpolation is intrinsically a severely under-determined inverse problem. Traditional non-adaptive interpolation methods do not account for local image statistics around the edges of image structures. In practice, this results in artifacts such as jagged edges, blurring and/or edge halos. To overcome this shortcoming, edge-directed interpolation has been introduced in different forms. One variant, new edge-directed interpolation (NEDI), has successfully exploited the 'geometric duality' that links the low-resolution image to its corresponding high-resolution image. It has been demonstrated that for scalar images, NEDI is able to produce better results than non-adaptive traditional methods, both visually and quantitatively. In this work, we return to the root of NEDI as a least-squares estimation method of neighborhood patterns and propose a robust scheme to improve it. The improvement is twofold: firstly, a robust least-squares technique is used to improve NEDI's performance to outliers and noise; secondly, the NEDI algorithm is extended with the recently proposed non-local mean estimation scheme. Moreover, the edge-directed concept is applied to the interpolation of multi-valued diffusion-weighted images. The framework is tested on phantom scalar images and real diffusion images, and is shown to achieve better results than the non-adaptive methods as well as NEDI, in terms of visual quality as well as quantitative measures.

  10. Degeneracy: a link between evolvability, robustness and complexity in biological systems.

    PubMed

    Whitacre, James M

    2010-01-01

    A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology.This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability. PMID:20167097

  11. Robust Inflation from fibrous strings

    NASA Astrophysics Data System (ADS)

    Burgess, C. P.; Cicoli, M.; de Alwis, S.; Quevedo, F.

    2016-05-01

    Successful inflationary models should (i) describe the data well; (ii) arise generically from sensible UV completions; (iii) be insensitive to detailed fine-tunings of parameters and (iv) make interesting new predictions. We argue that a class of models with these properties is characterized by relatively simple potentials with a constant term and negative exponentials. We here continue earlier work exploring UV completions for these models—including the key (though often ignored) issue of modulus stabilisation—to assess the robustness of their predictions. We show that string models where the inflaton is a fibration modulus seem to be robust due to an effective rescaling symmetry, and fairly generic since most known Calabi-Yau manifolds are fibrations. This class of models is characterized by a generic relation between the tensor-to-scalar ratio r and the spectral index ns of the form r propto (ns‑1)2 where the proportionality constant depends on the nature of the effects used to develop the inflationary potential and the topology of the internal space. In particular we find that the largest values of the tensor-to-scalar ratio that can be obtained by generalizing the original set-up are of order r lesssim 0.01. We contrast this general picture with specific popular models, such as the Starobinsky scenario and α-attractors. Finally, we argue the self consistency of large-field inflationary models can strongly constrain non-supersymmetric inflationary mechanisms.

  12. The Robustness of Acoustic Analogies

    NASA Technical Reports Server (NTRS)

    Freund, J. B.; Lele, S. K.; Wei, M.

    2004-01-01

    Acoustic analogies for the prediction of flow noise are exact rearrangements of the flow equations N(right arrow q) = 0 into a nominal sound source S(right arrow q) and sound propagation operator L such that L(right arrow q) = S(right arrow q). In practice, the sound source is typically modeled and the propagation operator inverted to make predictions. Since the rearrangement is exact, any sufficiently accurate model of the source will yield the correct sound, so other factors must determine the merits of any particular formulation. Using data from a two-dimensional mixing layer direct numerical simulation (DNS), we evaluate the robustness of two analogy formulations to different errors intentionally introduced into the source. The motivation is that since S can not be perfectly modeled, analogies that are less sensitive to errors in S are preferable. Our assessment is made within the framework of Goldstein's generalized acoustic analogy, in which different choices of a base flow used in constructing L give different sources S and thus different analogies. A uniform base flow yields a Lighthill-like analogy, which we evaluate against a formulation in which the base flow is the actual mean flow of the DNS. The more complex mean flow formulation is found to be significantly more robust to errors in the energetic turbulent fluctuations, but its advantage is less pronounced when errors are made in the smaller scales.

  13. Design of H(infinity) robust fault detection filter for linear uncertain time-delay systems.

    PubMed

    Bai, Leishi; Tian, Zuohua; Shi, Songjiao

    2006-10-01

    In this paper, the robust fault detection filter design problem for linear time-delay systems with both unknown inputs and parameter uncertainties is studied. Using a multiobjective optimization technique, a new performance index is introduced, which takes into account the robustness of the fault detection filter against disturbances and sensitivity to faults simultaneously. The reference residual model is then designed based on this performance index to formulate the robust fault detection filter design problem as an H(infinity) model-matching problem. By applying robust H(infinity) optimization control technique, the existence condition of the robust fault detection filter for linear time-delay systems with both unknown inputs and parameter uncertainties is presented in terms of linear matrix inequality formulation, independently of time delay. In order to detect the fault, an adaptive threshold which depends on the inputs is finally determined. An illustrative design example is used to demonstrate the validity of the proposed approach.

  14. A robust high-order ideal magnetohydrodynamic solver

    NASA Astrophysics Data System (ADS)

    Seal, David; Christlieb, Andrew; Feng, Xiao; Tang, Qi

    In this work we present a robust high-order numerical method for the ideal magnetohydrodynamics (MHD) equations. Our method is single-stage and single-step, and hence amenable to adaptive mesh refinement (AMR) technology. The numerical robustness of the scheme is realized by accomplishing a total of two unrelated tasks: we retain positivity of the density and pressure by limiting fluxes similar to what happens in a flux corrected transport method, and we obtain divergence free magnetic fields by implementing an unstaggered transport method for the evolution of the magnetic potential. We present numerical results in two and three dimensions that indicate the utility of the scheme. These results include several classical test problems such as Orzag-Tang, cloud shock interactions and blast wave problems.

  15. Fusion of inertial and visual: a geometrical observer-based approach

    SciTech Connect

    Bonnabel, S.; Rouchon, P.

    2009-03-05

    The problem of combination between inertial sensors and CCD cameras is of paramount importance in various applications in robotics and autonomous navigation. In this paper we develop a totally geometric model for analysis of this problem, independently from a camera model and from the structure of the scene (landmarks etc.). This formulation can be used for data fusion in several inertial navigation problems. The estimation is then decoupled from the structure of the scene. We use it in the particular case of the estimation of the gyroscopes bias and we build a nonlinear observer which is easy to compute, provides an estimation of the biais, filters the image, and is by construction very robust to noise.

  16. Multivariable disturbance observer-based H2 analytical decoupling control design for multivariable systems

    NASA Astrophysics Data System (ADS)

    Zhang, Wei; Wang, Yagang; Liu, Yurong; Zhang, Weidong

    2016-01-01

    In this paper, an H2 analytical decoupling control scheme with multivariable disturbance observer for both stable and unstable multi-input/multi-output (MIMO) systems with multiple time delays is proposed. Compared with conventional control strategies, the main merit is that the proposed control scheme can improve the system performances effectively when the MIMO processes with severe model mismatches and strong external disturbances. Besides, the design method has three additional advantages. First, the derived controller and observer are given in analytical forms, the design procedure is simple. Second, the orders of the designed controller and observer are low, they can be implemented easily in practice. Finally, the performance and robustness can be adjusted easily by tuning the parameters in the designed controller and observer. It is useful for practical application. Simulations are provided to illustrate the effectiveness of the proposed control scheme.

  17. Robust active binocular vision through intrinsically motivated learning.

    PubMed

    Lonini, Luca; Forestier, Sébastien; Teulière, Céline; Zhao, Yu; Shi, Bertram E; Triesch, Jochen

    2013-01-01

    The efficient coding hypothesis posits that sensory systems of animals strive to encode sensory signals efficiently by taking into account the redundancies in them. This principle has been very successful in explaining response properties of visual sensory neurons as adaptations to the statistics of natural images. Recently, we have begun to extend the efficient coding hypothesis to active perception through a form of intrinsically motivated learning: a sensory model learns an efficient code for the sensory signals while a reinforcement learner generates movements of the sense organs to improve the encoding of the signals. To this end, it receives an intrinsically generated reinforcement signal indicating how well the sensory model encodes the data. This approach has been tested in the context of binocular vison, leading to the autonomous development of disparity tuning and vergence control. Here we systematically investigate the robustness of the new approach in the context of a binocular vision system implemented on a robot. Robustness is an important aspect that reflects the ability of the system to deal with unmodeled disturbances or events, such as insults to the system that displace the stereo cameras. To demonstrate the robustness of our method and its ability to self-calibrate, we introduce various perturbations and test if and how the system recovers from them. We find that (1) the system can fully recover from a perturbation that can be compensated through the system's motor degrees of freedom, (2) performance degrades gracefully if the system cannot use its motor degrees of freedom to compensate for the perturbation, and (3) recovery from a perturbation is improved if both the sensory encoding and the behavior policy can adapt to the perturbation. Overall, this work demonstrates that our intrinsically motivated learning approach for efficient coding in active perception gives rise to a self-calibrating perceptual system of high robustness. PMID:24223552

  18. Robust active binocular vision through intrinsically motivated learning.

    PubMed

    Lonini, Luca; Forestier, Sébastien; Teulière, Céline; Zhao, Yu; Shi, Bertram E; Triesch, Jochen

    2013-01-01

    The efficient coding hypothesis posits that sensory systems of animals strive to encode sensory signals efficiently by taking into account the redundancies in them. This principle has been very successful in explaining response properties of visual sensory neurons as adaptations to the statistics of natural images. Recently, we have begun to extend the efficient coding hypothesis to active perception through a form of intrinsically motivated learning: a sensory model learns an efficient code for the sensory signals while a reinforcement learner generates movements of the sense organs to improve the encoding of the signals. To this end, it receives an intrinsically generated reinforcement signal indicating how well the sensory model encodes the data. This approach has been tested in the context of binocular vison, leading to the autonomous development of disparity tuning and vergence control. Here we systematically investigate the robustness of the new approach in the context of a binocular vision system implemented on a robot. Robustness is an important aspect that reflects the ability of the system to deal with unmodeled disturbances or events, such as insults to the system that displace the stereo cameras. To demonstrate the robustness of our method and its ability to self-calibrate, we introduce various perturbations and test if and how the system recovers from them. We find that (1) the system can fully recover from a perturbation that can be compensated through the system's motor degrees of freedom, (2) performance degrades gracefully if the system cannot use its motor degrees of freedom to compensate for the perturbation, and (3) recovery from a perturbation is improved if both the sensory encoding and the behavior policy can adapt to the perturbation. Overall, this work demonstrates that our intrinsically motivated learning approach for efficient coding in active perception gives rise to a self-calibrating perceptual system of high robustness.

  19. Robust Concentration and Frequency Control in Oscillatory Homeostats

    PubMed Central

    Thorsen, Kristian; Agafonov, Oleg; Selstø, Christina H.; Jolma, Ingunn W.; Ni, Xiao Y.; Drengstig, Tormod; Ruoff, Peter

    2014-01-01

    Homeostatic and adaptive control mechanisms are essential for keeping organisms structurally and functionally stable. Integral feedback is a control theoretic concept which has long been known to keep a controlled variable robustly (i.e. perturbation-independent) at a given set-point by feeding the integrated error back into the process that generates . The classical concept of homeostasis as robust regulation within narrow limits is often considered as unsatisfactory and even incompatible with many biological systems which show sustained oscillations, such as circadian rhythms and oscillatory calcium signaling. Nevertheless, there are many similarities between the biological processes which participate in oscillatory mechanisms and classical homeostatic (non-oscillatory) mechanisms. We have investigated whether biological oscillators can show robust homeostatic and adaptive behaviors, and this paper is an attempt to extend the homeostatic concept to include oscillatory conditions. Based on our previously published kinetic conditions on how to generate biochemical models with robust homeostasis we found two properties, which appear to be of general interest concerning oscillatory and homeostatic controlled biological systems. The first one is the ability of these oscillators (“oscillatory homeostats”) to keep the average level of a controlled variable at a defined set-point by involving compensatory changes in frequency and/or amplitude. The second property is the ability to keep the period/frequency of the oscillator tuned within a certain well-defined range. In this paper we highlight mechanisms that lead to these two properties. The biological applications of these findings are discussed using three examples, the homeostatic aspects during oscillatory calcium and p53 signaling, and the involvement of circadian rhythms in homeostatic regulation. PMID:25238410

  20. Simple adaptive tracking control for mobile robots

    NASA Astrophysics Data System (ADS)

    Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton

    2014-12-01

    The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.

  1. Transport and radiative impacts of atmospheric pollen using online, observation-based emissions

    NASA Astrophysics Data System (ADS)

    Wozniak, M. C.; Steiner, A. L.; Solmon, F.; Li, Y.

    2015-12-01

    Atmospheric pollen emitted from trees and grasses exhibits both a high temporal variability and a highly localized spatial distribution that has been difficult to quantify in the atmosphere. Pollen's radiative impact is also not quantified because it is neglected in climate modeling studies. Here we couple an online, meteorological active pollen emissions model guided by observations of airborne pollen to understand the role of pollen in the atmosphere. We use existing pollen counts from 2003-2008 across the continental U.S. in conjunction with a tree database and historical meteorological data to create an observation-based phenological model that produces accurately scaled and timed emissions. These emissions are emitted and transported within the regional climate model (RegCM4) and the direct radiative effect is calculated. Additionally, we simulate the rupture of coarse pollen grains into finer particles by adding a second size mode for pollen emissions, which contributes to the shortwave radiative forcing and also has an indirect effect on climate.

  2. Evaluation of Global Observations-Based Evapotranspiration Datasets and IPCC AR4 Simulations

    NASA Technical Reports Server (NTRS)

    Mueller, B.; Seneviratne, S. I.; Jimenez, C.; Corti, T.; Hirschi, M.; Balsamo, G.; Ciais, P.; Dirmeyer, P.; Fisher, J. B.; Guo, Z.; Jung, M.; Maignan, F.; McCabe, M. F.; Reichle, R.; Reichstein, M.; Rodell, M.; Sheffield, J.; Teuling, A. J.; Wang, K.; Wood, E. F.; Zhang, Y.

    2011-01-01

    Quantification of global land evapotranspiration (ET) has long been associated with large uncertainties due to the lack of reference observations. Several recently developed products now provide the capacity to estimate ET at global scales. These products, partly based on observational data, include satellite ]based products, land surface model (LSM) simulations, atmospheric reanalysis output, estimates based on empirical upscaling of eddycovariance flux measurements, and atmospheric water balance datasets. The LandFlux-EVAL project aims to evaluate and compare these newly developed datasets. Additionally, an evaluation of IPCC AR4 global climate model (GCM) simulations is presented, providing an assessment of their capacity to reproduce flux behavior relative to the observations ]based products. Though differently constrained with observations, the analyzed reference datasets display similar large-scale ET patterns. ET from the IPCC AR4 simulations was significantly smaller than that from the other products for India (up to 1 mm/d) and parts of eastern South America, and larger in the western USA, Australia and China. The inter-product variance is lower across the IPCC AR4 simulations than across the reference datasets in several regions, which indicates that uncertainties may be underestimated in the IPCC AR4 models due to shared biases of these simulations.

  3. Observation-based gridded runoff estimates for Europe (E-RUN version 1.1)

    NASA Astrophysics Data System (ADS)

    Gudmundsson, Lukas; Seneviratne, Sonia I.

    2016-07-01

    River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct databases. Observed monthly runoff rates are subsequently tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2015) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring. The newly derived data are made publicly available at doi:10.1594/PANGAEA.861371.

  4. State observer-based sliding mode control for semi-active hydro-pneumatic suspension

    NASA Astrophysics Data System (ADS)

    Ren, Hongbin; Chen, Sizhong; Zhao, Yuzhuang; Liu, Gang; Yang, Lin

    2016-02-01

    This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.

  5. Connector adapter

    NASA Technical Reports Server (NTRS)

    Hacker, Scott C. (Inventor); Dean, Richard J. (Inventor); Burge, Scott W. (Inventor); Dartez, Toby W. (Inventor)

    2007-01-01

    An adapter for installing a connector to a terminal post, wherein the connector is attached to a cable, is presented. In an embodiment, the adapter is comprised of an elongated collet member having a longitudinal axis comprised of a first collet member end, a second collet member end, an outer collet member surface, and an inner collet member surface. The inner collet member surface at the first collet member end is used to engage the connector. The outer collet member surface at the first collet member end is tapered for a predetermined first length at a predetermined taper angle. The collet includes a longitudinal slot that extends along the longitudinal axis initiating at the first collet member end for a predetermined second length. The first collet member end is formed of a predetermined number of sections segregated by a predetermined number of channels and the longitudinal slot.

