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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. Robust Adaptive Control

    NASA Technical Reports Server (NTRS)

    Narendra, K. S.; Annaswamy, A. M.

    1985-01-01

    Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.

  3. Observer-based robust-H-infinity control laws for uncertain linear systems

    NASA Technical Reports Server (NTRS)

    Shieh, Leang S.; Sunkel, J. W.; Wang, Yeih J.

    1991-01-01

    Based on the algebraic Riccati equation approach, this paper presents a simple and flexible method for designing observer-based robust-H-infinity control laws for linear systems with structured parameter uncertainty. The observer-based robust-H-infinity output-feedback control law, obtained by solving three augmented algebraic Riccati equations, provides both robust stability and disturbance attenuation with H-infinity-norm bound for the closed-loop uncertain linear system. Several tuning parameters are embedded into the augmented algebraic Riccati equations so that flexibility in finding the symmetric positive-definite solutions (and hence, the robust-H-infinity control laws) is significantly increased. A benchmark problem associated with a mass-spring system, which approximates the dynamics of a flexible structure, is used to illustrate the design methodologies, and simulation results are presented.

  4. Observer-based robust control of one-sided Lipschitz nonlinear systems.

    PubMed

    Ahmad, Sohaira; Rehan, Muhammad; Hong, Keum-Shik

    2016-11-01

    This paper presents an observer-based controller design for the class of nonlinear systems with time-varying parametric uncertainties and norm-bounded disturbances. The design methodology, for the less conservative one-sided Lipschitz nonlinear systems, involves astute utilization of Young's inequality and several matrix decompositions. A sufficient condition for simultaneous extraction of observer and controller gains is stipulated by a numerically tractable set of convex optimization conditions. The constraints are handled by a nonlinear iterative cone-complementary linearization method in obtaining gain matrices. Further, an observer-based control technique for one-sided Lipschitz nonlinear systems, robust against L2-norm-bounded perturbations, is contrived. The proposed methodology ensures robustness against parametric uncertainties and external perturbations. Simulation examples demonstrating the effectiveness of the proposed methodologies are presented.

  5. Robust, Adaptive Radar Detection and Estimation

    DTIC Science & Technology

    2015-07-21

    AFRL-OSR-VA-TR-2015-0208 Robust, Adaptive Radar Detection and Estimation Vishal Monga PENNSYLVANIA STATE UNIVERSITY THE Final Report 07/21/2015...Robust, Adaptive Radar Detection and Estimation 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1-0333 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Monga...we develop robust estimators that can adapt to imperfect knowledge of physical constraints using an expected likelihood (EL) approach. We analyze

  6. Robustness of reduced-order observer-based controllers in transitional 2D Blasius boundary layers

    NASA Astrophysics Data System (ADS)

    Belson, Brandt; Semeraro, Onofrio; Rowley, Clarence; Pralits, Jan; Henningson, Dan

    2011-11-01

    In this work, we seek to delay transition in the Blasius boundary layer. We trip the flow with an upstream disturbance and dampen the growth of the resulting structures downstream. The observer-based controllers use a single sensor and a single localized body force near the wall. To formulate the controllers, we first find a reduced-order model of the system via the Eigensystem Realization Algorithm (ERA), then find the H2 optimal controller for this reduced-order system. We find the resulting controllers are effective only when the sensor is upstream of the actuator (in a feedforward configuration), but as is expected, are sensitive to model uncertainty. When the sensor is downstream of the actuator (in a feedback configuration), the reduced-order observer-based controllers are not robust and ineffective on the full system. In order to investigate the robustness properties of the system, an iterative technique called the adjoint of the direct adjoint (ADA) is employed to find a full-dimensional H2 optimal controller. This avoids the reduced-order modelling step and serves as a reference point. ADA is promising for investigating the lack of robustness previously mentioned.

  7. Robust H∞ observer-based control for synchronization of a class of complex dynamical networks

    NASA Astrophysics Data System (ADS)

    Zheng, Hai-Qing; Jing, Yuan-Wei

    2011-06-01

    This paper is concerned with the robust H∞ synchronization problem for a class of complex dynamical networks by applying the observer-based control. The proposed feedback control scheme is developed to ensure the asymptotic stability of the augmented system, to reconstruct the non-measurable state variables of each node and to improve the H∞ performance related to the synchronization error and observation error despite the external disturbance. Based on the Lyapunov stability theory, a synchronization criterion is obtained under which the controlled network can be robustly stabilized onto a desired state with a guaranteed H∞ performance. The controller and the observer gains can be given by the feasible solutions of a set of linear matrix inequalities (LMIs). The effectiveness of the proposed control scheme is demonstrated by a numerical example through simulation.

  8. Extended observer based on adaptive second order sliding mode control for a fixed wing UAV.

    PubMed

    Castañeda, Herman; Salas-Peña, Oscar S; León-Morales, Jesús de

    2017-01-01

    This paper addresses the design of attitude and airspeed controllers for a fixed wing unmanned aerial vehicle. An adaptive second order sliding mode control is proposed for improving performance under different operating conditions and is robust in presence of external disturbances. Moreover, this control does not require the knowledge of disturbance bounds and avoids overestimation of the control gains. Furthermore, in order to implement this controller, an extended observer is designed to estimate unmeasurable states as well as external disturbances. Additionally, sufficient conditions are given to guarantee the closed-loop stability of the observer based control. Finally, using a full 6 degree of freedom model, simulation results are obtained where the performance of the proposed method is compared against active disturbance rejection based on sliding mode control.

  9. Robust adaptive beamforming for MIMO monopulse radar

    NASA Astrophysics Data System (ADS)

    Rowe, William; Ström, Marie; Li, Jian; Stoica, Petre

    2013-05-01

    Researchers have recently proposed a widely separated multiple-input multiple-output (MIMO) radar using monopulse angle estimation techniques for target tracking. The widely separated antennas provide improved tracking performance by mitigating complex target radar cross-section fades and angle scintillation. An adaptive array is necessary in this paradigm because the direct path from any transmitter could act as a jammer at a receiver. When the target-free covariance matrix is not available, it is critical to include robustness into the adaptive beamformer weights. This work explores methods of robust adaptive monopulse beamforming techniques for MIMO tracking radar.

  10. 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.

  11. Robust Adaptive Control of Hypnosis During Anesthesia

    DTIC Science & Technology

    2007-11-02

    1 of 4 ROBUST ADAPTIVE CONTROL OF HYPNOSIS DURING ANESTHESIA Pascal Grieder1, Andrea Gentilini1, Manfred Morari1, Thomas W. Schnider2 1ETH Zentrum...A closed-loop controller for hypnosis was designed and validated on humans at our laboratory. The controller aims at regulat- ing the Bispectral Index...BIS) - a surro- gate measure of hypnosis derived from the electroencephalogram of the patient - with the volatile anesthetic isoflurane administered

  12. 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.

  13. Real Time & Power Efficient Adaptive - Robust Control

    NASA Astrophysics Data System (ADS)

    Ioan Gliga, Lavinius; Constantin Mihai, Cosmin; Lupu, Ciprian; Popescu, Dumitru

    2017-01-01

    A design procedure for a control system suited for dynamic variable processes is presented in this paper. The proposed adaptive - robust control strategy considers both adaptive control advantages and robust control benefits. It estimates the degradation of the system’s performances due to the dynamic variation in the process and it then utilizes it to determine when the system must be adapted with a redesign of the robust controller. A single integral criterion is used for the identification of the process, and for the design of the control algorithm, which is expressed in direct form, through a cost function defined in the space of the parameters of both the process and the controller. For the minimization of this nonlinear function, an adequate mathematical programming minimization method is used. The theoretical approach presented in this paper was validated for a closed loop control system, simulated in an application developed in C. Because of the reduced number of operations, this method is suitable for implementation on fast processes. Due to its effectiveness, it increases the idle time of the CPU, thereby saving electrical energy.