  6. Adaptive VFH

    NASA Astrophysics Data System (ADS)

    Odriozola, Iñigo; Lazkano, Elena; Sierra, Basi

    2011-10-01

    This paper investigates the improvement of the Vector Field Histogram (VFH) local planning algorithm for mobile robot systems. The Adaptive Vector Field Histogram (AVFH) algorithm has been developed to improve the effectiveness of the traditional VFH path planning algorithm overcoming the side effects of using static parameters. This new algorithm permits the adaptation of planning parameters for the different type of areas in an environment. Genetic Algorithms are used to fit the best VFH parameters to each type of sector and, afterwards, every section in the map is labelled with the sector-type which best represents it. The Player/Stage simulation platform has been chosen for making all sort of tests and to prove the new algorithm's adequateness. Even though there is still much work to be carried out, the developed algorithm showed good navigation properties and turned out to be softer and more effective than the traditional VFH algorithm.

  7. Adaptive sampler

    DOEpatents

    Watson, B.L.; Aeby, I.

    1980-08-26

    An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  8. Adaptive sampler

    DOEpatents

    Watson, Bobby L.; Aeby, Ian

    1982-01-01

    An adaptive data compression device for compressing data having variable frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  9. Robust control with structured perturbations

    NASA Technical Reports Server (NTRS)

    Keel, Leehyun

    1991-01-01

    This semi-annual report describes continued progress on the research. Among several approaches in this area of research, our approach to the parametric uncertainties are being matured everyday. This approach deals with real parameter uncertainties which other techniques such as H (sup infinity) optimal control, micron analysis and synthesis, and l(sub 1) optimal control cannot deal. The primary assumption of this approach is that the mathematical models are well obtained so that the most of system uncertainties can be translated into parameter uncertainties of their linear system representations. These uncertainties may be due to modeling, nonlinearity of the physical system, some time-varying parameters, etc. In this report period of research, we are concentrating on implementing a computer aided analysis and design tool based on new results on parametric robust stability. This implementation will help us to reveal further details in this approach.

  10. The structure of robust observers

    NASA Technical Reports Server (NTRS)

    Bhattacharyya, S. P.

    1975-01-01

    Conventional observers for linear time-invariant systems are shown to be structurally inadequate from a sensitivity standpoint. It is proved that if a linear dynamic system is to provide observer action despite arbitrary small perturbations in a specified subset of its parameters, it must: (1) be a closed loop system, be driven by the observer error, (2) possess redundancy, the observer must be generating, implicitly or explicitly, at least one linear combination of states that is already contained in the measurements, and (3) contain a perturbation-free model of the portion of the system observable from the external input to the observer. The procedure for design of robust observers possessing the above structural features is established and discussed.

  11. Robust characterization of leakage errors

    NASA Astrophysics Data System (ADS)

    Wallman, Joel J.; Barnhill, Marie; Emerson, Joseph

    2016-04-01

    Leakage errors arise when the quantum state leaks out of some subspace of interest, for example, the two-level subspace of a multi-level system defining a computational ‘qubit’, the logical code space of a quantum error-correcting code, or a decoherence-free subspace. Leakage errors pose a distinct challenge to quantum control relative to the more well-studied decoherence errors and can be a limiting factor to achieving fault-tolerant quantum computation. Here we present a scalable and robust randomized benchmarking protocol for quickly estimating the leakage rate due to an arbitrary Markovian noise process on a larger system. We illustrate the reliability of the protocol through numerical simulations.

  12. CONTAINER MATERIALS, FABRICATION AND ROBUSTNESS

    SciTech Connect

    Dunn, K.; Louthan, M.; Rawls, G.; Sindelar, R.; Zapp, P.; Mcclard, J.

    2009-11-10

    The multi-barrier 3013 container used to package plutonium-bearing materials is robust and thereby highly resistant to identified degradation modes that might cause failure. The only viable degradation mechanisms identified by a panel of technical experts were pressurization within and corrosion of the containers. Evaluations of the container materials and the fabrication processes and resulting residual stresses suggest that the multi-layered containers will mitigate the potential for degradation of the outer container and prevent the release of the container contents to the environment. Additionally, the ongoing surveillance programs and laboratory studies should detect any incipient degradation of containers in the 3013 storage inventory before an outer container is compromised.

  13. How robust are distributed systems

    NASA Technical Reports Server (NTRS)

    Birman, Kenneth P.

    1989-01-01

    A distributed system is made up of large numbers of components operating asynchronously from one another and hence with imcomplete and inaccurate views of one another's state. Load fluctuations are common as new tasks arrive and active tasks terminate. Jointly, these aspects make it nearly impossible to arrive at detailed predictions for a system's behavior. It is important to the successful use of distributed systems in situations in which humans cannot provide the sorts of predictable realtime responsiveness of a computer, that the system be robust. The technology of today can too easily be affected by worn programs or by seemingly trivial mechanisms that, for example, can trigger stock market disasters. Inventors of a technology have an obligation to overcome flaws that can exact a human cost. A set of principles for guiding solutions to distributed computing problems is presented.

  14. Robust matching for voice recognition

    NASA Astrophysics Data System (ADS)

    Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.

    1994-10-01

    This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.

  15. Robust holographic storage system design.

    PubMed

    Watanabe, Takahiro; Watanabe, Minoru

    2011-11-21

    Demand is increasing daily for large data storage systems that are useful for applications in spacecraft, space satellites, and space robots, which are all exposed to radiation-rich space environment. As candidates for use in space embedded systems, holographic storage systems are promising because they can easily provided the demanded large-storage capability. Particularly, holographic storage systems, which have no rotation mechanism, are demanded because they are virtually maintenance-free. Although a holographic memory itself is an extremely robust device even in a space radiation environment, its associated lasers and drive circuit devices are vulnerable. Such vulnerabilities sometimes engendered severe problems that prevent reading of all contents of the holographic memory, which is a turn-off failure mode of a laser array. This paper therefore presents a proposal for a recovery method for the turn-off failure mode of a laser array on a holographic storage system, and describes results of an experimental demonstration.

  16. Sampled data observer based inter-sample output predictor for Electro-Hydraulic Actuators.

    PubMed

    Sofiane, Ahmed Ali

    2015-09-01

    In this paper, a Sampled Data Disturbance Observer which simultaneously estimates the unmeasurable states and the uncertainties for the Electro-Hydraulic Actuators systems are presented. The novelty of our approach is the use of an inter-sample output predictor which allows the user to increase the frequency acquisition of the piston position sensor without affecting the convergence performance. The stability analysis of the proposed observer is proved using the Lyapunov function adapted to hybrid systems. To show the efficiency of the proposed observer, numerical simulations of a control application which combine the proposed observer and a Proportional Integral controller for the purpose of piston position tracking problem are presented.

  17. Adaptive antennas

    NASA Astrophysics Data System (ADS)

    Barton, P.

    1987-04-01

    The basic principles of adaptive antennas are outlined in terms of the Wiener-Hopf expression for maximizing signal to noise ratio in an arbitrary noise environment; the analogy with generalized matched filter theory provides a useful aid to understanding. For many applications, there is insufficient information to achieve the above solution and thus non-optimum constrained null steering algorithms are also described, together with a summary of methods for preventing wanted signals being nulled by the adaptive system. The three generic approaches to adaptive weight control are discussed; correlation steepest descent, weight perturbation and direct solutions based on sample matrix conversion. The tradeoffs between hardware complexity and performance in terms of null depth and convergence rate are outlined. The sidelobe cancellor technique is described. Performance variation with jammer power and angular distribution is summarized and the key performance limitations identified. The configuration and performance characteristics of both multiple beam and phase scan array antennas are covered, with a brief discussion of performance factors.

  18. Robust pedestrian detection and tracking in crowded scenes

    NASA Astrophysics Data System (ADS)

    Lypetskyy, Yuriy

    2007-09-01

    This paper presents a vision based tracking system developed for very crowded situations like underground or railway stations. Our system consists on two main parts - searching of people candidates in single frames, and tracking them frame to frame over the scene. This paper concentrates mostly on the tracking part and describes its core components in detail. These are trajectories predictions using KLT vectors or Kalman filter, adaptive active shape model adjusting and texture matching. We show that combination of presented algorithms leads to robust people tracking even in complex scenes with permanent occlusions.

  19. Adaptive nonlinear flight control

    NASA Astrophysics Data System (ADS)

    Rysdyk, Rolf Theoduor

    1998-08-01

    Research under supervision of Dr. Calise and Dr. Prasad at the Georgia Institute of Technology, School of Aerospace Engineering. has demonstrated the applicability of an adaptive controller architecture. The architecture successfully combines model inversion control with adaptive neural network (NN) compensation to cancel the inversion error. The tiltrotor aircraft provides a specifically interesting control design challenge. The tiltrotor aircraft is capable of converting from stable responsive fixed wing flight to unstable sluggish hover in helicopter configuration. It is desirable to provide the pilot with consistency in handling qualities through a conversion from fixed wing flight to hover. The linear model inversion architecture was adapted by providing frequency separation in the command filter and the error-dynamics, while not exiting the actuator modes. This design of the architecture provides for a model following setup with guaranteed performance. This in turn allowed for convenient implementation of guaranteed handling qualities. A rigorous proof of boundedness is presented making use of compact sets and the LaSalle-Yoshizawa theorem. The analysis allows for the addition of the e-modification which guarantees boundedness of the NN weights in the absence of persistent excitation. The controller is demonstrated on the Generic Tiltrotor Simulator of Bell-Textron and NASA Ames R.C. The model inversion implementation is robustified with respect to unmodeled input dynamics, by adding dynamic nonlinear damping. A proof of boundedness of signals in the system is included. The effectiveness of the robustification is also demonstrated on the XV-15 tiltrotor. The SHL Perceptron NN provides a more powerful application, based on the universal approximation property of this type of NN. The SHL NN based architecture is also robustified with the dynamic nonlinear damping. A proof of boundedness extends the SHL NN augmentation with robustness to unmodeled actuator

  20. An improved robust ADMM algorithm for quantum state tomography

    NASA Astrophysics Data System (ADS)

    Li, Kezhi; Zhang, Hui; Kuang, Sen; Meng, Fangfang; Cong, Shuang

    2016-06-01

    In this paper, an improved adaptive weights alternating direction method of multipliers algorithm is developed to implement the optimization scheme for recovering the quantum state in nearly pure states. The proposed approach is superior to many existing methods because it exploits the low-rank property of density matrices, and it can deal with unexpected sparse outliers as well. The numerical experiments are provided to verify our statements by comparing the results to three different optimization algorithms, using both adaptive and fixed weights in the algorithm, in the cases of with and without external noise, respectively. The results indicate that the improved algorithm has better performances in both estimation accuracy and robustness to external noise. The further simulation results show that the successful recovery rate increases when more qubits are estimated, which in fact satisfies the compressive sensing theory and makes the proposed approach more promising.

  1. Addressing uncertainty in adaptation planning for agriculture.

    PubMed

    Vermeulen, Sonja J; Challinor, Andrew J; Thornton, Philip K; Campbell, Bruce M; Eriyagama, Nishadi; Vervoort, Joost M; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J; Hawkins, Ed; Smith, Daniel R

    2013-05-21

    We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

  2. Addressing uncertainty in adaptation planning for agriculture

    PubMed Central

    Vermeulen, Sonja J.; Challinor, Andrew J.; Thornton, Philip K.; Campbell, Bruce M.; Eriyagama, Nishadi; Vervoort, Joost M.; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J.; Hawkins, Ed; Smith, Daniel R.

    2013-01-01

    We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty. PMID:23674681

  3. Predictable signals in seasonal mean soil moisture simulated with observation-based atmospheric forcing over China

    NASA Astrophysics Data System (ADS)

    Ying, Kairan; Zhao, Tianbao; Zheng, Xiaogu; Quan, Xiao-Wei; Frederiksen, Carsten S.; Li, Mingxing

    2016-10-01

    The Community Land Model version 3.5 is driven by an observation-based meteorological dataset to simulate soil moisture over China for the period 1951-2008. A method for identifying the patterns of interannual variability that arise from slow (potentially predictable) and intraseasonal (unpredictable) variability is also applied; this allows identification of the sources of the predictability of seasonal soil moisture in China, during March-April-May (MAM), June-July-August (JJA), September-October-November (SON) and December-January-February (DJF). The potential predictability (slow-to-total) of the soil moisture above 1 m is high, with lowest value of 0.76 in JJA and highest value of 0.94 in DJF. The spatial distribution of the potential predictability comprises a northwest-southeast gradient, with a minimum center over East China and a maximum center over the northwest. The most important source of predictability is from the soil moisture persistence, which generally accounts for more than 50 % of the variability in soil moisture. The SSTs in the Indian Ocean, the North Atlantic and the eastern tropical Pacific Oceans are also identified as important sources of variability in the soil moisture, during MAM, JJA and SON/DJF, respectively. In addition, prolonged linear trends in each season are an important source. Using the slow principal component time series as predictands, a statistical scheme for the seasonal forecasting of soil moisture across China is developed. The prediction skills, in terms of the percentage of explained variance for the verification period (1992-2008), are 59, 51, 62 and 77 % during MAM-DJF, respectively. This is considerably higher than a normal grid prediction scheme.

  4. Constraining future terrestrial carbon cycle projections using observation-based water and carbon flux estimates.

    PubMed

    Mystakidis, Stefanos; Davin, Edouard L; Gruber, Nicolas; Seneviratne, Sonia I

    2016-06-01

    The terrestrial biosphere is currently acting as a sink for about a third of the total anthropogenic CO2  emissions. However, the future fate of this sink in the coming decades is very uncertain, as current earth system models (ESMs) simulate diverging responses of the terrestrial carbon cycle to upcoming climate change. Here, we use observation-based constraints of water and carbon fluxes to reduce uncertainties in the projected terrestrial carbon cycle response derived from simulations of ESMs conducted as part of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). We find in the ESMs a clear linear relationship between present-day evapotranspiration (ET) and gross primary productivity (GPP), as well as between these present-day fluxes and projected changes in GPP, thus providing an emergent constraint on projected GPP. Constraining the ESMs based on their ability to simulate present-day ET and GPP leads to a substantial decrease in the projected GPP and to a ca. 50% reduction in the associated model spread in GPP by the end of the century. Given the strong correlation between projected changes in GPP and in NBP in the ESMs, applying the constraints on net biome productivity (NBP) reduces the model spread in the projected land sink by more than 30% by 2100. Moreover, the projected decline in the land sink is at least doubled in the constrained ensembles and the probability that the terrestrial biosphere is turned into a net carbon source by the end of the century is strongly increased. This indicates that the decline in the future land carbon uptake might be stronger than previously thought, which would have important implications for the rate of increase in the atmospheric CO2 concentration and for future climate change. PMID:26732346

  5. Constraining future terrestrial carbon cycle projections using observation-based water and carbon flux estimates.

    PubMed

    Mystakidis, Stefanos; Davin, Edouard L; Gruber, Nicolas; Seneviratne, Sonia I

    2016-06-01

    The terrestrial biosphere is currently acting as a sink for about a third of the total anthropogenic CO2  emissions. However, the future fate of this sink in the coming decades is very uncertain, as current earth system models (ESMs) simulate diverging responses of the terrestrial carbon cycle to upcoming climate change. Here, we use observation-based constraints of water and carbon fluxes to reduce uncertainties in the projected terrestrial carbon cycle response derived from simulations of ESMs conducted as part of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). We find in the ESMs a clear linear relationship between present-day evapotranspiration (ET) and gross primary productivity (GPP), as well as between these present-day fluxes and projected changes in GPP, thus providing an emergent constraint on projected GPP. Constraining the ESMs based on their ability to simulate present-day ET and GPP leads to a substantial decrease in the projected GPP and to a ca. 50% reduction in the associated model spread in GPP by the end of the century. Given the strong correlation between projected changes in GPP and in NBP in the ESMs, applying the constraints on net biome productivity (NBP) reduces the model spread in the projected land sink by more than 30% by 2100. Moreover, the projected decline in the land sink is at least doubled in the constrained ensembles and the probability that the terrestrial biosphere is turned into a net carbon source by the end of the century is strongly increased. This indicates that the decline in the future land carbon uptake might be stronger than previously thought, which would have important implications for the rate of increase in the atmospheric CO2 concentration and for future climate change.

  6. Observability-Based Approach to Design, Analysis and Optimization of Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Alaeddini, Atiye

    The present dissertation aims to use the coupling between actuation and sensing in nonlinear systems to alternatively design a set of feasible control policies, to find the minimum number of sensors, or to find an optimal sensors configuration. Feasibility, here, means a combination of sensory system and control policy which guarantees observability. In some cases the optimality of the obtained solution is also considered. In some nonlinear systems, full observability requires active sensing, and will be shown how control policies that guarantee observability can be obtained by considering the geometry of the system dynamics. The observability matrix is used to test observability, whereas for the optimization problem observability Gramian matrix is used. This dissertation also considers the stability in designing controllers. The problem of designing a stabilizing control policy for a control-affine nonlinear system is addressed. The effect of time-varying control on the observability is investigated and shown to potentially improve the system observability. A particular application of the techniques considered here is the problem of designing network sensing and topology based on the observability criteria. The goal is to develop a protocol for the network which guarantees privacy. Furthermore, given a network of connected agents, we would like to determine which nodes should be observed to maximize information about the entire network. This dissertation begins with theoretical basis then moves towards applications of the theory. The first application is navigation of an autonomous ground robot with limited inertial sensing, motivated by the visuomotor system of insects. The second application is the problem of detecting an epidemic disease, which demonstrates design of an observability-based optimal network.