  14. 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.

  15. Non-monotonic robust H2 fuzzy observer-based control for discrete time nonlinear systems with parametric uncertainties

    NASA Astrophysics Data System (ADS)

    Fakhimi Derakhshan, Siavash; Fatehi, Alireza

    2015-09-01

    A non-monotonic Lyapunov function (NMLF) is deployed to design a robust H2 fuzzy observer-based control problem for discrete-time nonlinear systems in the presence of parametric uncertainties. The uncertain nonlinear system is presented as a Takagi and Sugeno (T-S) fuzzy model with norm-bounded uncertainties. The states of the fuzzy system are estimated by a fuzzy observer and the control design is established based on a parallel distributed compensation scheme. In order to derive a sufficient condition to establish the global asymptotic stability of the proposed closed-loop fuzzy system, an NMLF is adopted and an upper bound on the quadratic cost function is provided. The existence of a robust H2 fuzzy observer-based controller is expressed as a sufficient condition in the form of linear matrix inequalities (LMIs) and a sub-optimal fuzzy observer-based controller in the sense of cost bound minimization is obtained by utilising the aforementioned LMI optimisation techniques. Finally, the effectiveness of the proposed scheme is shown through an example.

  16. Sliding mode disturbance observer-based adaptive integral backstepping control of a piezoelectric nano-manipulator

    NASA Astrophysics Data System (ADS)

    Zhang, Yangming; Yan, Peng

    2016-12-01

    This paper investigates a systematic modeling and control methodology for a multi-axis PZT (piezoelectric transducer) actuated servo stage supporting nano-manipulations. A sliding mode disturbance observer-based adaptive integral backstepping control method with an estimated inverse model compensation scheme is proposed to achieve ultra high precision tracking in the presence of the hysteresis nonlinearities, model uncertainties, and external disturbances. By introducing a time rate of the input signal, an enhanced rate-dependent Prandtl-Ishlinskii model is developed to describe the hysteresis behaviors, and its inverse is also constructed to mitigate their adverse effects. In particular, the corresponding inverse compensation error is analyzed and its boundedness is proven. Subsequently, the sliding mode disturbance observer-based adaptive integral backstepping controller is designed to guarantee the convergence of the tracking error, where the sliding mode disturbance observer can track the total disturbances in a finite time, while the integral action is incorporated into the adaptive backstepping design to improve the steady-state control accuracy. Finally, real time implementations of the proposed algorithm are applied on the PZT actuated servo system, where excellent tracking performance with tracking precision error around 6‰ for circular contour tracking is achieved in the experimental results.

  17. Direct discrete-time design approach to robust ? sampled-data observer-based output-feedback fuzzy control

    NASA Astrophysics Data System (ADS)

    Kim, Do Wan; Lee, Ho Jae

    2016-01-01

    This paper addresses a direct discrete-time design methodology for a robust ? sampled-data observer-based output-feedback stabilisation problem for a class of non-linear systems suffering from parametric uncertainties and disturbances that is identically modelled as a Takagi-Sugeno (T-S) fuzzy model at least locally. The primary features in the current development are that (1) we are based on an exact (rather than approximate) discrete-time model in an integral (rather than closed) form while (2) the ? control performance is characterised with respect to an ? (rather than l2) norm. It is shown that the uncertain sampled-data non-linear control system is robustly asymptotically stable if the employed discrete-time model is so. Design conditions are investigated in the discrete-time Lyapunov sense and concretised in the format of linear matrix inequalities.

  18. Robust observer-based passive control for uncertain singular time-delay systems subject to actuator saturation.

    PubMed

    Ma, Yuechao; Yang, Pingjing; Yan, Yifang; Zhang, Qingling

    2017-03-01

    This paper investigates the problem of robust observer-based passive control for uncertain singular time-delay system subject to actuator saturation. A polytopic approach is used to describe the saturation behavior. First, by constructing Lyapunov-Krasovskii functional, a less conservative sufficient condition is obtained which guarantees that the closed-loop system is regular, impulse free, stable and robust strictly passive. Then, with this condition, the design method of state feedback controller and the observer are given by solving linear matrix inequalities. In addition, a domain of attraction in which the admissible initial states are ensured to converge asymptotically to the origin is solved as a convex optimization problem. Finally, some simulations are provided to demonstrate the effectiveness and superiority of the proposed method.

  19. 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.

  20. A disturbance observer-based adaptive control approach for flexure beam nano manipulators.

    PubMed

    Zhang, Yangming; Yan, Peng; Zhang, Zhen

    2016-01-01

    This paper presents a systematic modeling and control methodology for a two-dimensional flexure beam-based servo stage supporting micro/nano manipulations. Compared with conventional mechatronic systems, such systems have major control challenges including cross-axis coupling, dynamical uncertainties, as well as input saturations, which may have adverse effects on system performance unless effectively eliminated. A novel disturbance observer-based adaptive backstepping-like control approach is developed for high precision servo manipulation purposes, which effectively accommodates model uncertainties and coupling dynamics. An auxiliary system is also introduced, on top of the proposed control scheme, to compensate the input saturations. The proposed control architecture is deployed on a customized-designed nano manipulating system featured with a flexure beam structure and voice coil actuators (VCA). Real time experiments on various manipulating tasks, such as trajectory/contour tracking, demonstrate precision errors of less than 1%.

  1. Robust sigma-delta generalised proportional integral observer based control of a `buck' converter with uncertain loads

    NASA Astrophysics Data System (ADS)

    Sira-Ramírez, Hebertt; Núñez, Ciro A.; Visairo, Nancy

    2010-08-01

    This article describes the design of an observer based robust linear output feedback controller for the regulation and output reference trajectory tracking tasks in switched 'buck' converter circuits feeding a completely unknown time-varying load. The state-dependent perturbation effects of the unknown load resistance are on-line estimated by means of a generalised proportional integral (GPI) observer, which represents the dual counterpart of GPI controllers introduced in Fliess, Márquez, Delaleau and Sira-Ramírez (Fliess, M., Márquez, R., Delaleau, E., and Sira-Ramírez, H. (2002), 'Correcteurs Proportionnels-intégraux Géneralisés', ESAIM: Control, Optimisation and Calculus of Variations, 7, 23-41). The reconstructed perturbation complements the controller in a cancellation effort which allows the core of the feedback controller to become a traditional proportional derivative (PD) controller. The designed average feedback controller is then implemented via a sigma-delta-modulator, which effectively translates the designed continuous average feedback control input signal into a discrete valued switched input signal driving the converter's input switch and preserving all relevant features of the average design. The Appendix collects some generalities about GPI observers.

  2. Robustness of Adaptive Testing to Multidimensionality.

    ERIC Educational Resources Information Center

    Weiss, David J.; Suhadolnik, Debra

    The present monte carlo simulation study was designed to examine the effects of multidimensionality during the administration of computerized adaptive testing (CAT). It was assumed that multidimensionality existed in the individuals to whom test items were being administered, i.e., that the correct or incorrect responses given by an individual…

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Adaptive integral robust control and application to electromechanical servo systems.

    PubMed

    Deng, Wenxiang; Yao, Jianyong

    2017-03-01

    This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers.

  8. 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.

  9. Robust adaptive kinematic control of redundant robots

    NASA Technical Reports Server (NTRS)

    Tarokh, M.; Zuck, D. D.

    1992-01-01

    The paper presents a general method for the resolution of redundancy that combines the Jacobian pseudoinverse and augmentation approaches. A direct adaptive control scheme is developed to generate joint angle trajectories for achieving desired end-effector motion as well as additional user defined tasks. The scheme ensures arbitrarily small errors between the desired and the actual motion of the manipulator. Explicit bounds on the errors are established that are directly related to the mismatch between actual and estimated pseudoinverse Jacobian matrix, motion velocity and the controller gain. It is shown that the scheme is tolerant of the mismatch and consequently only infrequent pseudoinverse computations are needed during a typical robot motion. As a result, the scheme is computationally fast, and can be implemented for real-time control of redundant robots. A method is incorporated to cope with the robot singularities allowing the manipulator to get very close or even pass through a singularity while maintaining a good tracking performance and acceptable joint velocities. Computer simulations and experimental results are provided in support of the theoretical developments.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Disturbance observer based active and adaptive synchronization of energy resource chaotic system.

    PubMed

    Wei, Wei; Wang, Meng; Li, Donghai; Zuo, Min; Wang, Xiaoyi

    2016-11-01

    In this paper, synchronization of a three-dimensional energy resource chaotic system is considered. For the sake of achieving the synchronization between the drive and response systems, two different nonlinear control approaches, i.e. active control with known parameters and adaptive control with unknown parameters, have been designed. In order to guarantee the transient performance, finite-time boundedness (FTB) and finite-time stability (FTS) are introduced in the design of active control and adaptive control, respectively. Simultaneously, in view of the existence of disturbances, a new disturbance observer is proposed to estimate the disturbance. The conditions of the asymptotic stability for the closed-loop system are obtained. Numerical simulations are provided to illustrate the proposed approaches.

  15. Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

    PubMed

    Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

    2017-03-01

    A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies.

  16. 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

  17. Adaptive and robust radiation therapy in the presence of drift

    NASA Astrophysics Data System (ADS)

    Mar, Philip Allen; Chan, Timothy C. Y.

    2015-05-01

    Combining adaptive and robust optimization in radiation therapy has the potential to mitigate the negative effects of both intrafraction and interfraction uncertainty over a fractionated treatment course. A previously developed adaptive and robust radiation therapy (ARRT) method for lung cancer was demonstrated to be effective when the sequence of breathing patterns was well-behaved. In this paper, we examine the applicability of the ARRT method to less well-behaved breathing patterns. We develop a novel method to generate sequences of probability mass functions that represent different types of drift in the underlying breathing pattern. Computational results derived from applying the ARRT method to these sequences demonstrate that the ARRT method is effective for a much broader class of breathing patterns than previously demonstrated.

  18. 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.

  19. 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.

  20. Robustness of channel-adapted quantum error correction

    SciTech Connect

    Ballo, Gabor; Gurin, Peter

    2009-07-15

    A quantum channel models the interaction between the system we are interested in and its environment. Such a model can capture the main features of the interaction, but, because of the complexity of the environment, we cannot assume that it is fully accurate. We study the robustness of quantum error correction operations against completely unexpected and subsequently undetermined type of channel uncertainties. We find that a channel-adapted optimal error correction operation does not only give the best possible channel fidelity but it is more robust against channel alterations than any other error correction operation. Our results are valid for Pauli channels and stabilizer codes, but based on some numerical results, we believe that very similar conclusions can be drawn also in the general case.

  1. A decentralized adaptive robust method for chaos control.

    PubMed

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-09-01

    This paper presents a control strategy, which is based on sliding mode control, adaptive control, and fuzzy logic system for controlling the chaotic dynamics. We consider this control paradigm in chaotic systems where the equations of motion are not known. The proposed control strategy is robust against the external noise disturbance and system parameter variations and can be used to convert the chaotic orbits not only to the desired periodic ones but also to any desired chaotic motions. Simulation results of controlling some typical higher order chaotic systems demonstrate the effectiveness of the proposed control method.

  2. Robust visual tracking via adaptive kernelized correlation filter

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Wang, Desheng; Liao, Qingmin

    2016-10-01

    Correlation filter based trackers have proved to be very efficient and robust in object tracking with a notable performance competitive with state-of-art trackers. In this paper, we propose a novel object tracking method named Adaptive Kernelized Correlation Filter (AKCF) via incorporating Kernelized Correlation Filter (KCF) with Structured Output Support Vector Machines (SOSVM) learning method in a collaborative and adaptive way, which can effectively handle severe object appearance changes with low computational cost. AKCF works by dynamically adjusting the learning rate of KCF and reversely verifies the intermediate tracking result by adopting online SOSVM classifier. Meanwhile, we bring Color Names in this formulation to effectively boost the performance owing to its rich feature information encoded. Experimental results on several challenging benchmark datasets reveal that our approach outperforms numerous state-of-art trackers.

  3. Robust adaptive backstepping control for piezoelectric nano-manipulating systems

    NASA Astrophysics Data System (ADS)

    Zhang, Yangming; Yan, Peng; Zhang, Zhen

    2017-01-01

    In this paper we present a systematic modeling and control approach for nano-manipulations of a two-dimensional PZT (piezoelectric transducer) actuated servo stage. The major control challenges associated with piezoelectric nano-manipulators typically include the nonlinear dynamics of hysteresis, model uncertainties, and various disturbances. The adverse effects of these complications will result in significant performance loss, unless effectively eliminated. The primary goal of the paper is on the ultra high precision control of such systems by handling various model uncertainties and disturbances simultaneously. To this end, a novel robust adaptive backstepping-like control approach is developed such that parametric uncertainties can be estimated adaptively while the nonlinear dynamics and external disturbances are treated as bounded disturbances for robust elimination. Meanwhile, the L2-gain of the closed-loop system is considered, and an H∞ optimization problem is formulated to improve the tracking accuracy. Numerical simulations and real time experiments are finally conducted, which significantly outperform conventional PID methods and achieve around 1% tracking error for circular contouring tasks.

  4. 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.

  5. Robust adaptive cruise control of high speed trains.

    PubMed

    Faieghi, Mohammadreza; Jalali, Aliakbar; Mashhadi, Seyed Kamal-e-ddin Mousavi

    2014-03-01

    The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations.

  6. 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.

  7. 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.

  8. A robust adaptive load frequency control for micro-grids.

    PubMed

    Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede; Davari, Pooya; Dragicevic, Tomislav

    2016-11-01

    The goal of this study is to introduce a novel robust load frequency control (LFC) strategy for micro-grid(s) (MG(s)) in islanded mode operation. Admittedly, power generators in MG(s) cannot supply steady electric power output and sometimes cause unbalance between supply and demand. Battery energy storage system (BESS) is one of the effective solutions to these problems. Due to the high cost of the BESS, a new idea of Vehicle-to-Grid (V2G) is that a battery of Electric-Vehicle (EV) can be applied as a tantamount large-scale BESS in MG(s). As a result, a new robust control strategy for an islanded micro-grid (MG) is introduced that can consider electric vehicles׳ (EV(s)) effect. Moreover, in this paper, a new combination of the General Type II Fuzzy Logic Sets (GT2FLS) and the Modified Harmony Search Algorithm (MHSA) technique is applied for adaptive tuning of proportional-integral (PI) controller. Implementing General Type II Fuzzy Systems is computationally expensive. However, using a recently introduced α-plane representation, GT2FLS can be seen as a composition of several Interval Type II Fuzzy Logic Systems (IT2FLS) with a corresponding level of α for each. Real-data from an offshore wind farm in Sweden and solar radiation data in Aberdeen (United Kingdom) was used in order to examine the performance of the proposed novel controller. A comparison is made between the achieved results of Optimal Fuzzy-PI (OFPI) controller and those of Optimal Interval Type II Fuzzy-PI (IT2FPI) controller, which are of most recent advances in the area at hand. The Simulation results prove the successfulness and effectiveness of the proposed controller.