  7. A Robust Actin Filaments Image Analysis Framework

    PubMed Central

    Alioscha-Perez, Mitchel; Benadiba, Carine; Goossens, Katty; Kasas, Sandor; Dietler, Giovanni; Willaert, Ronnie; Sahli, Hichem

    2016-01-01

    The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a ‘cartoon’ part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the ‘cartoon’ image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts

  8. A Robust Actin Filaments Image Analysis Framework.

    PubMed

    Alioscha-Perez, Mitchel; Benadiba, Carine; Goossens, Katty; Kasas, Sandor; Dietler, Giovanni; Willaert, Ronnie; Sahli, Hichem

    2016-08-01

    The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a 'cartoon' part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the 'cartoon' image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts grown in

  9. The validation of the robust input estimation approach to two-dimensional inverse heat conduction problems

    SciTech Connect

    Tuan, P.C.; Ju, M.C.

    2000-03-01

    A novel adaptive and robust input estimation inverse methodology of estimating the time-varying unknown heat flux, named as the input, on the two active boundaries of a 2-D inverse heat conduction problem is presented. The algorithm includes using the Kalman filter to propose a regression model between the residual innovation and the two thermal unknown boundaries flux through given 2-D heat conduction state-space models and noisy measurement sequence. Based on this regression equation, a recursive least-square estimator (RLSE) weighted by the forgetting factor is proposed to on-line estimate these unknowns. The adaptive and robust weighting technique is essential since unknowns input are time-varied and have unpredictable changing status. In this article, the authors provide the bandwidth analysis together with bias and variance tests to construct an efficient and robust forgetting factor as the ratio between the standard deviation of measurement and observable bias innovation at each time step. Herein, the unknowns are robustly and adaptively estimated under the system involving measurement noise, process error, and unpredictable change status of time-varying unknowns. The capabilities of the proposed algorithm are demonstrated through the comparison with the conventional input estimation algorithm and validated by two benchmark performance tests in 2-D cases. Results show that the proposed algorithm not only exhibits superior robust capability but also enhances the estimation performance and highly facilitates practical implementation.

  10. A network property necessary for concentration robustness

    PubMed Central

    Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

    2016-01-01

    Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications. PMID:27759015

  11. Efficient robust conditional random fields.

    PubMed

    Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

    2015-10-01

    Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

  12. Perfect and Near-Perfect Adaptation in Cell Signaling.

    PubMed

    Ferrell, James E

    2016-02-24

    Adaptation is an important basic feature of cellular regulation. Previous theoretical work has identified three types of circuits-negative feedback loops, incoherent feedforward systems, and state-dependent inactivation systems-that can achieve perfect or near-perfect adaptation. Recent work has added another strategy, termed antithetic integral feedback, to the list of motifs capable of robust perfect adaptation. Here, we discuss the properties, limitations, and biological relevance of each of these circuits. PMID:27135159

  13. Robust satisficing and the probability of survival

    NASA Astrophysics Data System (ADS)

    Ben-Haim, Yakov

    2014-01-01

    Concepts of robustness are sometimes employed when decisions under uncertainty are made without probabilistic information. We present a theorem that establishes necessary and sufficient conditions for non-probabilistic robustness to be equivalent to the probability of satisfying the specified outcome requirements. When this holds, probability is enhanced (or maximised) by enhancing (or maximising) robustness. Two further theorems establish important special cases. These theorems have implications for success or survival under uncertainty. Applications to foraging and finance are discussed.

  14. Robustness enhancement of neurocontroller and state estimator

    NASA Technical Reports Server (NTRS)

    Troudet, Terry

    1993-01-01

    The feasibility of enhancing neurocontrol robustness, through training of the neurocontroller and state estimator in the presence of system uncertainties, is investigated on the example of a multivariable aircraft control problem. The performance and robustness of the newly trained neurocontroller are compared to those for an existing neurocontrol design scheme. The newly designed dynamic neurocontroller exhibits a better trade-off between phase and gain stability margins, and it is significantly more robust to degradations of the plant dynamics.

  15. AIRS Observations Based Evaluation of Relative Climate Feedback Strengths on a GCM Grid-Scale

    NASA Astrophysics Data System (ADS)

    Molnar, G. I.; Susskind, J.

    2012-12-01

    -term climate feedbacks due to global warming, for example. Nevertheless, one should take more confidence of greenhouse warming predictions of those GCMs that reproduce the (high quality observations-based) shorter-term feedback-relationships the best.

  16. Robust Mokken Scale Analysis by Means of the Forward Search Algorithm for Outlier Detection

    ERIC Educational Resources Information Center

    Zijlstra, Wobbe P.; van der Ark, L. Andries; Sijtsma, Klaas

    2011-01-01

    Exploratory Mokken scale analysis (MSA) is a popular method for identifying scales from larger sets of items. As with any statistical method, in MSA the presence of outliers in the data may result in biased results and wrong conclusions. The forward search algorithm is a robust diagnostic method for outlier detection, which we adapt here to…

  17. Robust Fixed-Structure Controller Synthesis

    NASA Technical Reports Server (NTRS)

    Corrado, Joseph R.; Haddad, Wassim M.; Gupta, Kajal (Technical Monitor)

    2000-01-01

    The ability to develop an integrated control system design methodology for robust high performance controllers satisfying multiple design criteria and real world hardware constraints constitutes a challenging task. The increasingly stringent performance specifications required for controlling such systems necessitates a trade-off between controller complexity and robustness. The principle challenge of the minimal complexity robust control design is to arrive at a tractable control design formulation in spite of the extreme complexity of such systems. Hence, design of minimal complexitY robust controllers for systems in the face of modeling errors has been a major preoccupation of system and control theorists and practitioners for the past several decades.

  18. Molecular mechanisms of robustness in plants

    PubMed Central

    Lempe, Janne; Lachowiec, Jennifer; Sullivan, Alessandra. M.; Queitsch, Christine

    2012-01-01

    Robustness, the ability of organisms to buffer phenotypes against perturbations, has drawn renewed interest among developmental biologists and geneticists. A growing body of research supports an important role of robustness in the genotype to phenotype translation, with far- reaching implications for evolutionary processes and disease susceptibility. Like for animals and fungi, plant robustness is a function of genetic network architecture. Most perturbations are buffered; however, perturbation of network hubs destabilizes many traits. Here, we review recent advances in identifying molecular robustness mechanisms in plants that have been enabled by a combination of classical genetics and population genetics with genome-scale data. PMID:23279801

  19. Robust Hypothesis Testing with alpha -Divergence

    NASA Astrophysics Data System (ADS)

    Gul, Gokhan; Zoubir, Abdelhak M.

    2016-09-01

    A robust minimax test for two composite hypotheses, which are determined by the neighborhoods of two nominal distributions with respect to a set of distances - called $\\alpha-$divergence distances, is proposed. Sion's minimax theorem is adopted to characterize the saddle value condition. Least favorable distributions, the robust decision rule and the robust likelihood ratio test are derived. If the nominal probability distributions satisfy a symmetry condition, the design procedure is shown to be simplified considerably. The parameters controlling the degree of robustness are bounded from above and the bounds are shown to be resulting from a solution of a set of equations. The simulations performed evaluate and exemplify the theoretical derivations.

  20. Observer-based predictive controller design with network-enhanced time-delay compensation

    NASA Astrophysics Data System (ADS)

    Florin Caruntu, Constantin

    2015-02-01

    State feedback control is very attractive due to the precise computation of the gain matrix, but the implementation of a state feedback controller is possible only when all state variables are directly measurable. This condition is almost impossible to accomplish due to the excess number of required sensors or unavailability of states for measurement in most of the practical situations. Hence, the need for an estimator or observer is obvious to estimate all the state variables by observing the input and the output of the controlled system. As such, the goal of this paper is to provide a control design methodology based on a Luenberger observer design that can assure the closed-loop performances of a vehicle drivetrain with backlash, while compensating the network-enhanced time-varying delays. This goal is achieved in a sequential manner: firstly, a piecewise linear model of two inertias drivetrain, which takes into consideration the backlash nonlinearity and the network-enhanced time-varying delay effects is derived; then, a Luenberger observer which estimates the state variables is synthesized and the robust full state-feedback predictive controller based on flexible control Lyapunov functions is designed to explicitly take into account the bounds of the disturbances caused by time-varying delays and to guarantee also the input-to-state stability of the system in a non-conservative way. The full state-feedback predictive control strategy based on the Luenberger observer design was experimentally tested on a vehicle drivetrain emulator controlled through controller area network, with the aim of minimizing the backlash effects while compensating the network-enhanced delays.

  1. Animal Density and Track Counts: Understanding the Nature of Observations Based on Animal Movements

    PubMed Central

    Keeping, Derek; Pelletier, Rick

    2014-01-01

    Counting animals to estimate their population sizes is often essential for their management and conservation. Since practitioners frequently rely on indirect observations of animals, it is important to better understand the relationship between such indirect indices and animal abundance. The Formozov-Malyshev-Pereleshin (FMP) formula provides a theoretical foundation for understanding the relationship between animal track counts and the true density of species. Although this analytical method potentially has universal applicability wherever animals are readily detectable by their tracks, it has long been unique to Russia and remains widely underappreciated. In this paper, we provide a test of the FMP formula by isolating the influence of animal travel path tortuosity (i.e., convolutedness) on track counts. We employed simulations using virtual and empirical data, in addition to a field test comparing FMP estimates with independent estimates from line transect distance sampling. We verify that track counts (total intersections between animals and transects) are determined entirely by density and daily movement distances. Hence, the FMP estimator is theoretically robust against potential biases from specific shapes or patterns of animal movement paths if transects are randomly situated with respect to those movements (i.e., the transects do not influence animals’ movements). However, detectability (the detection probability of individual animals) is not determined simply by daily travel distance but also by tortuosity, so ensuring that all intersections with transects are counted regardless of the number of individual animals that made them becomes critical for an accurate density estimate. Additionally, although tortuosity has no bearing on mean track encounter rates, it does affect encounter rate variance and therefore estimate precision. We discuss how these fundamental principles made explicit by the FMP formula have widespread implications for methods of

  2. Noise robust speech recognition with support vector learning algorithms

    NASA Astrophysics Data System (ADS)

    Namarvar, Hassan H.; Berger, Theodore W.

    2001-05-01

    We propose a new noise robust speech recognition system using time-frequency domain analysis and radial basis function (RBF) support vector machines (SVM). Here, we ignore the effects of correlative and nonstationary noise and only focus on continuous additive Gaussian white noise. We then develop an isolated digit/command recognizer and compare its performance to two other systems, in which the SVM classifier has been replaced by multilayer perceptron (MLP) and RBF neural networks. All systems are trained under the low signal-to-noise ratio (SNR) condition. We obtained the best correct classification rate of 83% and 52% for digit recognition on the TI-46 corpus for the SVM and MLP systems, respectively under the SNR=0 (dB), while we could not train the RBF network for the same dataset. The newly developed speech recognition system seems to be noise robust for medium size speech recognition problems under continuous, stationary background noise. However, it is still required to test the system under realistic noisy environment to observe whether the system keeps its adaptability and robustness under such conditions. [Work supported in part by grants from DARPA CBS, NASA, and ONR.

  3. Toward robust AV conferencing on next-generation networks

    NASA Astrophysics Data System (ADS)

    Liu, Haining; Cheng, Liang; El Zarki, Magda

    2005-01-01

    In order to enable a truly pervasive computing environment, next generation networks (including B3G and 4G) will merge the broadband wireless and wireline networking infrastructure. However, due to the tremendous complexity in administration and the unreliability of the wireless channel, provision of hard-guarantees for services on such networks will not happen in the foreseeable future. This consequently makes it particularly challenging to offer viable AV conferencing services due to their stringent synchronization, delay and data fidelity requirements. We propose in this paper a robust application-level solution for wireless mobile AV conferencing on B3G/4G networks. Expecting no special treatment from the network, we apply a novel adaptive delay and synchronization control mechanism to maintain the synchronization and reduce the latency as much as possible. We also employ a robust video coding technique that has better error-resilience capability. We investigate the performance of the proposed solution through simulations using a three-state hidden Markov chain as the generic end-to-end transport channel model. The results show that our scheme yields tight synchronization performance, relatively low end-to-end latency and satisfactory presentation quality. The scheme successfully provides a fairly robust AV conferencing service.

  4. Toward robust AV conferencing on next-generation networks

    NASA Astrophysics Data System (ADS)

    Liu, Haining; Cheng, Liang; El Zarki, Magda

    2004-12-01

    In order to enable a truly pervasive computing environment, next generation networks (including B3G and 4G) will merge the broadband wireless and wireline networking infrastructure. However, due to the tremendous complexity in administration and the unreliability of the wireless channel, provision of hard-guarantees for services on such networks will not happen in the foreseeable future. This consequently makes it particularly challenging to offer viable AV conferencing services due to their stringent synchronization, delay and data fidelity requirements. We propose in this paper a robust application-level solution for wireless mobile AV conferencing on B3G/4G networks. Expecting no special treatment from the network, we apply a novel adaptive delay and synchronization control mechanism to maintain the synchronization and reduce the latency as much as possible. We also employ a robust video coding technique that has better error-resilience capability. We investigate the performance of the proposed solution through simulations using a three-state hidden Markov chain as the generic end-to-end transport channel model. The results show that our scheme yields tight synchronization performance, relatively low end-to-end latency and satisfactory presentation quality. The scheme successfully provides a fairly robust AV conferencing service.

  5. Robust algorithms for anatomic plane primitive detection in MR

    NASA Astrophysics Data System (ADS)

    Dewan, Maneesh; Zhan, Yiqiang; Peng, Zhigang; Zhou, Xiang Sean

    2009-02-01

    One of primary challenges in the medical image data analysis is the ability to handle abnormal, irregular and/or partial cases. In this paper, we present two different robust algorithms towards the goal of automatic planar primitive detection in 3D volumes. The overall algorithm is a bottoms-up approach starting with the anatomic point primitives (or landmarks) detection. The robustness in computing the planar primitives is built in through both a novel consensus-based voting approach, and a random sampling-based weighted least squares regression method. Both these approaches remove inconsistent landmarks and outliers detected in the landmark detection step. Unlike earlier approaches focused towards a particular plane, the presented approach is generic and can be easily adapted to computing more complex primitives such as ROIs or surfaces. To demonstrate the robustness and accuracy of our approach, we present extensive results for automatic plane detection (Mig-Sagittal and Optical Triangle planes) in brain MR-images. In comparison to ground truth, our approach has marginal errors on about 90 patients. The algorithm also works really well under adverse conditions of arbitrary rotation and cropping of the 3D volume. In order to exhibit generalization of the approach, we also present preliminary results on intervertebrae-plane detection for 3D spine MR application.

  6. Robust fault detection filter design

    NASA Astrophysics Data System (ADS)

    Douglas, Randal Kirk

    The detection filter is a specially tuned linear observer that forms the residual generation part of an analytical redundancy system designed for model-based fault detection and identification. The detection filter has an invariant state subspace structure that produces a residual with known and fixed directional characteristics in response to a known design fault direction. In addition to a parameterization of the detection filter gain, three methods are given for improving performance in the presence of system disturbances, sensor noise, model mismatch and sensitivity to small parameter variations. First, it is shown that by solving a modified algebraic Riccati equation, a stabilizing detection filter gain is found that bounds the H-infinity norm of the transfer matrix from system disturbances and sensor noise to the detection filter residual. Second, a specially chosen expanded-order detection filter is formed with fault detection properties identical to a set of independent reduced-order filters that have no structural constraints. This result is important to the practitioner because the difficult problem of finding a detection filter insensitive to disturbances and sensor noise is converted to the easier problem of finding a set of uncoupled noise insensitive filters. Furthermore, the statistical properties of the reduced-order filter residuals are easier to find than the statistical properties of the structurally constrained detection filter residual. Third, an interpretation of the detection filter as a special case of the dual of the restricted decoupling problem leads to a new detection filter eigenstructure assignment algorithm. The new algorithm places detection filter left eigenvectors, which annihilate the detection spaces, rather than right eigenvectors, which span the detection spaces. This allows for a more flexible observer based fault detection system structure that could not be formulated as a detection filter. Furthermore, the link to the dual

  7. Robust control with structured perturbations

    NASA Technical Reports Server (NTRS)

    Keel, Leehyun

    1988-01-01

    Two important problems in the area of control systems design and analysis are discussed. The first is the robust stability using characteristic polynomial, which is treated first in characteristic polynomial coefficient space with respect to perturbations in the coefficients of the characteristic polynomial, and then for a control system containing perturbed parameters in the transfer function description of the plant. In coefficient space, a simple expression is first given for the l(sup 2) stability margin for both monic and non-monic cases. Following this, a method is extended to reveal much larger stability region. This result has been extended to the parameter space so that one can determine the stability margin, in terms of ranges of parameter variations, of the closed loop system when the nominal stabilizing controller is given. The stability margin can be enlarged by a choice of better stabilizing controller. The second problem describes the lower order stabilization problem, the motivation of the problem is as follows. Even though the wide range of stabilizing controller design methodologies is available in both the state space and transfer function domains, all of these methods produce unnecessarily high order controllers. In practice, the stabilization is only one of many requirements to be satisfied. Therefore, if the order of a stabilizing controller is excessively high, one can normally expect to have a even higher order controller on the completion of design such as inclusion of dynamic response requirements, etc. Therefore, it is reasonable to have a lowest possible order stabilizing controller first and then adjust the controller to meet additional requirements. The algorithm for designing a lower order stabilizing controller is given. The algorithm does not necessarily produce the minimum order controller; however, the algorithm is theoretically logical and some simulation results show that the algorithm works in general.