  9. 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.

  10. Investigation of Adaptive Robust Kalman Filtering Algorithms for GPS/DR Navigation System Filters

    NASA Astrophysics Data System (ADS)

    Elzoghby, MOSTAFA; Arif, USMAN; Li, FU; Zhi Yu, XI

    2017-03-01

    The conventional Kalman filter (KF) algorithm is suitable if the characteristic noise covariance for states as well as measurements is readily known but in most cases these are unknown. Similarly robustness is required instead of smoothing if states are changing abruptly. Such an adaptive as well as robust Kalman filter is vital for many real time applications, like target tracking and navigating aerial vehicles. A number of adaptive as well as robust Kalman filtering methods are available in the literature. In order to investigate the performance of some of these methods, we have selected three different Kalman filters, namely Sage Husa KF, Modified Adaptive Robust KF and Adaptively Robust KF, which are easily simulate able as well as implementable for real time applications. These methods are simulated for land based vehicle and the results are compared with conventional Kalman filter. Results show that the Modified Adaptive Robust KF is best amongst the selected methods and can be used for Navigation applications.

  11. 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.

  12. 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.

  13. Robust adaptive digital watermark for still images using hybrid modulation

    NASA Astrophysics Data System (ADS)

    Alturki, Faisal T.; Mersereau, Russell M.

    2001-08-01

    A digital watermark is a short sequence of information containing an owner identity or copyright information embedded in a way that is difficult to erase. We present a new oblivious digital watermarking technique for copyright protection of still images. The technique embeds the watermark in a subset of low to mid frequency coefficients. A key is used to randomly select a group of coefficients from that subset for watermark embedding. The original phases of the selected coefficients are removed and the new phases are set in accordance with the embedded watermark. Since the coefficients are selected at random, the powers of the low magnitude coefficients are increased to enhance their immunity against image attacks. To cope with small geometric attacks, a replica of the watermark is embedded by dividing the image into sub-blocks and taking the DCT of these blocks. The watermark is embedded in the DC component of some of these blocks selected in an adaptive way using quantization techniques. A major advantage of this technique is its complete suppression of the noise due to the host image. The robustness of the technique to a number of standard image processing attacks is demonstrated using the criteria of the latest Stirmark benchmark test.

  14. Robust online tracking via adaptive samples selection with saliency detection

    NASA Astrophysics Data System (ADS)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

    Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

  15. 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.

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

    PubMed

    Egbert, Matthew D; Pérez-Mercader, Juan

    2016-01-08

    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.

  17. 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

  18. 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.

  19. Adaptive Introspection and Deployment for Robust Long Duration Autonomy

    DTIC Science & Technology

    2014-09-30

    Duration Autonomy Nathan Michael, Sebastian Scherer Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA, 15213-3890 phone: (412) 268...7816 fax: (412) 268-1338 email: nmichael@cmu.edu, scherer@cmu.edu Award Number: N000141310821 LONG-TERM GOALS Long duration autonomy ...integrative experimental framework toward evaluating the approaches developed through the first two tasks. Task 1: Introspection for Robust Autonomy

  20. 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.

  1. BOLD subjective value signals exhibit robust range adaptation.

    PubMed

    Cox, Karin M; Kable, Joseph W

    2014-12-03

    Many theories of decision making assume that choice options are assessed along a common subjective value (SV) scale. The neural correlates of SV are widespread and reliable, despite the wide variation in the range of values over which decisions are made (e.g., between goods worth a few dollars, in some cases, or hundreds of dollars, in others). According to adaptive coding theories (Barlow, 1961), an efficient value signal should exhibit range adaptation, such that neural activity maintains a fixed dynamic range, and the slope of the value response varies inversely with the range of values within the local context. Although monkey data have demonstrated range adaptation in single-unit correlates of value (Padoa-Schioppa, 2009; Kobayashi et al., 2010), whether BOLD value signals exhibit similar range adaptation is unknown. To test for this possibility, we presented human participants with choices between a fixed immediate and variable delayed payment options. Across two conditions, the delayed options' SVs spanned either a narrow or wide range. SV-tracking activity emerged in the posterior cingulate, ventral striatum, anterior cingulate, and ventromedial prefrontal cortex. Throughout this network, we observed evidence consistent with the predictions of range adaptation: the SV response slope increased in the narrow versus wide range, with statistically significant slope changes confirmed for the posterior cingulate and ventral striatum. No regions exhibited a reliably increased BOLD activity range in the wide versus narrow condition. Our observations of range adaptation present implications for the interpretation of BOLD SV responses that are measured across different contexts or individuals.

  2. Extended-state-observer-based adaptive control for synchronisation of multi-agent systems with unknown nonlinearities

    NASA Astrophysics Data System (ADS)

    Yang, Hongjiu; You, Xiu; Liu, Zhixin; Sun, Fuchun

    2015-10-01

    This paper studies the problem of synchronisation to a desired trajectory for non-linear multi-agent systems. By introducing extended state observer approach, decentralised adaptive controllers are designed for distributed systems which have non-identical unknown non-linear dynamics. The non-identical unknown non-linear dynamics allows for a tracked command dynamics which is also non-linear and unknown. State variables of agents can be obtained only in the case where leader agent and the network communication topology for multi-agent systems is strongly connected digraph network structures. A Lyapunov-function-based approach is given to show that the tracking error is ultimately bounded. Some simulation results are given to demonstrate the effectiveness of the developed techniques in this paper.

  3. 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.

  4. 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.

  5. Robust speech perception: recognize the familiar, generalize to the similar, and adapt to the novel.

    PubMed

    Kleinschmidt, Dave F; Jaeger, T Florian

    2015-04-01

    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 nonstationary world and propose that the speech perception system overcomes this challenge by (a) recognizing previously encountered situations, (b) generalizing to other situations based on previous similar experience, and (c) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (a) to (c) 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 2 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 that listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these 2 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.

  6. 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.

  7. 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.

  8. Robust adaptive synchronization of Rossler and Chen chaotic systems via slide technique

    NASA Astrophysics Data System (ADS)

    Li, Zhi; Shi, Songjiao

    2003-05-01

    This Letter considers the robust adaptive synchronization problem of Rossler and Chen chaotic systems with different time-varying unknown parameters. When system's unknown parameters vary in bound intervals and the bounds of intervals are unknown, a robust adaptive controller is designed. In order to increase the robustness of the closed loop systems, the key idea is that a sliding mode type of controller is employed. Besides, instead of the estimate values of systems' unknown parameters being taken as updating object, a new updating object is introduced in constructing controller. The proposed controller can make the states of Rossler and Chen chaotic systems globally asymptotically robustly synchronized. Simulation results are given to show the effectiveness of the proposed method.

  9. 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

  10. 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.

  11. Robust adaptive self-structuring fuzzy control design for nonaffine, nonlinear systems

    NASA Astrophysics Data System (ADS)

    Chen, Pin-Cheng; Wang, Chi-Hsu; Lee, Tsu-Tian

    2011-01-01

    In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L 2 tracking performance to stabilise the closed-loop system. This L 2 tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.

  12. A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

    NASA Astrophysics Data System (ADS)

    Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

    2015-04-01

    This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation.

  13. Robust adaptive neural network control of uncertain nonholonomic systems with strong nonlinear drifts.

    PubMed

    Wang, Z P; Ge, S S; Lee, T H

    2004-10-01

    In this paper, robust adaptive neural network (NN) control is presented to solve the control problem of nonholonomic systems in chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive NN control laws are developed using state scaling and backstepping. Uniform ultimate boundedness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neighborhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. The proposed adaptive NN control is free of control singularity problem. An adaptive control based switching strategy is used to overcome the uncontrollability problem associated with x0 (t0) = 0. The simulation results demonstrate the effectiveness of the proposed controllers.

  14. Distributed robust adaptive control for a class of dynamical complex networks against imperfect communications

    NASA Astrophysics Data System (ADS)

    Jin, Xiao-Zheng; Yang, Guang-Hong

    2011-03-01

    In this article, a robust tracking control problem of a class of dynamical complex networks is presented through a distributed adaptive approach. Uncertain network topology with unknown coupling strength, delayed and perturbed communications and external disturbances are considered, while the bounds of channel noises and coupling delays and disturbances are assumed to be unknown. Adaptation laws are proposed to estimate the network coupling strength and the upper and lower bounds of communication state errors and disturbances on-line. Based on the information from adaptive schemes, a class of distributed robust adaptive controllers is constructed to automatically compensate for the imperfect network and disturbance effects. Then, according to the Lyapunov stability theory, it is shown that the achievement of tracking for complex networks is effective on imperfect communications and disturbances. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of an F-18 aircraft.

  15. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands

    NASA Astrophysics Data System (ADS)

    Haasnoot, M.; Schellekens, J.; Beersma, J. J.; Middelkoop, H.; Kwadijk, J. C. J.

    2015-10-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for local or regional decision making on climate adaptation are static ‘endpoint’ projections. This paper describes the development and use of transient (time-dependent) scenarios by means of a case on water management in the Netherlands. Relevant boundary conditions (sea level, precipitation and evaporation) were constructed by generating an ensemble of synthetic time-series with a rainfall generator and a transient delta change method. Climate change impacted river flows were then generated with a hydrological simulation model for the Rhine basin. The transient scenarios were applied in model simulations and game experiments. We argue that there are at least three important assets of using transient scenarios for supporting robust climate adaptation: (1) raise awareness about (a) the implications of climate variability and climate change for decision making and (b) the difficulty of finding proof of climate change in relevant variables for water management; (2) assessment of when to adapt by identifying adaptation tipping points which can then be used to explore adaptation pathways, and (3) identification of triggers for climate adaptation.

  16. Adaptive Denoising Technique for Robust Analysis of Functional Magnetic Resonance Imaging Data

    DTIC Science & Technology

    2007-11-02

    or receive while t fMRI o versatil of epoc method ER-fM to the studies comes intra-su functioADAPTIVE DENOISING TECHNIQUE FOR ROBUST ANALYSIS OF...supported in part by the Center for Advanced Software and Biomedical Engineering Consultations (CASBEC), Cairo University, and IBE Technologies , Egypt

  17. Adaptive resolution simulation of liquid para-hydrogen: testing the robustness of the quantum-classical adaptive coupling.

    PubMed

    Poma, A B; Delle Site, L

    2011-06-14

    Adaptive resolution simulations for classical systems are currently made within a reasonably consistent theoretical framework. Recently we have extended this approach to the quantum-classical coupling by mapping the quantum nature of an atom onto a classical polymer ring representation within the path integral approach [Poma & Delle Site, Phys. Rev. Lett., 2010, 104, 250201]. In this way the process of interfacing adaptively a quantum representation to a classical one corresponds to the problem of interfacing two regions with a different number of effective "classical" degrees of freedom; thus the classical formulation of the adaptive algorithm applies straightforwardly to the quantum-classical problem. In this work we show the robustness of such an approach for a liquid of para-hydrogen at low temperature. This system represents a highly challenging conceptual and technical test for the adaptive approach due to the extreme thermodynamical conditions where quantum effects play a central role.

  18. 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

  19. Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

    PubMed

    Chen, Tien-Chi; Yu, Chih-Hsien

    2009-07-01

    A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

  20. Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.

    PubMed

    Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng

    2016-07-01

    In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.

  1. Adaptive integral LOS path following for an unmanned airship with uncertainties based on robust RBFNN backstepping.

    PubMed

    Zheng, Zewei; Zou, Yao

    2016-11-01

    This paper investigates the path following control problem for an unmanned airship in the presence of unknown wind and uncertainties. The backstepping technique augmented by a robust adaptive radial basis function neural network (RBFNN) is employed as the main control framework. Based on the horizontal dynamic model of the airship, an improved adaptive integral line-of-sight (LOS) guidance law is first proposed, which suits any parametric paths. The guidance law calculates the desired yaw angle and estimates the wind. Then the controller is extended to cope with the airship yaw tracking and velocity control by resorting to the augmented backstepping technique. The uncertainties of the dynamics are compensated by using the robust RBFNNs. Each robust RBFNN utilizes an nth-order smooth switching function to combine a conventional RBFNN with a robust control. The conventional RBFNN dominates in the neural active region, while the robust control retrieves the transient outside the active region, so that the stability range can be widened. Stability analysis shows that the controlled closed-loop system is globally uniformly ultimately bounded. Simulations are provided to validate the effectiveness of the proposed control approach.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    PubMed

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used.

  7. Guidance and adaptive-robust attitude & orbit control of a small information satellite

    NASA Astrophysics Data System (ADS)

    Somov, Ye.; Butyrin, S.; Somov, S.; Somova, T.; Testoyedov, N.; Rayevsky, V.; Titov, G.; Yakimov, Ye.; Ovchinnikov, A.; Mathylenko, M.

    2017-01-01

    We consider a small information satellite which may be placed on an orbit with altitude from 600 up to 1000 km. The satellite attitude and orbit control system contains a strap-down inertial navigation system, cluster of four reaction wheels, magnetic driver and a correcting engine unit with eight electro-reaction engines. We study problems on design of algorithms for spatial guidance, in-flight identification and adaptive-robust control of the satellite motion on sun-synchronous orbit.

  8. Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

    NASA Technical Reports Server (NTRS)

    Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.

    1985-01-01

    This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

  9. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    NASA Technical Reports Server (NTRS)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

  10. 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.

  11. Assistance using adaptive oscillators: robustness to errors in the identification of the limb parameters.

    PubMed

    Rinderknecht, Mike Domenik; Delaloye, Fabien André; Crespi, Alessandro; Ronsse, Renaud; Ijspeert, Auke Jan

    2011-01-01

    This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.

  12. Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector

    NASA Astrophysics Data System (ADS)

    Wang, Chuntao; Ni, Jiangqun; Zhang, Rongyue; Kwon, Goo-Rak; Ko, Sung-Jea

    Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.

  13. 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

  14. 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

  15. 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

  16. Adaptive robust motion/force control of holonomic-constrained nonholonomic mobile manipulators.

    PubMed

    Li, Zhijun; Ge, Shuzhi Sam; Ming, Aiguo

    2007-06-01

    In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance and the bounded constraint force. Simulation results validate that the motion of the system converges to the desired trajectory, and the constraint force converges to the desired force.

  17. Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise.

    PubMed

    Smithson, Michael; Ben-Haim, Yakov

    2015-10-01

    Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam.