  8. Noise and Robustness in Phyllotaxis

    PubMed Central

    Mirabet, Vincent; Besnard, Fabrice; Vernoux, Teva; Boudaoud, Arezki

    2012-01-01

    A striking feature of vascular plants is the regular arrangement of lateral organs on the stem, known as phyllotaxis. The most common phyllotactic patterns can be described using spirals, numbers from the Fibonacci sequence and the golden angle. This rich mathematical structure, along with the experimental reproduction of phyllotactic spirals in physical systems, has led to a view of phyllotaxis focusing on regularity. However all organisms are affected by natural stochastic variability, raising questions about the effect of this variability on phyllotaxis and the achievement of such regular patterns. Here we address these questions theoretically using a dynamical system of interacting sources of inhibitory field. Previous work has shown that phyllotaxis can emerge deterministically from the self-organization of such sources and that inhibition is primarily mediated by the depletion of the plant hormone auxin through polarized transport. We incorporated stochasticity in the model and found three main classes of defects in spiral phyllotaxis – the reversal of the handedness of spirals, the concomitant initiation of organs and the occurrence of distichous angles – and we investigated whether a secondary inhibitory field filters out defects. Our results are consistent with available experimental data and yield a prediction of the main source of stochasticity during organogenesis. Our model can be related to cellular parameters and thus provides a framework for the analysis of phyllotactic mutants at both cellular and tissular levels. We propose that secondary fields associated with organogenesis, such as other biochemical signals or mechanical forces, are important for the robustness of phyllotaxis. More generally, our work sheds light on how a target pattern can be achieved within a noisy background. PMID:22359496

  9. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  10. Climate adaptation heuristics and the science/policy divide

    SciTech Connect

    Preston, Benjamin L.; Mustelin, Johanna; Maloney, Megan C.

    2013-09-05

    The adaptation science enterprise has expanded rapidly in recent years, presumably in response to growth in demand for knowledge that can facilitate adaptation policy and practice. However, evidence suggests such investments in adaptation science have not necessarily translated into adaptation implementation. One potential constraint on adaptation may be the underlying heuristics that are used as the foundation for both adaptation research and practice. In this paper, we explore the adaptation academic literature with the objective of identifying adaptation heuristics, assessing the extent to which they have become entrenched within the adaptation discourse, and discussing potential weaknesses in their framing that could undermine adaptation efforts. This investigation is supported by a multi-method analysis that includes both a quantitative content analysis of the adaptation literature that evidences the use of adaptation heuristics and a qualitative analysis of the implications of such heuristics for enhancing or hindering the implementation of adaptation. Results demonstrate that a number of heuristic devices are commonly used in both the peer-reviewed adaptation literature as well as within grey literature designed to inform adaptation practitioners. Furthermore, the apparent lack of critical reflection upon the robustness of these heuristics for diverse contexts may contribute to potential cognitive bias with respect to the framing of adaptation by both researchers and practitioners. Finally, we discuss this phenomenon by drawing upon heuristic-analytic theory, which has explanatory utility in understanding both the origins of such heuristics as well as the measures that can be pursued toward the co-generation of more robust approaches to adaptation problem-solving.

  11. Climate adaptation heuristics and the science/policy divide

    DOE PAGES

    Preston, Benjamin L.; Mustelin, Johanna; Maloney, Megan C.

    2013-09-05

    The adaptation science enterprise has expanded rapidly in recent years, presumably in response to growth in demand for knowledge that can facilitate adaptation policy and practice. However, evidence suggests such investments in adaptation science have not necessarily translated into adaptation implementation. One potential constraint on adaptation may be the underlying heuristics that are used as the foundation for both adaptation research and practice. In this paper, we explore the adaptation academic literature with the objective of identifying adaptation heuristics, assessing the extent to which they have become entrenched within the adaptation discourse, and discussing potential weaknesses in their framing thatmore » could undermine adaptation efforts. This investigation is supported by a multi-method analysis that includes both a quantitative content analysis of the adaptation literature that evidences the use of adaptation heuristics and a qualitative analysis of the implications of such heuristics for enhancing or hindering the implementation of adaptation. Results demonstrate that a number of heuristic devices are commonly used in both the peer-reviewed adaptation literature as well as within grey literature designed to inform adaptation practitioners. Furthermore, the apparent lack of critical reflection upon the robustness of these heuristics for diverse contexts may contribute to potential cognitive bias with respect to the framing of adaptation by both researchers and practitioners. Finally, we discuss this phenomenon by drawing upon heuristic-analytic theory, which has explanatory utility in understanding both the origins of such heuristics as well as the measures that can be pursued toward the co-generation of more robust approaches to adaptation problem-solving.« less

  12. Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems.

    PubMed

    Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan

    2015-11-01

    This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. PMID:26365366

  13. Comparability of naturalistic and controlled observation assessment of adaptive behavior.

    PubMed

    Millham, J; Chilcutt, J; Atkinson, B L

    1978-07-01

    The comparability of retrospective naturalistic and controlled observation assessment of adaptive behavior was evaluated. The number, degree, and direction of discrepancies were evaluated with respect to level of retardation of the client, rater differences, behavior domain sampled, and prior observational base for the ratings. Generally poor comparability between the procedures was found and questions were raised concerning the types of generalizability that can be made from adaptive behavior assessment obtained under the two procedures.

  14. A novel robust digital image watermarking method using SVD and GA

    NASA Astrophysics Data System (ADS)

    Golshan, F.; Mohammadi, K.

    2011-06-01

    A novel evolutionary-based watermarking algorithm for digital images is proposed. Robustness and imperceptibility are two important properties in digital image watermarking which compete with each other. In this paper a DCT and SVD based intelligent algorithm is applied to make a tradeoff between these two properties. First of all, a cover image is divided into 8×8 blocks and some of them which are special ones are transformed to DCT domain. The singular value decomposition is applied to DCT coefficients and singular values change according to a binary watermark image. The binary watermark image is obtained by Genetic Algorithm to solve the optimization problem between robustness and imperceptibility. So the novelty of this method is image adaptability. Robustness of the proposed method against several attacks such as filtering, noise contamination, JPEG compression and some geometrical attacks is good. In comparison with a recently similar existing work, experimental results show improvement in both imperceptibility and robustness.

  15. The Utility of Robust Means in Statistics

    ERIC Educational Resources Information Center

    Goodwyn, Fara

    2012-01-01

    Location estimates calculated from heuristic data were examined using traditional and robust statistical methods. The current paper demonstrates the impact outliers have on the sample mean and proposes robust methods to control for outliers in sample data. Traditional methods fail because they rely on the statistical assumptions of normality and…

  16. Robust Hope and Teacher Education Policy

    ERIC Educational Resources Information Center

    Sawyer, Wayne; Singh, Michael; Woodrow, Christine; Downes, Toni; Johnston, Christine; Whitton, Diana

    2007-01-01

    The research question for this paper is: How can we mobilise robust hope in the analysis of teacher education policy? Specifically, this paper asks how a robust hope framework might speak to the "Top of the Class," a report into teacher education by the Australian House of Representatives Standing Committee on Education and Vocational Training.

  17. Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels

    PubMed Central

    Steinacher, Arno; Bates, Declan G.; Akman, Ozgur E.; Soyer, Orkun S.

    2016-01-01

    Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for

  18. Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

    PubMed

    Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

    2016-01-01

    Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for

  19. A model observer based on human perception to quantify the detectability

    NASA Astrophysics Data System (ADS)

    Acharian, Georges; Guyader, Nathalie; Vignolle, Jean-Michel; Jutten, Christian

    2014-03-01

    In medical imaging, model observers such as the "Hotelling observer" and the "Non Prewhitening Matched Filter" have been proposed to detect objects in X-ray images. These models, based on decision theory, are applied over the entire image. In this paper, we developed a model that mimics some processes of human visual perception. The proposed model is locally applied on some particular areas that correspond to the salient areas of the object. By doing this, the model mimics the sequence of eye fixations that we make when we explore an image for example in order to detect an object. The study is divided into three parts: a psychophysical experiment to obtain human's performance to detect various objects in noises, a theoretical part to develop the proposed model, and finally, a result part. During the experiment, several participants were asked to detect objects in noisy images using a free search task. The luminance contrast of objects was adaptively adjusted according to their responses to obtain a percentage of correct detection for each object of 50 %. The proposed model, based on decision theory, was applied locally on some areas of the image that has a size corresponding to the high visual acuity of foveal vision. Areas were chosen according to their high saliency values computed through a bio-inspired model of visual attention. For each area, our model returned a detectability index. By supposing statistical independence between areas, the local indexes are combined into a global detectability index. Results show that the proposed model fits the results of the psychophysical experiment and outperforms classical models of the literature.

  20. Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

    NASA Astrophysics Data System (ADS)

    Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

    2016-01-01

    Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

  1. Evaluating efficiency and robustness in cilia design

    NASA Astrophysics Data System (ADS)

    Guo, Hanliang; Kanso, Eva

    2016-03-01

    Motile cilia are used by many eukaryotic cells to transport flow. Cilia-driven flows are important to many physiological functions, yet a deep understanding of the interplay between the mechanical structure of cilia and their physiological functions in healthy and diseased conditions remains elusive. To develop such an understanding, one needs a quantitative framework to assess cilia performance and robustness when subject to perturbations in the cilia apparatus. Here we link cilia design (beating patterns) to function (flow transport) in the context of experimentally and theoretically derived cilia models. We particularly examine the optimality and robustness of cilia design. Optimality refers to efficiency of flow transport, while robustness is defined as low sensitivity to variations in the design parameters. We find that suboptimal designs can be more robust than optimal ones. That is, designing for the most efficient cilium does not guarantee robustness. These findings have significant implications on the understanding of cilia design in artificial and biological systems.

  2. Evaluating efficiency and robustness in cilia design.

    PubMed

    Guo, Hanliang; Kanso, Eva

    2016-03-01

    Motile cilia are used by many eukaryotic cells to transport flow. Cilia-driven flows are important to many physiological functions, yet a deep understanding of the interplay between the mechanical structure of cilia and their physiological functions in healthy and diseased conditions remains elusive. To develop such an understanding, one needs a quantitative framework to assess cilia performance and robustness when subject to perturbations in the cilia apparatus. Here we link cilia design (beating patterns) to function (flow transport) in the context of experimentally and theoretically derived cilia models. We particularly examine the optimality and robustness of cilia design. Optimality refers to efficiency of flow transport, while robustness is defined as low sensitivity to variations in the design parameters. We find that suboptimal designs can be more robust than optimal ones. That is, designing for the most efficient cilium does not guarantee robustness. These findings have significant implications on the understanding of cilia design in artificial and biological systems. PMID:27078459

  3. Maturity Matrices for Quality of Model- and Observation-Based Climate Data Records

    NASA Astrophysics Data System (ADS)

    Höck, Heinke; Kaiser-Weiss, Andrea; Kaspar, Frank; Stockhause, Martina; Toussaint, Frank; Lautenschlager, Michael

    2015-04-01

    In the field of Software Engineering the Capability Maturity Model is used to evaluate and improve software development processes. The application of a Maturity Matrix is a method to assess the degree of software maturity. This method was adapted to the maturity of Earth System data in scientific archives. The application of such an approach to Climate Data Records was first proposed in the context of satellite-based climate products and applied by NOAA and NASA. The European FP7 project CORE-CLIMAX suggested and tested extensions of the approach in order to allow the applicability to additional climate datasets, e.g. based on in-situ observations as well as model-based reanalysis. Within that project the concept was applied to products of satellite- and in-situ based datasets. Examples are national ground-based data from Germany as an example for typical products of a national meteorological service, the EUMETSAT Satellite Application Facility Network, the ESA Climate Change Initiative, European Reanalysis activities (ERA-CLIM) and international in situ-based climatologies such as GPCC, ECA&D, BSRN, HadSST. Climate models and their related output have some additional characteristics that need specific consideration in such an approach. Here we use examples from the World Data Centre for Climate (WDCC) to discuss the applicability. The WDCC focuses on climate data products, specifically those resulting from climate simulations. Based on these already existing Maturity Matrix models, WDCC developed a generic Quality Assessment System for Earth System data. A self-assessment is performed using a maturity matrix evaluating the data quality for five maturity levels with respect to the criteria data and metadata consistency, completeness, accessibility and accuracy. The classical goals of a quality assessment system in a data processing workflow are: (1) to encourage data creators to improve quality to reach the next quality level, (2) enable data consumers to decide

  4. Defining robustness protocols: a method to include and evaluate robustness in clinical plans

    NASA Astrophysics Data System (ADS)

    McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

    2015-04-01

    We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

  5. Molecular evolution and thermal adaptation

    NASA Astrophysics Data System (ADS)

    Chen, Peiqiu

    2011-12-01

    generations. Diversity plays an important role in thermal adaptation: While monoclonal strains adapt via acquisition and rapid fixation of new early mutations, wild population adapt via standing genetic variations, and they are more robust against thermal shocks due to greater diversity within the initial population.

  6. Step Detection Robust against the Dynamics of Smartphones

    PubMed Central

    Lee, Hwan-hee; Choi, Suji; Lee, Myeong-jin

    2015-01-01

    A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms. PMID:26516857

  7. Robust document image binarization technique for degraded document images.

    PubMed

    Su, Bolan; Lu, Shijian; Tan, Chew Lim

    2013-04-01

    Segmentation of text from badly degraded document images is a very challenging task due to the high inter/intra-variation between the document background and the foreground text of different document images. In this paper, we propose a novel document image binarization technique that addresses these issues by using adaptive image contrast. The adaptive image contrast is a combination of the local image contrast and the local image gradient that is tolerant to text and background variation caused by different types of document degradations. In the proposed technique, an adaptive contrast map is first constructed for an input degraded document image. The contrast map is then binarized and combined with Canny's edge map to identify the text stroke edge pixels. The document text is further segmented by a local threshold that is estimated based on the intensities of detected text stroke edge pixels within a local window. The proposed method is simple, robust, and involves minimum parameter tuning. It has been tested on three public datasets that are used in the recent document image binarization contest (DIBCO) 2009 & 2011 and handwritten-DIBCO 2010 and achieves accuracies of 93.5%, 87.8%, and 92.03%, respectively, that are significantly higher than or close to that of the best-performing methods reported in the three contests. Experiments on the Bickley diary dataset that consists of several challenging bad quality document images also show the superior performance of our proposed method, compared with other techniques. PMID:23221822

  8. Robustness and structure of complex networks

    NASA Astrophysics Data System (ADS)

    Shao, Shuai

    This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

  9. Robust stability of second-order systems

    NASA Technical Reports Server (NTRS)

    Chuang, C. H.

    1993-01-01

    This report presents a robust control design using strictly positive realness for second-order dynamic systems. The robust strictly positive real controller allows the system to be stabilized with only acceleration measurements. An important property of this design is that stabilization of the system is independent of the system parameters. The control design connects a virtual system to the given plant. The combined system is positive real regardless of system parameter uncertainty. Then any strictly positive real controllers can be used to achieve robust stability. A spring-mass system example and its computer simulations are presented to demonstrate this controller design.

  10. Regulated cell death and adaptive stress responses.

    PubMed

    Galluzzi, Lorenzo; Bravo-San Pedro, José Manuel; Kepp, Oliver; Kroemer, Guido

    2016-06-01

    Eukaryotic cells react to potentially dangerous perturbations of the intracellular or extracellular microenvironment by activating rapid (transcription-independent) mechanisms that attempt to restore homeostasis. If such perturbations persist, cells may still try to cope with stress by activating delayed and robust (transcription-dependent) adaptive systems, or they may actively engage in cellular suicide. This regulated form of cell death can manifest with various morphological, biochemical and immunological correlates, and constitutes an ultimate attempt of stressed cells to maintain organismal homeostasis. Here, we dissect the general organization of adaptive cellular responses to stress, their intimate connection with regulated cell death, and how the latter operates for the preservation of organismal homeostasis.

  11. Chaotic satellite attitude control by adaptive approach

    NASA Astrophysics Data System (ADS)

    Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping

    2014-06-01

    In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.

  12. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

    PubMed Central

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  13. Tempering temperature changes for robust development.