  18. Defense planning for the Post-Cold War Era. Giving Meaning to Flexibility, Adaptiveness, and Robustness of Capability

    DTIC Science & Technology

    1993-01-01

    care was guaranteed. Family policies helped to sup- port child care. Most importantly, it became extremely difficult to terminate employees for...management value seen in adaptiveness, flexibilty , and processes robustness of capabilities. Increasing flexibility Decentralization to CINCs where

  19. 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.

  20. Robust respiration rate estimation using adaptive Kalman filtering with textile ECG sensor and accelerometer.

    PubMed

    Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Koizumi, Hiroshi; Ogasawara, Takayuki; Tajima, Takuro; Kasahara, Ryoichi; Lepine, Nicholas N

    2016-08-01

    An adaptive Kalman filter-based fusion algorithm capable of estimating respiration rate for unobtrusive respiratory monitoring is proposed. Using both signal characteristics and a priori information, the Kalman filter is adaptively optimized to improve accuracy. Furthermore, the system is able to combine the respiration-related signals extracted from a textile ECG sensor and an accelerometer to create a single robust measurement. We measured derived respiratory rates and, when compared to a reference, found root-mean-square error of 2.11 breaths-per-minute (BrPM) while lying down, 2.30 BrPM while sitting, 5.97 BrPM while walking, and 5.98 BrPM while running. These results demonstrate that the proposed system is applicable to unobtrusive monitoring for various applications.

  1. 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

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

    PubMed

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

    2016-07-05

    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.

  3. Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

    PubMed

    Piatrou, Piotr; Gilles, Luc

    2005-02-20

    Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Robust Scale Adaptive Tracking by Combining Correlation Filters with Sequential Monte Carlo

    PubMed Central

    Ma, Junkai; Luo, Haibo; Hui, Bin; Chang, Zheng

    2017-01-01

    A robust and efficient object tracking algorithm is required in a variety of computer vision applications. Although various modern trackers have impressive performance, some challenges such as occlusion and target scale variation are still intractable, especially in the complex scenarios. This paper proposes a robust scale adaptive tracking algorithm to predict target scale by a sequential Monte Carlo method and determine the target location by the correlation filter simultaneously. By analyzing the response map of the target region, the completeness of the target can be measured by the peak-to-sidelobe rate (PSR), i.e., the lower the PSR, the more likely the target is being occluded. A strict template update strategy is designed to accommodate the appearance change and avoid template corruption. If the occlusion occurs, a retained scheme is allowed and the tracker refrains from drifting away. Additionally, the feature integration is incorporated to guarantee the robustness of the proposed approach. The experimental results show that our method outperforms other state-of-the-art trackers in terms of both the distance precision and overlap precision on the publicly available TB-50 dataset. PMID:28273840

  10. Robust Impacts of Climate Change in Europe and Why Study Scale is Important for Adaptation

    NASA Astrophysics Data System (ADS)

    Donnelly, C.; Andersson, J.; Olsson, J.; Bosshard, T.; Yang, W.; Berg, P.; Arheimer, B.

    2015-12-01

    Impacts of climate change on water resources in Europe have been studied using multiple climate, hydrological and downscaling models and at multiple scales. Although results seem to differ largely between these studies, robust qualitative results have emerged at the European scale. Generally, a drying trend coupled with more intense extremes (floods & droughts) is observed in southern Europe, whereas a wetting trend coupled with less intense extremes is observed in Northern Europe. The location of the change between wetting and drying leads to uncertainty of climate change impacts in central Europe. Also, temperature-related hydrological processes lead to more robust predictions than precipitation-related processes as climate models are more consistent for temperature. For European hydrology, this leads to more robust predictions in regions with snow-dominated hydrology and where evapotranspiration dominates the water cycle. Robust predictions of changes to the seasonality of discharge are seen in snow-dominated regions (Fennoscandinavia, Alps) while robust predictions of decreases in runoff are seen for the Iberian peninsula. While uncertainty in the projections mostly comes from climate uncertainty, predictions of impacts on soil moisture and low flows can be largely dependent on the choice of hydrological model where methods to estimate evapotranspiration and runoff differ widely. While the regional-scale results show some robustness, there can be large local-scale differences even where the same catchment is considered at different scales. Furthermore, understanding of uncertainties due to correction and downscaling procedures are only beginning to emerge. Our evaluations of bias-correction indicate that uncertainties vary considerably depending on the variable. The scale of uncertainty due to bias-correction can be similar to the projected climate changes and to the uncertainty from the climate models. In this presentation we put forward a new bottom-up method

  11. 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.

  12. 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.

  13. 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.

  14. Adaptive robust synchronization of Rossler systems in the presence of unknown matched time-varying parameters

    NASA Astrophysics Data System (ADS)

    Arefi, M. M.; Jahed-Motlagh, M. R.

    2010-12-01

    This paper deals with the problem of adaptive robust synchronization of chaotic systems based on the Lyapunov theory. A controller is designed for a feedback linearizable error system with matched uncertainties. The proposed method shows that the drive and response systems are synchronized and states of the response system track the states of the drive system as time tends to infinity. Since this approach does not require any information about the bound of uncertainties, this information is not needed in advance. In order to prevent the frequent switching phenomenon in the control signal, the method is modified such that the norm of tracking error is bounded. Numerical simulations on two uncertain Rossler systems with matched uncertainties show fast responses of tracking error, while the errors are Uniformly Ultimately Bounded, and the control signal is reasonably smooth.

  15. 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.

  16. 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.

  17. 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.

  18. Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

    NASA Astrophysics Data System (ADS)

    Kesrarat, Darun; Patanavijit, Vorapoj

    2017-02-01

    In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

  19. Flight control design using a blend of modern nonlinear adaptive and robust techniques

    NASA Astrophysics Data System (ADS)

    Yang, Xiaolong

    In this dissertation, the modern control techniques of feedback linearization, mu synthesis, and neural network based adaptation are used to design novel control laws for two specific applications: F/A-18 flight control and reusable launch vehicle (an X-33 derivative) entry guidance. For both applications, the performance of the controllers is assessed. As a part of a NASA Dryden program to develop and flight test experimental controllers for an F/A-18 aircraft, a novel method of combining mu synthesis and feedback linearization is developed to design longitudinal and lateral-directional controllers. First of all, the open-loop and closed-loop dynamics of F/A-18 are investigated. The production F/A-18 controller as well as the control distribution mechanism are studied. The open-loop and closed-loop handling qualities of the F/A-18 are evaluated using low order transfer functions. Based on this information, a blend of robust mu synthesis and feedback linearization is used to design controllers for a low dynamic pressure envelope of flight conditions. For both the longitudinal and the lateral-directional axes, a robust linear controller is designed for a trim point in the center of the envelope. Then by including terms to cancel kinematic nonlinearities and variations in the aerodynamic forces and moments over the flight envelope, a complete nonlinear controller is developed. In addition, to compensate for the model uncertainty, linearization error and variations between operating points, neural network based adaptation is added to the designed longitudinal controller. The nonlinear simulations, robustness and handling qualities analysis indicate that the performance is similar to or better than that for the production F/A-18 controllers. When the dynamic pressure is very low, the performance of both the experimental and the production flight controllers is degraded, but Level I handling qualities are still achieved. A new generation of Reusable Launch Vehicles

  20. Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.