    PubMed

    Delidakis, Christos

    2014-05-22

    Developmental signaling pathways needed to evolve to be robust against environmental fluctuations. In this issue, Shimizu et al. reveal a complex system of interacting endocytic pathways that help to maintain consistent levels of Notch activity across a range of temperatures.

  14. Robust lateral control of highway vehicles

    SciTech Connect

    Byrne, R.H.; Abdallah, C.

    1994-08-01

    Vehicle lateral dynamics are affected by vehicle mass, longitudinal velocity, vehicle inertia, and the cornering stiffness of the tires. All of these parameters are subject to variation, even over the course of a single trip. Therefore, a practical lateral control system must guarantee stability, and hopefully ride comfort, over a wide range of parameter changes. This paper describes a robust controller which theoretically guarantees stability over a wide range of parameter changes. The robust controller is designed using a frequency domain transfer function approach. An uncertainty band in the frequency domain is determined using simulations over the range of expected parameter variations. Based on this bound, a robust controller is designed by solving the Nevanlinna-Pick interpolation problem. The performance of the robust controller is then evaluated over the range of parameter variations through simulations.

  15. Bypass rewiring and robustness of complex networks.

    PubMed

    Park, Junsang; Hahn, Sang Geun

    2016-08-01

    A concept of bypass rewiring is introduced, and random bypass rewiring is analytically and numerically investigated with simulations. Our results show that bypass rewiring makes networks robust against removal of nodes including random failures and attacks. In particular, random bypass rewiring connects all nodes except the removed nodes on an even degree infinite network and makes the percolation threshold 0 for arbitrary occupation probabilities. In our example, the even degree network is more robust than the original network with random bypass rewiring, while the original network is more robust than the even degree networks without random bypass. We propose a greedy bypass rewiring algorithm which guarantees the maximum size of the largest component at each step, assuming which node will be removed next is unknown. The simulation result shows that the greedy bypass rewiring algorithm improves the robustness of the autonomous system of the Internet under attacks more than random bypass rewiring.

  16. Bypass rewiring and robustness of complex networks

    NASA Astrophysics Data System (ADS)

    Park, Junsang; Hahn, Sang Geun

    2016-08-01

    A concept of bypass rewiring is introduced, and random bypass rewiring is analytically and numerically investigated with simulations. Our results show that bypass rewiring makes networks robust against removal of nodes including random failures and attacks. In particular, random bypass rewiring connects all nodes except the removed nodes on an even degree infinite network and makes the percolation threshold 0 for arbitrary occupation probabilities. In our example, the even degree network is more robust than the original network with random bypass rewiring, while the original network is more robust than the even degree networks without random bypass. We propose a greedy bypass rewiring algorithm which guarantees the maximum size of the largest component at each step, assuming which node will be removed next is unknown. The simulation result shows that the greedy bypass rewiring algorithm improves the robustness of the autonomous system of the Internet under attacks more than random bypass rewiring.

  17. Robust control design for aerospace applications

    NASA Technical Reports Server (NTRS)

    Yedavalli, Rama K.

    1989-01-01

    Time-domain control design for stability robustness of linear systems with structured uncertainty is addressed. Upper bounds on the linear perturbation of an asymptotically stable linear system are obtained, making it possible to maintain stability by using the structural information of the uncertainty. A quantitative measure called the stability robustness index is introduced and used to design controllers for robust stability. The proposed state feedback control design algorithm can be used, for a given set of perturbations, to select the range of control effort for which the system is stability-robust. Conversely it can be used, for a given control effort, to determine the size of the tolerable perturbation. The algorithm is illustrated with examples from aircraft control and large-space-structure control problems.

  18. Robust optimisation of railway crossing geometry

    NASA Astrophysics Data System (ADS)

    Wan, Chang; Markine, Valeri; Dollevoet, Rolf

    2016-05-01

    This paper presents a methodology for improving the crossing (frog) geometry through the robust optimisation approach, wherein the variability of the design parameters within a prescribed tolerance is included in the optimisation problem. Here, the crossing geometry is defined by parameterising the B-spline represented cross-sectional shape and the longitudinal height profile of the nose rail. The dynamic performance of the crossing is evaluated considering the variation of wheel profiles and track alignment. A multipoint approximation method (MAM) is applied in solving the optimisation problem of minimising the contact pressure during the wheel-rail contact and constraining the location of wheel transition at the crossing. To clarify the difference between the robust optimisation and the normal deterministic optimisation approaches, the optimisation problems are solved in both approaches. The results show that the deterministic optimum fails under slight change of the design variables; the robust optimum, however, has improved and robust performance.

  19. Robust design of polyrhythmic neural circuits

    NASA Astrophysics Data System (ADS)

    Schwabedal, Justus T. C.; Neiman, Alexander B.; Shilnikov, Andrey L.

    2014-08-01

    Neural circuit motifs producing coexistent rhythmic patterns are treated as building blocks of multifunctional neuronal networks. We study the robustness of such a motif of inhibitory model neurons to reliably sustain bursting polyrhythms under random perturbations. Without noise, the exponential stability of each of the coexisting rhythms increases with strengthened synaptic coupling, thus indicating an increased robustness. Conversely, after adding noise we find that noise-induced rhythm switching intensifies if the coupling strength is increased beyond a critical value, indicating a decreased robustness. We analyze this stochastic arrhythmia and develop a generic description of its dynamic mechanism. Based on our mechanistic insight, we show how physiological parameters of neuronal dynamics and network coupling can be balanced to enhance rhythm robustness against noise. Our findings are applicable to a broad class of relaxation-oscillator networks, including Fitzhugh-Nagumo and other Hodgkin-Huxley-type networks.

  20. Robust nonlinear control of vectored thrust aircraft

    NASA Technical Reports Server (NTRS)

    Doyle, John C.; Murray, Richard; Morris, John

    1993-01-01

    An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations.

  1. Robust facial expression recognition via compressive sensing.

    PubMed

    Zhang, Shiqing; Zhao, Xiaoming; Lei, Bicheng

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP), are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN), linear support vector machines (SVM) and the nearest subspace (NS), experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks.

  2. Bypass rewiring and robustness of complex networks.

    PubMed

    Park, Junsang; Hahn, Sang Geun

    2016-08-01

    A concept of bypass rewiring is introduced, and random bypass rewiring is analytically and numerically investigated with simulations. Our results show that bypass rewiring makes networks robust against removal of nodes including random failures and attacks. In particular, random bypass rewiring connects all nodes except the removed nodes on an even degree infinite network and makes the percolation threshold 0 for arbitrary occupation probabilities. In our example, the even degree network is more robust than the original network with random bypass rewiring, while the original network is more robust than the even degree networks without random bypass. We propose a greedy bypass rewiring algorithm which guarantees the maximum size of the largest component at each step, assuming which node will be removed next is unknown. The simulation result shows that the greedy bypass rewiring algorithm improves the robustness of the autonomous system of the Internet under attacks more than random bypass rewiring. PMID:27627320

  3. Mechanically robust, chemically inert superhydrophobic charcoal surfaces.

    PubMed

    Xie, Jian-Bo; Li, Liang; Knyazeva, Anastassiya; Weston, James; Naumov, Panče

    2016-08-11

    We report a fast and cost-effective strategy towards the preparation of superhydrophobic composites where a double-sided adhesive tape is paved with charcoal particles. The composites are mechanically robust, and resistant to strong chemical agents. PMID:27405255

  4. Violations of robustness trade-offs

    PubMed Central

    Kitano, Hiroaki

    2010-01-01

    Biological robustness is a principle that may shed light on system-level characteristics of biological systems. One intriguing aspect of the concept of biological robustness is the possible existence of intrinsic trade-offs among robustness, fragility, performance, and so on. At the same time, whether such trade-offs hold regardless of the situation or hold only under specific conditions warrants careful investigation. In this paper, we reassess this concept and argue that biological robustness may hold only when a system is sufficiently optimized and that it may not be conserved when there is room for optimization in its design. Several testable predictions and implications for cell culture experiments are presented. PMID:20571533

  5. Design principles for robust oscillatory behavior.

    PubMed

    Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M

    2015-09-01

    Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

  6. Image Watermarking Based on Adaptive Models of Human Visual Perception

    NASA Astrophysics Data System (ADS)

    Khawne, Amnach; Hamamoto, Kazuhiko; Chitsobhuk, Orachat

    This paper proposes a digital image watermarking based on adaptive models of human visual perception. The algorithm exploits the local activities estimated from wavelet coefficients of each subband to adaptively control the luminance masking. The adaptive luminance is thus delicately combined with the contrast masking and edge detection and adopted as a visibility threshold. With the proposed combination of adaptive visual sensitivity parameters, the proposed perceptual model can be more appropriate to the different characteristics of various images. The weighting function is chosen such that the fidelity, imperceptibility and robustness could be preserved without making any perceptual difference to the image quality.

  7. A Design of Fuzzy Neural Network Based Robust Gain Scheduling Controllers

    NASA Astrophysics Data System (ADS)

    Sato, Yoshishige

    This paper propose robust gain scheduling control design by intelligent control which uses Fuzzy-Neural Network without model. Proposal methods are as follows, To constitute a robust and capable of automatically gain controlling against the conventional fixed PID control system. To build the Neural Network which learns inverse dynamics as feed forward compensation, and to build 2 degrees freedom control which is the feedback compensation. To propose the control system which adaptively adjusts the gain according to the changes of target errors, and to verified the effectiveness of the proposed method.

  8. Research in robust control for hypersonic aircraft

    NASA Technical Reports Server (NTRS)

    Calise, A. J.

    1993-01-01

    The research during the second reporting period has focused on robust control design for hypersonic vehicles. An already existing design for the Hypersonic Winged-Cone Configuration has been enhanced. Uncertainty models for the effects of propulsion system perturbations due to angle of attack variations, structural vibrations, and uncertainty in control effectiveness were developed. Using H(sub infinity) and mu-synthesis techniques, various control designs were performed in order to investigate the impact of these effects on achievable robust performance.

  9. Robustness of entanglement as a resource

    SciTech Connect

    Chaves, Rafael; Davidovich, Luiz

    2010-11-15

    The robustness of multipartite entanglement of systems undergoing decoherence is of central importance to the area of quantum information. Its characterization depends, however, on the measure used to quantify entanglement and on how one partitions the system. Here we show that the unambiguous assessment of the robustness of multipartite entanglement is obtained by considering the loss of functionality in terms of two communication tasks, namely the splitting of information between many parties and the teleportation of states.

  10. ADAPTATION AND ADAPTABILITY, THE BELLEFAIRE FOLLOWUP STUDY.

    ERIC Educational Resources Information Center

    ALLERHAND, MELVIN E.; AND OTHERS

    A RESEARCH TEAM STUDIED INFLUENCES, ADAPTATION, AND ADAPTABILITY IN 50 POORLY ADAPTING BOYS AT BELLEFAIRE, A REGIONAL CHILD CARE CENTER FOR EMOTIONALLY DISTURBED CHILDREN. THE TEAM ATTEMPTED TO GAUGE THE SUCCESS OF THE RESIDENTIAL TREATMENT CENTER IN TERMS OF THE PSYCHOLOGICAL PATTERNS AND ROLE PERFORMANCES OF THE BOYS DURING INDIVIDUAL CASEWORK…

  11. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    NASA Technical Reports Server (NTRS)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  12. The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes

    PubMed Central

    Yang, Xiaofan; Zhu, Yuanrui; Hong, Jing; Yang, Lu-Xing; Wu, Yingbo; Tang, Yuan Yan

    2016-01-01

    There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized meshes (GMs). First, a heuristic growth algorithm (the Proximity-Growth algorithm) is proposed. The resulting proximity-optimal GMs are intuitively robust and hence are adopted as the benchmark. Then, a generalized mesh (GM) is grown up by stepwise optimizing a given measure of network robustness. The following findings are presented: (1) The algebraic connectivity-optimal GMs deviate quickly from the proximity-optimal GMs, yielding a number of less robust GMs. This hints that the rationality of the algebraic connectivity as a measure of network robustness is still in doubt. (2) The effective resistace-optimal GMs and the average edge betweenness-optimal GMs are in line with the proximity-optimal GMs. This partly justifies the two quantities as metrics of network robustness. (3) The efficiency-optimal GMs deviate gradually from the proximity-optimal GMs, yielding some less robust GMs. This suggests the limited utility of the efficiency as a measure of network robustness. PMID:27518448

  13. Enhancing network robustness against malicious attacks

    NASA Astrophysics Data System (ADS)

    Zeng, An; Liu, Weiping

    2012-06-01

    In a recent work [Schneider , Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.1009440108 108, 3838 (2011)], the authors proposed a simple measure for network robustness under malicious attacks on nodes. Using a greedy algorithm, they found that the optimal structure with respect to this quantity is an onion structure in which high-degree nodes form a core surrounded by rings of nodes with decreasing degree. However, in real networks the failure can also occur in links such as dysfunctional power cables and blocked airlines. Accordingly, complementary to the node-robustness measurement (Rn), we propose a link-robustness index (Rl). We show that solely enhancing Rn cannot guarantee the improvement of Rl. Moreover, the structure of an Rl-optimized network is found to be entirely different from that of an onion network. In order to design robust networks that are resistant to a more realistic attack condition, we propose a hybrid greedy algorithm that takes both the Rn and Rl into account. We validate the robustness of our generated networks against malicious attacks mixed with both nodes and links failure. Finally, some economical constraints for swapping the links in real networks are considered, and significant improvement in both aspects of robustness is still achieved.

  14. Robust fuzzy mappings for QSAR studies.

    PubMed

    Kumar, Mohit; Thurow, Kerstin; Stoll, Norbert; Stoll, Regina

    2007-05-01

    This study presents a new robust method of developing quantitative structure-activity relationship (QSAR) models based on fuzzy mappings. An important issue in QSAR modelling is of robustness, i.e., model should not undergo overtraining and model performance should be least sensitive to the modelling errors associated with the chosen descriptors and structure of the model. We establish robust input-output mappings for QSAR studies based on fuzzy "if-then" rules. The identification of these mappings (i.e. the construction of fuzzy rules) is based on a robust criterion that the maximum possible value of energy-gain from modelling errors to the identification errors is minimum. The robustness of proposed approach has been illustrated with simulation studies and QSAR modelling examples. The method of robust fuzzy mappings has been compared with Bayesian regularized neural networks through the QSAR modelling examples of (1) carboquinones' data set, (2) benzodiazepine data set, and (3) predicting the rate constant for hydroxyl radical tropospheric degradation of 460 heterogeneous organic compounds.

  15. Enhancing network robustness against malicious attacks.

    PubMed

    Zeng, An; Liu, Weiping

    2012-06-01

    In a recent work [Schneider et al., Proc. Natl. Acad. Sci. USA 108, 3838 (2011)], the authors proposed a simple measure for network robustness under malicious attacks on nodes. Using a greedy algorithm, they found that the optimal structure with respect to this quantity is an onion structure in which high-degree nodes form a core surrounded by rings of nodes with decreasing degree. However, in real networks the failure can also occur in links such as dysfunctional power cables and blocked airlines. Accordingly, complementary to the node-robustness measurement (R(n)), we propose a link-robustness index (R(l)). We show that solely enhancing R(n) cannot guarantee the improvement of R(l). Moreover, the structure of an R(l)-optimized network is found to be entirely different from that of an onion network. In order to design robust networks that are resistant to a more realistic attack condition, we propose a hybrid greedy algorithm that takes both the R(n) and R(l) into account. We validate the robustness of our generated networks against malicious attacks mixed with both nodes and links failure. Finally, some economical constraints for swapping the links in real networks are considered, and significant improvement in both aspects of robustness is still achieved.