    PubMed

    Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

    2017-04-06

    An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

  1. An adaptive and robust biological network based on the vacant-particle transportation model.

    PubMed

    Gunji, Yukio-Pegio; Shirakawa, Tomohiro; Niizato, Takayuki; Yamachiyo, Masaki; Tani, Iori

    2011-03-07

    A living system reveals local computing by referring to a whole system beyond the exploration-exploitation dilemma. The slime mold, Physarum polycephalum, uses protoplasmic flow to change its own outer shape, which yields the boundary condition and forms an adaptive and robust network. This observation suggests that the whole Physarum can be represented as a local protoplasmic flow system. Here, we show that a system composed of particles, which move and are modified based upon the particle transformation that contains the relationship between the parts and the whole, can emulate the network formed by Physarum. This system balances the exploration-exploitation trade-off and shows a scale-free sub-domain. By decreasing the number of particles, our model, VP-S, can emulate the Physarum adaptive network as it is attracted to a food stimulus. By increasing the number of particles, our model, VP-D, can emulate the pattern of a growing Physarum. The patterns produced by our model were compared with those of the Physarum pattern quantitatively, which showed that both patterns balance exploration with exploitation. This model should have a wide applicability to study biological collective phenomena in general.

  2. 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.

  3. Adaptive tracking of discriminative frequency components in electroencephalograms for a robust brain-computer interface

    NASA Astrophysics Data System (ADS)

    Thomas, Kavitha P.; Guan, Cuntai; Tong Lau, Chiew; Vinod, A. P.; Keng Ang, Kai

    2011-06-01

    In an electroencephalogram (EEG)-based brain-computer interface (BCI), motor imagery has been successfully used as a communication strategy. Motor imagery causes detectable amplitude changes in certain frequency bands of EEGs, which are dubbed event-related desynchronization\\synchronization. The frequency components that give effective discrimination between different types of motor imagery are subject specific and identification of these subject-specific discriminative frequency components (DFCs) is important for the accurate classification of motor imagery activities. In this paper, we propose a new method to estimate the DFC using the Fisher criterion and investigate the variability of these DFCs over multiple sessions of EEG recording. Observing the variability of DFC over sessions in the analysis, a new BCI approach called the Adaptively Weighted Spectral-Spatial Patterns (AWSSP) algorithm is proposed. AWSSP tracks the variation in DFC over time adaptively based on the deviation of discriminative weight values of frequency components. The classification performance of the proposed AWSSP is compared with a static BCI approach that employs fixed DFCs. In the offline and online experiments, AWSSP offers better classification performance than the static approach, emphasizing the significance of tracking the variability of DFCs in EEGs for developing robust motor imagery-based BCI systems. A study of the effect of feedback on the variation in DFCs is also performed in online experiments and it is found that the presence of visual feedback results in increased variation in DFCs.

  4. Robust Adaptive Beamforming Based on Low-Rank and Cross-Correlation Techniques

    NASA Astrophysics Data System (ADS)

    Ruan, Hang; de Lamare, Rodrigo C.

    2016-08-01

    This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. Firstly, we construct a general linear equation considered in large dimensions whose solution yields the steering vector mismatch. Then, we employ the idea of the full orthogonalization method (FOM), an orthogonal Krylov subspace based method, to iteratively estimate the steering vector mismatch in a reduced-dimensional subspace, resulting in the proposed orthogonal Krylov subspace projection mismatch estimation (OKSPME) method. We also devise adaptive algorithms based on stochastic gradient (SG) and conjugate gradient (CG) techniques to update the beamforming weights with low complexity and avoid any costly matrix inversion. The main advantages of the proposed low-rank and mismatch estimation techniques are their cost-effectiveness when dealing with high dimension subspaces or large sensor arrays. Simulations results show excellent performance in terms of the output signal-to-interference-plus-noise ratio (SINR) of the beamformer among all the compared RAB methods.

  5. 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.

  6. Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

    PubMed

    Zhang, Lei; Zhang, David

    2016-08-10

    We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

  7. Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

    PubMed

    Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

    2012-03-01

    Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

  8. A multi-layer robust adaptive fault tolerant control system for high performance aircraft

    NASA Astrophysics Data System (ADS)

    Huo, Ying

    Modern high-performance aircraft demand advanced fault-tolerant flight control strategies. Not only the control effector failures, but the aerodynamic type failures like wing-body damages often result in substantially deteriorate performance because of low available redundancy. As a result the remaining control actuators may yield substantially lower maneuvering capabilities which do not authorize the accomplishment of the air-craft's original specified mission. The problem is to solve the control reconfiguration on available control redundancies when the mission modification is urged to save the aircraft. The proposed robust adaptive fault-tolerant control (RAFTC) system consists of a multi-layer reconfigurable flight controller architecture. It contains three layers accounting for different types and levels of failures including sensor, actuator, and fuselage damages. In case of the nominal operation with possible minor failure(s) a standard adaptive controller stands to achieve the control allocation. This is referred to as the first layer, the controller layer. The performance adjustment is accounted for in the second layer, the reference layer, whose role is to adjust the reference model in the controller design with a degraded transit performance. The upmost mission adjust is in the third layer, the mission layer, when the original mission is not feasible with greatly restricted control capabilities. The modified mission is achieved through the optimization of the command signal which guarantees the boundedness of the closed-loop signals. The main distinguishing feature of this layer is the the mission decision property based on the current available resources. The contribution of the research is the multi-layer fault-tolerant architecture that can address the complete failure scenarios and their accommodations in realities. Moreover, the emphasis is on the mission design capabilities which may guarantee the stability of the aircraft with restricted post

  9. A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple

    NASA Astrophysics Data System (ADS)

    Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

    2016-11-01

    Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

  10. Adaptive tuning of a 2DOF controller for robust cell manipulation using IPMC actuators

    NASA Astrophysics Data System (ADS)

    McDaid, A. J.; Aw, K. C.; Haemmerle, E.; Shahinpoor, M.; Xie, S. Q.

    2011-12-01

    Rapid advancement in medicine and bioscience is causing demand for faster, more accurate and dexterous as well as safer and more reliable micro-manipulators capable of handling biological cells. Current micro-manipulation techniques commonly damage cell walls and membranes due to their stiffness and rigidity. Ionic polymer-metal composite (IPMC) actuators have inherent compliance and with their ability to operate well in fluid and cellular environments they present a unique solution for safe cell manipulation. The reason for the downfall of IPMCs is that their complex behaviour makes them hard to control precisely in unknown environments and in the presence of sizeable external disturbances. This paper presents a novel scheme for adaptively tuning IPMC actuators for precise and robust micro-manipulation of biological cells. A two-degree-of-freedom (2DOF) controller is developed to allow optimal performance for both disturbance rejection (DR) and set point (SP) tracking. These criteria are optimized using a proposed IFT algorithm which adaptively updates the controller parameters, with no model or prior knowledge of the operating conditions, to achieve a compliant manipulation system which can precisely track targets in the presence of large external disturbances, as will be encountered in real biological environments. Experiments are presented showing the performance optimization of an IPMC actuator in the presence of external mechanical disturbances as well as the optimization of the SP tracking. The IFT algorithm successfully tunes the DR and SP to an 85% and 69% improvement, respectively. Results are also presented for a one-degree-of-freedom (1DOF) controller tuned first for DR and then for SP, for a comparison with the 2DOF controller. Validation has been undertaken to verify that the 2DOF controller does indeed outperform both 1DOF controllers over a variety of operating conditions.

  11. Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.

    PubMed

    Zhang, Jiong; Dashtbozorg, Behdad; Bekkers, Erik; Pluim, Josien P W; Duits, Remco; Ter Haar Romeny, Bart M

    2016-12-01

    This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations [Formula: see text]. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain [Formula: see text], vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.