  16. Enhancing network robustness against malicious attacks.

    PubMed

    Zeng, An; Liu, Weiping

    2012-06-01

    In a recent work [Schneider et al., Proc. Natl. Acad. Sci. USA 108, 3838 (2011)], the authors proposed a simple measure for network robustness under malicious attacks on nodes. Using a greedy algorithm, they found that the optimal structure with respect to this quantity is an onion structure in which high-degree nodes form a core surrounded by rings of nodes with decreasing degree. However, in real networks the failure can also occur in links such as dysfunctional power cables and blocked airlines. Accordingly, complementary to the node-robustness measurement (R(n)), we propose a link-robustness index (R(l)). We show that solely enhancing R(n) cannot guarantee the improvement of R(l). Moreover, the structure of an R(l)-optimized network is found to be entirely different from that of an onion network. In order to design robust networks that are resistant to a more realistic attack condition, we propose a hybrid greedy algorithm that takes both the R(n) and R(l) into account. We validate the robustness of our generated networks against malicious attacks mixed with both nodes and links failure. Finally, some economical constraints for swapping the links in real networks are considered, and significant improvement in both aspects of robustness is still achieved. PMID:23005185

  17. Transient absolute robustness in stochastic biochemical networks.

    PubMed

    Enciso, German A

    2016-08-01

    Absolute robustness allows biochemical networks to sustain a consistent steady-state output in the face of protein concentration variability from cell to cell. This property is structural and can be determined from the topology of the network alone regardless of rate parameters. An important question regarding these systems is the effect of discrete biochemical noise in the dynamical behaviour. In this paper, a variable freezing technique is developed to show that under mild hypotheses the corresponding stochastic system has a transiently robust behaviour. Specifically, after finite time the distribution of the output approximates a Poisson distribution, centred around the deterministic mean. The approximation becomes increasingly accurate, and it holds for increasingly long finite times, as the total protein concentrations grow to infinity. In particular, the stochastic system retains a transient, absolutely robust behaviour corresponding to the deterministic case. This result contrasts with the long-term dynamics of the stochastic system, which eventually must undergo an extinction event that eliminates robustness and is completely different from the deterministic dynamics. The transiently robust behaviour may be sufficient to carry out many forms of robust signal transduction and cellular decision-making in cellular organisms. PMID:27581485

  18. Robust electromagnetic absorption by graphene/polymer heterostructures.

    PubMed

    Lobet, Michaël; Reckinger, Nicolas; Henrard, Luc; Lambin, Philippe

    2015-07-17

    Polymer/graphene heterostructures present good shielding efficiency against GHz electromagnetic perturbations. Theory and experiments demonstrate that there is an optimum number of graphene planes, separated by thin polymer spacers, leading to maximum absorption for millimeter waves Batrakov et al (2014 Sci. Rep. 4 7191). Here, electrodynamics of ideal polymer/graphene multilayered material is first approached with a well-adapted continued-fraction formalism. In a second stage, rigorous coupled wave analysis is used to account for the presence of defects in graphene that are typical of samples produced by chemical vapor deposition, namely microscopic holes, microscopic dots (embryos of a second layer) and grain boundaries. It is shown that the optimum absorbance of graphene/polymer multilayers does not weaken to the first order in defect concentration. This finding testifies to the robustness of the shielding efficiency of the proposed absorption device. PMID:26112385

  19. Robust electromagnetic absorption by graphene/polymer heterostructures

    NASA Astrophysics Data System (ADS)

    Lobet, Michaël; Reckinger, Nicolas; Henrard, Luc; Lambin, Philippe

    2015-07-01

    Polymer/graphene heterostructures present good shielding efficiency against GHz electromagnetic perturbations. Theory and experiments demonstrate that there is an optimum number of graphene planes, separated by thin polymer spacers, leading to maximum absorption for millimeter waves Batrakov et al (2014 Sci. Rep. 4 7191). Here, electrodynamics of ideal polymer/graphene multilayered material is first approached with a well-adapted continued-fraction formalism. In a second stage, rigorous coupled wave analysis is used to account for the presence of defects in graphene that are typical of samples produced by chemical vapor deposition, namely microscopic holes, microscopic dots (embryos of a second layer) and grain boundaries. It is shown that the optimum absorbance of graphene/polymer multilayers does not weaken to the first order in defect concentration. This finding testifies to the robustness of the shielding efficiency of the proposed absorption device.

  20. Robust negative impacts of climate change on African agriculture

    NASA Astrophysics Data System (ADS)

    Schlenker, Wolfram; Lobell, David B.

    2010-01-01

    There is widespread interest in the impacts of climate change on agriculture in Sub-Saharan Africa (SSA), and on the most effective investments to assist adaptation to these changes, yet the scientific basis for estimating production risks and prioritizing investments has been quite limited. Here we show that by combining historical crop production and weather data into a panel analysis, a robust model of yield response to climate change emerges for several key African crops. By mid-century, the mean estimates of aggregate production changes in SSA under our preferred model specification are - 22, - 17, - 17, - 18, and - 8% for maize, sorghum, millet, groundnut, and cassava, respectively. In all cases except cassava, there is a 95% probability that damages exceed 7%, and a 5% probability that they exceed 27%. Moreover, countries with the highest average yields have the largest projected yield losses, suggesting that well-fertilized modern seed varieties are more susceptible to heat related losses.

  1. Fast and robust recognition and localization of 2D objects

    NASA Astrophysics Data System (ADS)

    Otterbach, Rainer; Gerdes, Rolf; Kammueller, R.

    1994-11-01

    The paper presents a vision system which provides a robust model-based identification and localization of 2-D objects in industrial scenes. A symbolic image description based on the polygonal approximation of the object silhouettes is extracted in video real time by the use of dedicated hardware. Candidate objects are selected from the model database using a time and memory efficient hashing algorithm. Any candidate object is submitted to the next computation stage which generates pose hypotheses by assigning model to image contours. Corresponding continuous measures of similarity are derived from the turning functions of the curves. Finally, the previous generated hypotheses are verified using a voting scheme in transformation space. Experimental results reveal the fault tolerance of the vision system with regard to noisy and split image contours as well as partial occlusion of objects. THe short cycle time and the easy adaptability of the vision system make it well suited for a wide variety of applications in industrial automation.

  2. Robust geostatistical analysis of spatial data

    NASA Astrophysics Data System (ADS)

    Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

    2013-04-01

    Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R

  3. Infinite impulse response modal filtering in visible adaptive optics

    NASA Astrophysics Data System (ADS)

    Agapito, G.; Arcidiacono, C.; Quirós-Pacheco, F.; Puglisi, A.; Esposito, S.

    2012-07-01

    Diffraction limited resolution adaptive optics (AO) correction in visible wavelengths requires a high performance control. In this paper we investigate infinite impulse response filters that optimize the wavefront correction: we tested these algorithms through full numerical simulations of a single-conjugate AO system comprising an adaptive secondary mirror with 1127 actuators and a pyramid wavefront sensor (WFS). The actual practicability of the algorithms depends on both robustness and knowledge of the real system: errors in the system model may even worsen the performance. In particular we checked the robustness of the algorithms in different conditions, proving that the proposed method can reject both disturbance and calibration errors.

  4. Certification Considerations for Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

    2015-01-01

    Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

  5. Adaptive Image Denoising by Mixture Adaptation

    NASA Astrophysics Data System (ADS)

    Luo, Enming; Chan, Stanley H.; Nguyen, Truong Q.

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the Expectation-Maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad-hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper: First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. Experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.

  6. Robust system for human airway-tree segmentation

    NASA Astrophysics Data System (ADS)

    Graham, Michael W.; Gibbs, Jason D.; Higgins, William E.

    2008-03-01

    Robust and accurate segmentation of the human airway tree from multi-detector computed-tomography (MDCT) chest scans is vital for many pulmonary-imaging applications. As modern MDCT scanners can detect hundreds of airway tree branches, manual segmentation and semi-automatic segmentation requiring significant user intervention are impractical for producing a full global segmentation. Fully-automated methods, however, may fail to extract small peripheral airways. We propose an automatic algorithm that searches the entire lung volume for airway branches and poses segmentation as a global graph-theoretic optimization problem. The algorithm has shown strong performance on 23 human MDCT chest scans acquired by a variety of scanners and reconstruction kernels. Visual comparisons with adaptive region-growing results and quantitative comparisons with manually-defined trees indicate a high sensitivity to peripheral airways and a low false-positive rate. In addition, we propose a suite of interactive segmentation tools for cleaning and extending critical areas of the automatically segmented result. These interactive tools have potential application for image-based guidance of bronchoscopy to the periphery, where small, terminal branches can be important visual landmarks. Together, the automatic segmentation algorithm and interactive tool suite comprise a robust system for human airway-tree segmentation.

  7. Pathological bases for a robust application of cancer molecular classification.

    PubMed

    Diaz-Cano, Salvador J

    2015-01-01

    Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification) and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes), and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors. PMID:25898411

  8. Robust Feedback Control of Flow Induced Structural Radiation of Sound

    NASA Technical Reports Server (NTRS)

    Heatwole, Craig M.; Bernhard, Robert J.; Franchek, Matthew A.

    1997-01-01

    A significant component of the interior noise of aircraft and automobiles is a result of turbulent boundary layer excitation of the vehicular structure. In this work, active robust feedback control of the noise due to this non-predictable excitation is investigated. Both an analytical model and experimental investigations are used to determine the characteristics of the flow induced structural sound radiation problem. The problem is shown to be broadband in nature with large system uncertainties associated with the various operating conditions. Furthermore the delay associated with sound propagation is shown to restrict the use of microphone feedback. The state of the art control methodologies, IL synthesis and adaptive feedback control, are evaluated and shown to have limited success for solving this problem. A robust frequency domain controller design methodology is developed for the problem of sound radiated from turbulent flow driven plates. The control design methodology uses frequency domain sequential loop shaping techniques. System uncertainty, sound pressure level reduction performance, and actuator constraints are included in the design process. Using this design method, phase lag was added using non-minimum phase zeros such that the beneficial plant dynamics could be used. This general control approach has application to lightly damped vibration and sound radiation problems where there are high bandwidth control objectives requiring a low controller DC gain and controller order.

  9. Robust algebraic image enhancement for intelligent control systems

    NASA Technical Reports Server (NTRS)

    Lerner, Bao-Ting; Morrelli, Michael

    1993-01-01

    Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

  10. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

    PubMed Central

    Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

    2016-01-01

    Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

  11. A Generalized Cauchy Distribution Framework for Problems Requiring Robust Behavior

    NASA Astrophysics Data System (ADS)

    Carrillo, Rafael E.; Aysal, Tuncer C.; Barner, Kenneth E.

    2010-12-01

    Statistical modeling is at the heart of many engineering problems. The importance of statistical modeling emanates not only from the desire to accurately characterize stochastic events, but also from the fact that distributions are the central models utilized to derive sample processing theories and methods. The generalized Cauchy distribution (GCD) family has a closed-form pdf expression across the whole family as well as algebraic tails, which makes it suitable for modeling many real-life impulsive processes. This paper develops a GCD theory-based approach that allows challenging problems to be formulated in a robust fashion. Notably, the proposed framework subsumes generalized Gaussian distribution (GGD) family-based developments, thereby guaranteeing performance improvements over traditional GCD-based problem formulation techniques. This robust framework can be adapted to a variety of applications in signal processing. As examples, we formulate four practical applications under this framework: (1) filtering for power line communications, (2) estimation in sensor networks with noisy channels, (3) reconstruction methods for compressed sensing, and (4) fuzzy clustering.

  12. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

    PubMed Central

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

  13. Robust disturbance rejection control of a biped robotic system using high-order extended state observer.

    PubMed

    Martínez-Fonseca, Nadhynee; Castañeda, Luis Ángel; Uranga, Agustín; Luviano-Juárez, Alberto; Chairez, Isaac

    2016-05-01

    This study addressed the problem of robust control of a biped robot based on disturbance estimation. Active disturbance rejection control was the paradigm used for controlling the biped robot by direct active estimation. A robust controller was developed to implement disturbance cancelation based on a linear extended state observer of high gain class. A robust high-gain scheme was proposed for developing a state estimator of the biped robot despite poor knowledge of the plant and the presence of uncertainties. The estimated states provided by the state estimator were used to implement a feedback controller that was effective in actively rejecting the perturbations as well as forcing the trajectory tracking error to within a small vicinity of the origin. The theoretical convergence of the tracking error was proven using the Lyapunov theory. The controller was implemented by numerical simulations that showed the convergence of the tracking error. A comparison with a high-order sliding-mode-observer-based controller confirmed the superior performance of the controller using the robust observer introduced in this study. Finally, the proposed controller was implemented on an actual biped robot using an embedded hardware-in-the-loop strategy.

  14. Robust disturbance rejection control of a biped robotic system using high-order extended state observer.

    PubMed

    Martínez-Fonseca, Nadhynee; Castañeda, Luis Ángel; Uranga, Agustín; Luviano-Juárez, Alberto; Chairez, Isaac

    2016-05-01

    This study addressed the problem of robust control of a biped robot based on disturbance estimation. Active disturbance rejection control was the paradigm used for controlling the biped robot by direct active estimation. A robust controller was developed to implement disturbance cancelation based on a linear extended state observer of high gain class. A robust high-gain scheme was proposed for developing a state estimator of the biped robot despite poor knowledge of the plant and the presence of uncertainties. The estimated states provided by the state estimator were used to implement a feedback controller that was effective in actively rejecting the perturbations as well as forcing the trajectory tracking error to within a small vicinity of the origin. The theoretical convergence of the tracking error was proven using the Lyapunov theory. The controller was implemented by numerical simulations that showed the convergence of the tracking error. A comparison with a high-order sliding-mode-observer-based controller confirmed the superior performance of the controller using the robust observer introduced in this study. Finally, the proposed controller was implemented on an actual biped robot using an embedded hardware-in-the-loop strategy. PMID:26928517

  15. The comparison of robust partial least squares regression with robust principal component regression on a real

    NASA Astrophysics Data System (ADS)

    Polat, Esra; Gunay, Suleyman

    2013-10-01

    One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

  16. A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

    PubMed Central

    Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

    2011-01-01

    Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

  17. A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization.

    PubMed

    Li, Zukui; Ding, Ran; Floudas, Christodoulos A

    2011-09-21

    Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented.

  18. Robust optimization of intensity modulated proton therapy

    SciTech Connect

    Liu Wei; Zhang Xiaodong; Li Yupeng; Mohan, Radhe

    2012-02-15

    Purpose: Intensity modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT optimized based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. In this paper, a method that takes the uncertainties into account during plan optimization is used to mitigate the influence of uncertainties in IMPT. Methods: The authors use the so-called ''worst-case robust optimization'' to render IMPT plans robust in the face of uncertainties. For each iteration, nine different dose distributions are computed--one each for {+-} setup uncertainties along anteroposterior (A-P), lateral (R-L) and superior-inferior (S-I) directions, for {+-} range uncertainty, and the nominal dose distribution. The worst-case dose distribution is obtained by assigning the lowest dose among the nine doses to each voxel in the clinical target volume (CTV) and the highest dose to each voxel outside the CTV. Conceptually, the use of worst-case dose distribution is similar to the dose distribution achieved based on the use of PTV in traditional planning. The objective function value for a given iteration is computed using this worst-case dose distribution. The objective function used has been extended to further constrain the target dose inhomogeneity. Results: The worst-case robust optimization method is applied to a lung case, a skull base case, and a prostate case. Compared with IMPT plans optimized using conventional methods based on the PTV, our method yields plans that are considerably less sensitive to range and setup uncertainties. An interesting finding of the work presented here is that, in addition to reducing sensitivity to uncertainties, robust optimization also leads to improved optimality of treatment plans compared to the PTV-based optimization. This is reflected in reduction in plan scores and in the lower normal tissue doses for the

  19. Precise Adaptation in Bacterial Chemotaxis through ``Assistance Neighborhoods''

    NASA Astrophysics Data System (ADS)

    Endres, Robert

    2007-03-01

    The chemotaxis network in Escherichia coli is remarkable for its sensitivity to small relative changes in the concentrations of multiple chemical signals over a broad range of ambient concentrations. Key to this sensitivity is an adaptation system that relies on methylation and demethylation (or deamidation) of specific modification sites of the chemoreceptors by the enzymes CheR and CheB, respectively. It was recently discovered that these enzymes can access five to seven receptors when tethered to a particular receptor. We show that these ``assistance neighborhoods'' (ANs) are necessary for precise and robust adaptation in a model for signaling by clusters of chemoreceptors: (1) ANs suppress fluctuations of the receptor methylation level; (2) ANs lead to robustness with respect to biochemical parameters. We predict two limits of precise adaptation at large attractant concentrations: either receptors reach full methylation and turn off, or receptors become saturated and cease to respond to attractant but retain their adapted activity.

  20. Robust Unit Commitment Considering Uncertain Demand Response

    DOE PAGES

    Liu, Guodong; Tomsovic, Kevin

    2014-09-28

    Although price responsive demand response has been widely accepted as playing an important role in the reliable and economic operation of power system, the real response from demand side can be highly uncertain due to limited understanding of consumers' response to pricing signals. To model the behavior of consumers, the price elasticity of demand has been explored and utilized in both research and real practice. However, the price elasticity of demand is not precisely known and may vary greatly with operating conditions and types of customers. To accommodate the uncertainty of demand response, alternative unit commitment methods robust to themore » uncertainty of the demand response require investigation. In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand. By optimizing the worst case under proper robust level, the unit commitment solution of the proposed model is robust against all possible realizations of the modeled uncertain demand response. Numerical simulations on the IEEE Reliability Test System show the e ectiveness of the method. Finally, compared to unit commitment with deterministic price elasticity of demand, the proposed robust model can reduce the average Locational Marginal Prices (LMPs) as well as the price volatility.« less

  1. Robust Crossfeed Design for Hovering Rotorcraft

    NASA Technical Reports Server (NTRS)

    Catapang, David R.

    1993-01-01

    Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust'. A new low-order matching method is presented here to design robust crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.

  2. On the robustness of Herlihy's hierarchy

    NASA Technical Reports Server (NTRS)

    Jayanti, Prasad

    1993-01-01

    A wait-free hierarchy maps object types to levels in Z(+) U (infinity) and has the following property: if a type T is at level N, and T' is an arbitrary type, then there is a wait-free implementation of an object of type T', for N processes, using only registers and objects of type T. The infinite hierarchy defined by Herlihy is an example of a wait-free hierarchy. A wait-free hierarchy is robust if it has the following property: if T is at level N, and S is a finite set of types belonging to levels N - 1 or lower, then there is no wait-free implementation of an object of type T, for N processes, using any number and any combination of objects belonging to the types in S. Robustness implies that there are no clever ways of combining weak shared objects to obtain stronger ones. Contrary to what many researchers believe, we prove that Herlihy's hierarchy is not robust. We then define some natural variants of Herlihy's hierarchy, which are also infinite wait-free hierarchies. With the exception of one, which is still open, these are not robust either. We conclude with the open question of whether non-trivial robust wait-free hierarchies exist.

  3. Robust Unit Commitment Considering Uncertain Demand Response

    SciTech Connect

    Liu, Guodong; Tomsovic, Kevin

    2014-09-28

    Although price responsive demand response has been widely accepted as playing an important role in the reliable and economic operation of power system, the real response from demand side can be highly uncertain due to limited understanding of consumers' response to pricing signals. To model the behavior of consumers, the price elasticity of demand has been explored and utilized in both research and real practice. However, the price elasticity of demand is not precisely known and may vary greatly with operating conditions and types of customers. To accommodate the uncertainty of demand response, alternative unit commitment methods robust to the uncertainty of the demand response require investigation. In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand. By optimizing the worst case under proper robust level, the unit commitment solution of the proposed model is robust against all possible realizations of the modeled uncertain demand response. Numerical simulations on the IEEE Reliability Test System show the e ectiveness of the method. Finally, compared to unit commitment with deterministic price elasticity of demand, the proposed robust model can reduce the average Locational Marginal Prices (LMPs) as well as the price volatility.

  4. Replication and robustness in developmental research.

    PubMed

    Duncan, Greg J; Engel, Mimi; Claessens, Amy; Dowsett, Chantelle J

    2014-11-01

    Replications and robustness checks are key elements of the scientific method and a staple in many disciplines. However, leading journals in developmental psychology rarely include explicit replications of prior research conducted by different investigators, and few require authors to establish in their articles or online appendices that their key results are robust across estimation methods, data sets, and demographic subgroups. This article makes the case for prioritizing both explicit replications and, especially, within-study robustness checks in developmental psychology. It provides evidence on variation in effect sizes in developmental studies and documents strikingly different replication and robustness-checking practices in a sample of journals in developmental psychology and a sister behavioral science-applied economics. Our goal is not to show that any one behavioral science has a monopoly on best practices, but rather to show how journals from a related discipline address vital concerns of replication and generalizability shared by all social and behavioral sciences. We provide recommendations for promoting graduate training in replication and robustness-checking methods and for editorial policies that encourage these practices. Although some of our recommendations may shift the form and substance of developmental research articles, we argue that they would generate considerable scientific benefits for the field. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  5. Robust Signal Processing in Living Cells

    PubMed Central

    Steuer, Ralf; Waldherr, Steffen; Sourjik, Victor; Kollmann, Markus

    2011-01-01

    Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations. PMID:22215991

  6. Topological plasticity increases robustness of mutualistic networks.

    PubMed

    Ramos-Jiliberto, Rodrigo; Valdovinos, Fernanda S; Moisset de Espanés, Pablo; Flores, José D

    2012-07-01

    1. Earlier studies used static models to evaluate the responses of mutualistic networks to external perturbations. Two classes of dynamics can be distinguished in ecological networks; population dynamics, represented mainly by changes in species abundances, and topological dynamics, represented by changes in the architecture of the web. 2. In this study, we model the temporal evolution of three empirical plant-pollination networks incorporating both population and topological dynamics. We test the hypothesis that topological plasticity, realized through the ability of animals to rewire their connections after depletion of host abundances, enhances tolerance of mutualistic networks to species loss. We also compared the performance of various rewiring rules in affecting robustness. 3. The results show that topological plasticity markedly increased the robustness of mutualistic networks. Our analyses also revealed that network robustness reached maximum levels when animals with less host plant availability were more likely to rewire. Also, preferential attachment to richer host plants, that is, to plants exhibiting higher abundance and few exploiters, enhances robustness more than other rewiring alternatives. 4. Our results highlight the potential role of topological plasticity in the robustness of mutualistic networks to species extinctions and suggest some plausible mechanisms by which the decisions of foragers may shape the collective dynamics of plant-pollinator systems.

  7. The topology of robustness and evolvability in evolutionary systems with genotype-phenotype map.

    PubMed

    Ibáñez-Marcelo, Esther; Alarcón, Tomás

    2014-09-01

    In this paper we formulate a topological definition of the concepts of robustness and evolvability. We start our investigation by formulating a multiscale model of the evolutionary dynamics of a population of cells. Our cells are characterised by a genotype-phenotype map: their chances of survival under selective pressure are determined by their phenotypes, whereas the latter are determined their genotypes. According to our multiscale dynamics, the population dynamics generates the evolution of a genotype-phenotype network. Our representation of the genotype-phenotype network is similar to previously described ones, but has a novel element, namely, our network contains two types of nodes: genotype and phenotype nodes. This network representation allows us to characterise robustness and evolvability in terms of its topological properties: phenotypic robustness by means of the clustering coefficient of the phenotype nodes, and evolvability as the emergence of giant connected component which allows navigation between phenotypes. This topological definition of evolvability allows us to characterise the so-called robustness of evolvability, which is defined in terms of the robustness against attack (i.e. edge removal) of the giant connected component. An investigation of the factors that affect the robustness of evolvability shows that phenotypic robustness and the cryptic genetic variation are key to the integrity of the ability to innovate. These results fit within the framework of a number of models which point out that robustness favours rather than hindering evolvability. We further show that the corresponding phenotype network, defined as the one-component projection of the whole genotype-phenotype network, exhibits the small-world phenomenon, which implies that in this type of evolutionary system the rate of adaptability is enhanced. PMID:24793533

  8. The maternal-to-zygotic transition targets actin to promote robustness during morphogenesis.

    PubMed

    Zheng, Liuliu; Sepúlveda, Leonardo A; Lua, Rhonald C; Lichtarge, Olivier; Golding, Ido; Sokac, Anna Marie

    2013-11-01

    Robustness is a property built into biological systems to ensure stereotypical outcomes despite fluctuating inputs from gene dosage, biochemical noise, and the environment. During development, robustness safeguards embryos against structural and functional defects. Yet, our understanding of how robustness is achieved in embryos is limited. While much attention has been paid to the role of gene and signaling networks in promoting robust cell fate determination, little has been done to rigorously assay how mechanical processes like morphogenesis are designed to buffer against variable conditions. Here we show that the cell shape changes that drive morphogenesis can be made robust by mechanisms targeting the actin cytoskeleton. We identified two novel members of the Vinculin/α-Catenin Superfamily that work together to promote robustness during Drosophila cellularization, the dramatic tissue-building event that generates the primary epithelium of the embryo. We find that zygotically-expressed Serendipity-α (Sry-α) and maternally-loaded Spitting Image (Spt) share a redundant, actin-regulating activity during cellularization. Spt alone is sufficient for cellularization at an optimal temperature, but both Spt plus Sry-α are required at high temperature and when actin assembly is compromised by genetic perturbation. Our results offer a clear example of how the maternal and zygotic genomes interact to promote the robustness of early developmental events. Specifically, the Spt and Sry-α collaboration is informative when it comes to genes that show both a maternal and zygotic requirement during a given morphogenetic process. For the cellularization of Drosophilids, Sry-α and its expression profile may represent a genetic adaptive trait with the sole purpose of making this extreme event more reliable. Since all morphogenesis depends on cytoskeletal remodeling, both in embryos and adults, we suggest that robustness-promoting mechanisms aimed at actin could be effective at

  9. The Maternal-to-Zygotic Transition Targets Actin to Promote Robustness during Morphogenesis

    PubMed Central

    Zheng, Liuliu; Sepúlveda, Leonardo A.; Lua, Rhonald C.; Lichtarge, Olivier; Golding, Ido; Sokac, Anna Marie

    2013-01-01

    Robustness is a property built into biological systems to ensure stereotypical outcomes despite fluctuating inputs from gene dosage, biochemical noise, and the environment. During development, robustness safeguards embryos against structural and functional defects. Yet, our understanding of how robustness is achieved in embryos is limited. While much attention has been paid to the role of gene and signaling networks in promoting robust cell fate determination, little has been done to rigorously assay how mechanical processes like morphogenesis are designed to buffer against variable conditions. Here we show that the cell shape changes that drive morphogenesis can be made robust by mechanisms targeting the actin cytoskeleton. We identified two novel members of the Vinculin/α-Catenin Superfamily that work together to promote robustness during Drosophila cellularization, the dramatic tissue-building event that generates the primary epithelium of the embryo. We find that zygotically-expressed Serendipity-α (Sry-α) and maternally-loaded Spitting Image (Spt) share a redundant, actin-regulating activity during cellularization. Spt alone is sufficient for cellularization at an optimal temperature, but both Spt plus Sry-α are required at high temperature and when actin assembly is compromised by genetic perturbation. Our results offer a clear example of how the maternal and zygotic genomes interact to promote the robustness of early developmental events. Specifically, the Spt and Sry-α collaboration is informative when it comes to genes that show both a maternal and zygotic requirement during a given morphogenetic process. For the cellularization of Drosophilids, Sry-α and its expression profile may represent a genetic adaptive trait with the sole purpose of making this extreme event more reliable. Since all morphogenesis depends on cytoskeletal remodeling, both in embryos and adults, we suggest that robustness-promoting mechanisms aimed at actin could be effective at

  10. The maternal-to-zygotic transition targets actin to promote robustness during morphogenesis.

    PubMed

    Zheng, Liuliu; Sepúlveda, Leonardo A; Lua, Rhonald C; Lichtarge, Olivier; Golding, Ido; Sokac, Anna Marie

    2013-11-01

    Robustness is a property built into biological systems to ensure stereotypical outcomes despite fluctuating inputs from gene dosage, biochemical noise, and the environment. During development, robustness safeguards embryos against structural and functional defects. Yet, our understanding of how robustness is achieved in embryos is limited. While much attention has been paid to the role of gene and signaling networks in promoting robust cell fate determination, little has been done to rigorously assay how mechanical processes like morphogenesis are designed to buffer against variable conditions. Here we show that the cell shape changes that drive morphogenesis can be made robust by mechanisms targeting the actin cytoskeleton. We identified two novel members of the Vinculin/α-Catenin Superfamily that work together to promote robustness during Drosophila cellularization, the dramatic tissue-building event that generates the primary epithelium of the embryo. We find that zygotically-expressed Serendipity-α (Sry-α) and maternally-loaded Spitting Image (Spt) share a redundant, actin-regulating activity during cellularization. Spt alone is sufficient for cellularization at an optimal temperature, but both Spt plus Sry-α are required at high temperature and when actin assembly is compromised by genetic perturbation. Our results offer a clear example of how the maternal and zygotic genomes interact to promote the robustness of early developmental events. Specifically, the Spt and Sry-α collaboration is informative when it comes to genes that show both a maternal and zygotic requirement during a given morphogenetic process. For the cellularization of Drosophilids, Sry-α and its expression profile may represent a genetic adaptive trait with the sole purpose of making this extreme event more reliable. Since all morphogenesis depends on cytoskeletal remodeling, both in embryos and adults, we suggest that robustness-promoting mechanisms aimed at actin could be effective at

  11. Robustness of reduced-order multivariable state-space self-tuning controller

    NASA Technical Reports Server (NTRS)

    Yuan, Zhuzhi; Chen, Zengqiang

    1994-01-01

    In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

  12. Robust estimation procedure in panel data model

    SciTech Connect

    Shariff, Nurul Sima Mohamad; Hamzah, Nor Aishah

    2014-06-19

    The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.

  13. Information theory perspective on network robustness

    NASA Astrophysics Data System (ADS)

    Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

    2016-01-01

    A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology.

  14. Average-cost based robust structural control

    NASA Technical Reports Server (NTRS)

    Hagood, Nesbitt W.

    1993-01-01

    A method is presented for the synthesis of robust controllers for linear time invariant structural systems with parameterized uncertainty. The method involves minimizing quantities related to the quadratic cost (H2-norm) averaged over a set of systems described by real parameters such as natural frequencies and modal residues. Bounded average cost is shown to imply stability over the set of systems. Approximations for the exact average are derived and proposed as cost functionals. The properties of these approximate average cost functionals are established. The exact average and approximate average cost functionals are used to derive dynamic controllers which can provide stability robustness. The robustness properties of these controllers are demonstrated in illustrative numerical examples and tested in a simple SISO experiment on the MIT multi-point alignment testbed.

  15. Robust tooth surface reconstruction by iterative deformation.

    PubMed

    Jiang, Xiaotong; Dai, Ning; Cheng, Xiaosheng; Wang, Jun; Peng, Qingjin; Liu, Hao; Cheng, Cheng

    2016-01-01

    Digital design technologies have been applied extensively in dental medicine, especially in the field of dental restoration. The all-ceramic crown is an important restoration type of dental CAD systems. This paper presents a robust tooth surface reconstruction algorithm for all-ceramic crown design. The algorithm involves three necessary steps: standard tooth initial positioning and division; salient feature point extraction using Morse theory; and standard tooth deformation using iterative Laplacian Surface Editing and mesh stitching. This algorithm can retain the morphological features of the tooth surface well. It is robust and suitable for almost all types of teeth, including incisor, canine, premolar, and molar. Moreover, it allows dental technicians to use their own preferred library teeth for reconstruction. The algorithm has been successfully integrated in our Dental CAD system, more than 1000 clinical cases have been tested to demonstrate the robustness and effectiveness of the proposed algorithm.

  16. An engineering viewpoint on biological robustness.

    PubMed

    Khammash, Mustafa

    2016-03-23

    In his splendid article "Can a biologist fix a radio?--or, what I learned while studying apoptosis," Y. Lazebnik argues that when one uses the right tools, similarity between a biological system, like a signal transduction pathway, and an engineered system, like a radio, may not seem so superficial. Here I advance this idea by focusing on the notion of robustness as a unifying lens through which to view complexity in biological and engineered systems. I show that electronic amplifiers and gene expression circuits share remarkable similarities in their dynamics and robustness properties. I explore robustness features and limitations in biology and engineering and highlight the role of negative feedback in shaping both.

  17. An engineering viewpoint on biological robustness.

    PubMed

    Khammash, Mustafa

    2016-01-01

    In his splendid article "Can a biologist fix a radio?--or, what I learned while studying apoptosis," Y. Lazebnik argues that when one uses the right tools, similarity between a biological system, like a signal transduction pathway, and an engineered system, like a radio, may not seem so superficial. Here I advance this idea by focusing on the notion of robustness as a unifying lens through which to view complexity in biological and engineered systems. I show that electronic amplifiers and gene expression circuits share remarkable similarities in their dynamics and robustness properties. I explore robustness features and limitations in biology and engineering and highlight the role of negative feedback in shaping both. PMID:27007299

  18. Robust visual tracking with contiguous occlusion constraint

    NASA Astrophysics Data System (ADS)

    Wang, Pengcheng; Qian, Weixian; Chen, Qian

    2016-02-01

    Visual tracking plays a fundamental role in video surveillance, robot vision and many other computer vision applications. In this paper, a robust visual tracking method that is motivated by the regularized ℓ1 tracker is proposed. We focus on investigating the case that the object target is occluded. Generally, occlusion can be treated as some kind of contiguous outlier with the target object as background. However, the penalty function of the ℓ1 tracker is not robust for relatively dense error distributed in the contiguous regions. Thus, we exploit a nonconvex penalty function and MRFs for outlier modeling, which is more probable to detect the contiguous occluded regions and recover the target appearance. For long-term tracking, a particle filter framework along with a dynamic model update mechanism is developed. Both qualitative and quantitative evaluations demonstrate a robust and precise performance.

  19. Robust fuzzy logic stabilization with disturbance elimination.

    PubMed

    Danapalasingam, Kumeresan A

    2014-01-01

    A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design. PMID:25177713

  20. Robust Fuzzy Logic Stabilization with Disturbance Elimination

    PubMed Central

    Danapalasingam, Kumeresan A.

    2014-01-01

    A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design. PMID:25177713

  1. Experimental Robust Control of Structural Acoustic Radiation

    NASA Technical Reports Server (NTRS)

    Cox, David E.; Gibbs, Gary P.; Clark, Robert L.; Vipperman, Jeffrey S.

    1998-01-01

    This work addresses the design and application of robust controllers for structural acoustic control. Both simulation and experimental results are presented. H(infinity) and mu-synthesis design methods were used to design feedback controllers which minimize power radiated from a panel while avoiding instability due to unmodeled dynamics. Specifically, high order structural modes which couple strongly to the actuator-sensor path were poorly modeled. This model error was analytically bounded with an uncertainty model, which allowed controllers to be designed without artificial limits on control effort. It is found that robust control methods provide the control designer with physically meaningful parameters with which to tune control designs and can be very useful in determining limits of performance. Experimental results also showed, however, poor robustness properties for control designs with ad-hoc uncertainty models. The importance of quantifying and bounding model errors is discussed.

  2. Robust audio hashing for audio authentication watermarking

    NASA Astrophysics Data System (ADS)

    Zmudzinski, Sascha; Steinebach, Martin

    2008-02-01

    Current systems and protocols based on cryptographic methods for integrity and authenticity verification of media data do not distinguish between legitimate signal transformation and malicious tampering that manipulates the content. Furthermore, they usually provide no localization or assessment of the relevance of such manipulations with respect to human perception or semantics. We present an algorithm for a robust message authentication code in the context of content fragile authentication watermarking to verify the integrity of audio recodings by means of robust audio fingerprinting. Experimental results show that the proposed algorithm provides both a high level of distinction between perceptually different audio data and a high robustness against signal transformations that do not change the perceived information. Furthermore, it is well suited for the integration in a content-based authentication watermarking system.

  3. Robust fuzzy logic stabilization with disturbance elimination.

    PubMed

    Danapalasingam, Kumeresan A

    2014-01-01

    A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design.

  4. Dynamical robustness of coupled heterogeneous oscillators.

    PubMed

    Tanaka, Gouhei; Morino, Kai; Daido, Hiroaki; Aihara, Kazuyuki

    2014-05-01

    We study tolerance of dynamic behavior in networks of coupled heterogeneous oscillators to deterioration of the individual oscillator components. As the deterioration proceeds with reduction in dynamic behavior of the oscillators, an order parameter evaluating the level of global oscillation decreases and then vanishes at a certain critical point. We present a method to analytically derive a general formula for this critical point and an approximate formula for the order parameter in the vicinity of the critical point in networks of coupled Stuart-Landau oscillators. Using the critical point as a measure for dynamical robustness of oscillator networks, we show that the more heterogeneous the oscillator components are, the more robust the oscillatory behavior of the network is to the component deterioration. This property is confirmed also in networks of Morris-Lecar neuron models coupled through electrical synapses. Our approach could provide a useful framework for theoretically understanding the role of population heterogeneity in robustness of biological networks.

  5. ROBUST TECHNIQUES FOR BACKGROUND SUBTRACTION IN URBAN TRAFFIC VIDEO

    SciTech Connect

    Kamath, C; Cheung, S S

    2003-10-28

    Identifying moving objects from a video sequence is a fundamental and critical task in many computer-vision applications. A common approach is to perform background subtraction, which identifies moving objects from the portion of a video frame that differs significantly from a background model. There are many challenges in developing a good background subtraction algorithm. First, it must be robust against changes in illumination. Second, it should avoid detecting non-stationary background objects such as swinging leaves, rain, snow, and shadow cast by moving objects. Finally, its internal background model should react quickly to changes in background such as starting and stopping of vehicles. In this paper, we compare various background subtraction algorithms for detecting moving vehicles and pedestrians in urban traffic video sequences. We consider approaches varying from simple techniques such as frame differencing and adaptive median filtering, to more sophisticated probabilistic modeling techniques. While complicated techniques often produce superior performance, our experiments show that simple techniques such as adaptive median filtering can produce good results with much lower computational complexity.

  6. Robust and Opportunistic Autonomous Science for a Potential Titan Aerobot

    NASA Technical Reports Server (NTRS)

    Gaines, Daniel M.; Estlin, Tara; Schaffer, Steve; Castano, Rebecca; Elfes, Alberto

    2010-01-01

    We are developing onboard planning and execution technologies to provide robust and opportunistic mission operations for a potential Titan aerobot. Aerobot have the potential for collecting a vast amount of high priority science data. However, to be effective, an aerobot must address several challenges including communication constraints, extended periods without contact with Earth, uncertain and changing environmental conditions, maneuverability constraints and potentially short-lived science opportunities. We are developing the AerOASIS system to develop and test technology to support autonomous science operations for a potential Titan Aerobot. The planning and execution component of AerOASIS is able to generate mission operations plans that achieve science and engineering objectives while respecting mission and resource constraints as well as adapting the plan to respond to new science opportunities. Our technology leverages prior work on the OASIS system for autonomous rover exploration. In this paper we describe how the OASIS planning component was adapted to address the unique challenges of a Titan Aerobot and we describe a field demonstration of the system with the JPL prototype aerobot.

  7. Competition improves robustness against loss of information.

    PubMed

    Kermani Kolankeh, Arash; Teichmann, Michael; Hamker, Fred H

    2015-01-01

    A substantial number of works have aimed at modeling the receptive field properties of the primary visual cortex (V1). Their evaluation criterion is usually the similarity of the model response properties to the recorded responses from biological organisms. However, as several algorithms were able to demonstrate some degree of similarity to biological data based on the existing criteria, we focus on the robustness against loss of information in the form of occlusions as an additional constraint for better understanding the algorithmic level of early vision in the brain. We try to investigate the influence of competition mechanisms on the robustness. Therefore, we compared four methods employing different competition mechanisms, namely, independent component analysis, non-negative matrix factorization with sparseness constraint, predictive coding/biased competition, and a Hebbian neural network with lateral inhibitory connections. Each of those methods is known to be capable of developing receptive fields comparable to those of V1 simple-cells. Since measuring the robustness of methods having simple-cell like receptive fields against occlusion is difficult, we measure the robustness using the classification accuracy on the MNIST hand written digit dataset. For this we trained all methods on the training set of the MNIST hand written digits dataset and tested them on a MNIST test set with different levels of occlusions. We observe that methods which employ competitive mechanisms have higher robustness against loss of information. Also the kind of the competition mechanisms plays an important role in robustness. Global feedback inhibition as employed in predictive coding/biased competition has an advantage compared to local lateral inhibition learned by an anti-Hebb rule.

  8. Robust control synthesis for uncertain dynamical systems

    NASA Technical Reports Server (NTRS)

    Byun, Kuk-Whan; Wie, Bong; Sunkel, John

    1989-01-01

    This paper presents robust control synthesis techniques for uncertain dynamical systems subject to structured parameter perturbation. Both QFT (quantitative feedback theory) and H-infinity control synthesis techniques are investigated. Although most H-infinity-related control techniques are not concerned with the structured parameter perturbation, a new way of incorporating the parameter uncertainty in the robust H-infinity control design is presented. A generic model of uncertain dynamical systems is used to illustrate the design methodologies investigated in this paper. It is shown that, for a certain noncolocated structural control problem, use of both techniques results in nonminimum phase compensation.

  9. Outlier robust nonlinear mixed model estimation.

    PubMed

    Williams, James D; Birch, Jeffrey B; Abdel-Salam, Abdel-Salam G

    2015-04-15

    In standard analyses of data well-modeled by a nonlinear mixed model, an aberrant observation, either within a cluster, or an entire cluster itself, can greatly distort parameter estimates and subsequent standard errors. Consequently, inferences about the parameters are misleading. This paper proposes an outlier robust method based on linearization to estimate fixed effects parameters and variance components in the nonlinear mixed model. An example is given using the four-parameter logistic model and bioassay data, comparing the robust parameter estimates with the nonrobust estimates given by SAS(®).

  10. Security analysis of robust perceptual hashing

    NASA Astrophysics Data System (ADS)

    Koval, Oleksiy; Voloshynovskiy, Sviatoslav; Beekhof, Fokko; Pun, Thierry

    2008-02-01

    In this paper we considered the problem of security analysis of robust perceptual hashing in authentication application. The main goal of our analysis was to estimate the amount of trial efforts of the attacker, who is acting within the Kerckhoffs security principle, to reveal a secret key. For this purpose, we proposed to use Shannon equivocation that provides an estimate of complexity of the key search performed based on all available prior information and presented its application to security evaluation of particular robust perceptual hashing algorithms.

  11. Robust overlay schemes for the fusion of fluorescence and color channels in biological imaging.

    PubMed

    Glatz, Jürgen; Symvoulidis, Panagiotis; Garcia-Allende, P Beatriz; Ntziachristos, Vasilis

    2014-04-01

    Molecular fluorescence imaging is a commonly used method in various biomedical fields and is undergoing rapid translation toward clinical applications. Color images are commonly superimposed with fluorescence measurements to provide orientation, anatomical information, and molecular tissue properties in a single image. New adaptive methods that produce a more robust composite image than conventional lime green alpha blending are presented and demonstrated herein. Moreover, visualization through temporal changes is showcased as an alternative for real-time imaging systems.

  12. An observer based approach for achieving fault diagnosis and fault tolerant control of systems modeled as hybrid Petri nets.

    PubMed

    Renganathan, K; Bhaskar, VidhyaCharan

    2011-07-01

    In this paper, we propose an approach for achieving detection and identification of faults, and provide fault tolerant control for systems that are modeled using timed hybrid Petri nets. For this purpose, an observer based technique is adopted which is useful in detection of faults, such as sensor faults, actuator faults, signal conditioning faults, etc. The concepts of estimation, reachability and diagnosability have been considered for analyzing faulty behaviors, and based on the detected faults, different schemes are proposed for achieving fault tolerant control using optimization techniques. These concepts are applied to a typical three tank system and numerical results are obtained.

  13. Self-adaptive Vision System

    NASA Astrophysics Data System (ADS)

    Stipancic, Tomislav; Jerbic, Bojan

    Light conditions represent an important part of every vision application. This paper describes one active behavioral scheme of one particular active vision system. This behavioral scheme enables an active system to adapt to current environmental conditions by constantly validating the amount of the reflected light using luminance meter and dynamically changed significant vision parameters. The purpose of the experiment was to determine the connections between light conditions and inner vision parameters. As a part of the experiment, Response Surface Methodology (RSM) was used to predict values of vision parameters with respect to luminance input values. RSM was used to approximate an unknown function for which only few values were computed. The main output validation system parameter is called Match Score. Match Score indicates how well the found object matches the learned model. All obtained data are stored in the local database. By timely applying new parameters predicted by the RSM, the vision application works in a stabile and robust manner.

  14. Robust design method and thermostatic experiment for multiple piezoelectric vibration absorber system

    NASA Astrophysics Data System (ADS)

    Nambu, Yohsuke; Takashima, Toshihide; Inagaki, Akiya

    2015-12-01

    This paper examines the effects of connecting multiplexing shunt circuits composed of inductors and resistors to piezoelectric transducers so as to improve the robustness of a piezoelectric vibration absorber (PVA). PVAs are well known to be effective at suppressing the vibration of an adaptive structure; their weakness is low robustness to changes in the dynamic parameters of the system, including the main structure and the absorber. In the application to space structures, the temperature-dependency of capacitance of piezoelectric ceramics is the factor that causes performance reduction. To improve robustness to the temperature-dependency of the capacitance, this paper proposes a multiple-PVA system that is composed of distributed piezoelectric transducers and several shunt circuits. The optimization problems that determine both the frequencies and the damping ratios of the PVAs are multi-objective problems, which are solved using a real-coded genetic algorithm in this paper. A clamped aluminum beam with four groups of piezoelectric ceramics attached was considered in simulations and experiments. Numerical simulations revealed that the PVA systems designed using the proposed method had tolerance to changes in the capacitances. Furthermore, experiments using a thermostatic bath were conducted to reveal the effectiveness and robustness of the PVA systems. The maximum peaks of the transfer functions of the beam with the open circuit, the single-PVA system, the double-PVA system, and the quadruple-PVA system at 20 °C were 14.3 dB, -6.91 dB, -7.47 dB, and -8.51 dB, respectively. The experimental results also showed that the multiple-PVA system is more robust than a single PVA in a variable temperature environment from -10 °C to 50 °C. In conclusion, the use of multiple PVAs results in an effective, robust vibration control method for adaptive structures.

  15. Genetic algorithms in adaptive fuzzy control

    NASA Technical Reports Server (NTRS)

    Karr, C. Lucas; Harper, Tony R.

    1992-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

  16. Reference Device-Assisted Adaptive Location Fingerprinting

    PubMed Central

    Wu, Dongjin; Xia, Linyuan

    2016-01-01

    Location fingerprinting suffers in dynamic environments and needs recalibration from time to time to maintain system performance. This paper proposes an adaptive approach for location fingerprinting. Based on real-time received signal strength indicator (RSSI) samples measured by a group of reference devices, the approach applies a modified Universal Kriging (UK) interpolant to estimate adaptive temporal and environmental radio maps. The modified UK can take the spatial distribution characteristics of RSSI into account. In addition, the issue of device heterogeneity caused by multiple reference devices is further addressed. To compensate the measuring differences of heterogeneous reference devices, differential RSSI metric is employed. Extensive experiments were conducted in an indoor field and the results demonstrate that the proposed approach not only adapts to dynamic environments and the situation of changing APs’ positions, but it is also robust toward measuring differences of heterogeneous reference devices. PMID:27258284

  17. Robust stabilization, robust performance, and disturbance attenuation for uncertain linear systems

    NASA Technical Reports Server (NTRS)

    Wang, Yeih J.; Shieh, Leang S.; Sunkel, John W.

    1992-01-01

    This paper presents a linear quadratic regulator approach to the robust stabilization, robust performance, and disturbance attenuation of uncertain linear systems. The state-feedback designed systems provide both the robust stability with optimal performance and the disturbance attenuation with H-infinity-norm bounds. The proposed approach can be applied to matched and/or mismatched uncertain linear systems. For a matched uncertain linear system, it is shown that the disturbance attenuation robust-stabilizing controllers with or without optimal performance always exist and can be easily determined without searching; whereas, for a mismatched uncertain linear system, the introduced tuning parameters greatly enhance the flexibility of finding the disturbance-attenuation robust-stabilizing controllers.

  18. Global Climate Change Adaptation Priorities for Biodiversity and Food Security

    PubMed Central

    Hannah, Lee; Ikegami, Makihiko; Hole, David G.; Seo, Changwan; Butchart, Stuart H. M.; Peterson, A. Townsend; Roehrdanz, Patrick R.

    2013-01-01

    International policy is placing increasing emphasis on adaptation to climate change, including the allocation of new funds to assist adaptation efforts. Climate change adaptation funding may be most effective where it meets integrated goals, but global geographic priorities based on multiple development and ecological criteria are not well characterized. Here we show that human and natural adaptation needs related to maintaining agricultural productivity and ecosystem integrity intersect in ten major areas globally, providing a coherent set of international priorities for adaptation funding. An additional seven regional areas are identified as worthy of additional study. The priority areas are locations where changes in crop suitability affecting impoverished farmers intersect with changes in ranges of restricted-range species. Agreement among multiple climate models and emissions scenarios suggests that these priorities are robust. Adaptation funding directed to these areas could simultaneously address multiple international policy goals, including poverty reduction, protecting agricultural production and safeguarding ecosystem services. PMID:23991125

  19. Global climate change adaptation priorities for biodiversity and food security.

    PubMed

    Hannah, Lee; Ikegami, Makihiko; Hole, David G; Seo, Changwan; Butchart, Stuart H M; Peterson, A Townsend; Roehrdanz, Patrick R

    2013-01-01

    International policy is placing increasing emphasis on adaptation to climate change, including the allocation of new funds to assist adaptation efforts. Climate change adaptation funding may be most effective where it meets integrated goals, but global geographic priorities based on multiple development and ecological criteria are not well characterized. Here we show that human and natural adaptation needs related to maintaining agricultural productivity and ecosystem integrity intersect in ten major areas globally, providing a coherent set of international priorities for adaptation funding. An additional seven regional areas are identified as worthy of additional study. The priority areas are locations where changes in crop suitability affecting impoverished farmers intersect with changes in ranges of restricted-range species. Agreement among multiple climate models and emissions scenarios suggests that these priorities are robust. Adaptation funding directed to these areas could simultaneously address multiple international policy goals, including poverty reduction, protecting agricultural production and safeguarding ecosystem services.

  20. Adaptive Peer Sampling with Newscast

    NASA Astrophysics Data System (ADS)

    Tölgyesi, Norbert; Jelasity, Márk

    The peer sampling service is a middleware service that provides random samples from a large decentralized network to support gossip-based applications such as multicast, data aggregation and overlay topology management. Lightweight gossip-based implementations of the peer sampling service have been shown to provide good quality random sampling while also being extremely robust to many failure scenarios, including node churn and catastrophic failure. We identify two problems with these approaches. The first problem is related to message drop failures: if a node experiences a higher-than-average message drop rate then the probability of sampling this node in the network will decrease. The second problem is that the application layer at different nodes might request random samples at very different rates which can result in very poor random sampling especially at nodes with high request rates. We propose solutions for both problems. We focus on Newscast, a robust implementation of the peer sampling service. Our solution is based on simple extensions of the protocol and an adaptive self-control mechanism for its parameters, namely—without involving failure detectors—nodes passively monitor local protocol events using them as feedback for a local control loop for self-tuning the protocol parameters. The proposed solution is evaluated by simulation experiments.