  12. Robustness and management adaptability in tropical rangelands: a viability-based assessment under the non-equilibrium paradigm.

    PubMed

    Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M

    2014-08-01

    Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

  13. 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.

  14. 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.

  15. Improving Robustness of Deep Neural Network Acoustic Models via Speech Separation and Joint Adaptive Training

    PubMed Central

    Narayanan, Arun; Wang, DeLiang

    2015-01-01

    Although deep neural network (DNN) acoustic models are known to be inherently noise robust, especially with matched training and testing data, the use of speech separation as a frontend and for deriving alternative feature representations has been shown to improve performance in challenging environments. We first present a supervised speech separation system that significantly improves automatic speech recognition (ASR) performance in realistic noise conditions. The system performs separation via ratio time-frequency masking; the ideal ratio mask (IRM) is estimated using DNNs. We then propose a framework that unifies separation and acoustic modeling via joint adaptive training. Since the modules for acoustic modeling and speech separation are implemented using DNNs, unification is done by introducing additional hidden layers with fixed weights and appropriate network architecture. On the CHiME-2 medium-large vocabulary ASR task, and with log mel spectral features as input to the acoustic model, an independently trained ratio masking frontend improves word error rates by 10.9% (relative) compared to the noisy baseline. In comparison, the jointly trained system improves performance by 14.4%. We also experiment with alternative feature representations to augment the standard log mel features, like the noise and speech estimates obtained from the separation module, and the standard feature set used for IRM estimation. Our best system obtains a word error rate of 15.4% (absolute), an improvement of 4.6 percentage points over the next best result on this corpus. PMID:26973851

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  1. Interindividual variation in functionally adapted trait sets is established during postnatal growth and predictable based on bone robustness.

    PubMed

    Pandey, Nirnimesh; Bhola, Siddharth; Goldstone, Andrew; Chen, Fred; Chrzanowski, Jessica; Terranova, Carl J; Ghillani, Richard; Jepsen, Karl J

    2009-12-01

    Adults acquire unique sets of morphological and tissue-quality bone traits that are predictable based on robustness and deterministic of strength and fragility. How and when individual trait sets arise during growth has not been established. Longitudinal structural changes of the metacarpal diaphysis were measured for boys and girls from 3 mo to 8 yr of age using hand radiographs obtained from the Bolton-Brush collection. Robustness varied approximately 2-fold among boys and girls, and individual values were established by 2 yr of age, indicating that genetic and environmental factors controlling the relationship between growth in width and growth in length were established early during postnatal growth. Significant negative correlations between robustness and relative cortical area and a significant positive correlation between robustness and a novel measure capturing the efficiency of growth indicated that coordination of the subperiosteal and endocortical surfaces was responsible for this population acquiring a narrow range of trait sets that was predictable based on robustness. Boys and girls with robust diaphyses had proportionally thinner cortices to minimize mass, whereas children with slender diaphyses had proportionally thicker cortices to maximize stiffness. Girls had more slender metacarpals with proportionally thicker cortices compared with boys at all prepubertal ages. Although postnatal growth patterns varied in fundamentally different ways with sex and robustness, the dependence of trait sets on robustness indicated that children sustained variants affecting subperiosteal growth because they shared a common biological factor regulating functional adaptation. Considering the natural variation in acquired trait sets may help identify determinants of fracture risk, because age-related bone loss and gain will affect slender and robust structures differently.

  2. Adaptive Photothermal Emission Analysis Techniques for Robust Thermal Property Measurements of Thermal Barrier Coatings

    NASA Astrophysics Data System (ADS)

    Valdes, Raymond

    The characterization of thermal barrier coating (TBC) systems is increasingly important because they enable gas turbine engines to operate at high temperatures and efficiency. Phase of photothermal emission analysis (PopTea) has been developed to analyze the thermal behavior of the ceramic top-coat of TBCs, as a nondestructive and noncontact method for measuring thermal diffusivity and thermal conductivity. Most TBC allocations are on actively-cooled high temperature turbine blades, which makes it difficult to precisely model heat transfer in the metallic subsystem. This reduces the ability of rote thermal modeling to reflect the actual physical conditions of the system and can lead to higher uncertainty in measured thermal properties. This dissertation investigates fundamental issues underpinning robust thermal property measurements that are adaptive to non-specific, complex, and evolving system characteristics using the PopTea method. A generic and adaptive subsystem PopTea thermal model was developed to account for complex geometry beyond a well-defined coating and substrate system. Without a priori knowledge of the subsystem characteristics, two different measurement techniques were implemented using the subsystem model. In the first technique, the properties of the subsystem were resolved as part of the PopTea parameter estimation algorithm; and, the second technique independently resolved the subsystem properties using a differential "bare" subsystem. The confidence in thermal properties measured using the generic subsystem model is similar to that from a standard PopTea measurement on a "well-defined" TBC system. Non-systematic bias-error on experimental observations in PopTea measurements due to generic thermal model discrepancies was also mitigated using a regression-based sensitivity analysis. The sensitivity analysis reported measurement uncertainty and was developed into a data reduction method to filter out these "erroneous" observations. It was found

  3. 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.

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

    PubMed Central

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

    2017-01-01

    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. PMID:27008349

  5. 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

  6. 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.

  7. Robust-adaptive active vibration control of alloy and flexible matrix composite rotorcraft drivelines via magnetic bearings: Theory and experiment

    NASA Astrophysics Data System (ADS)

    Desmidt, Hans A.

    This thesis explores the use of Active Magnetic Bearing (AMB) technology and newly emerging Flexible Matrix Composite (FMC) materials to advance the state-of-the-art of rotorcraft and other high performance driveline systems. Specifically, two actively controlled tailrotor driveline configurations are explored. The first driveline configuration (Configuration I) consists of a multi-segment alloy driveline connected by Non-Constant-Velocity (NCV) flexible couplings and mounted on non-contact AMB devices. The second configuration (Configuration II) consists of a single piece, rigidly coupled, FMC shaft supported by AMBs. For each driveline configuration, a novel hybrid robust-adaptive vibration control strategy is theoretically developed and experimentally validated based on the specific driveline characteristics and uncertainties. In the case of Configuration I, the control strategy is based on a hybrid design consisting of a PID feedback controller augmented with a slowly adapting, Multi-Harmonic Adaptive Vibration Control (MHAVC) input. Here, the control is developed to ensure robustness with respect to the driveline operating conditions e.g. driveline misalignment, load-torque, shaft speed and shaft imbalance. The analysis shows that the hybrid PID/MHAVC control strategy achieves multi-harmonic suppression of the imbalance, misalignment and load-torque induced driveline vibration over a range of operating conditions. Furthermore, the control law developed for Configuration II is based on a hybrid robust Hinfinity feedback/Synchronous Adaptive Vibration Control (SAVC) strategy. Here, the effects of temperature dependent FMC material properties, rotating-frame damping and shaft imbalance are considered in the control design. The analysis shows that the hybrid Hinfinity/SAVC control strategy guarantees stability, convergence and imbalance vibration suppression under the conditions of bounded temperature deviations and unknown imbalance. Finally, the robustness and

  8. 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.

  9. 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

  10. Robust Matching Cost Function for Stereo Correspondence Using Matching by Tone Mapping and Adaptive Orthogonal Integral Image.

    PubMed

    Dinh, Vinh Quang; Nguyen, Vinh Dinh; Jeon, Jae Wook

    2015-12-01

    Real-world stereo images are inevitably affected by radiometric differences, including variations in exposure, vignetting, lighting, and noise. Stereo images with severe radiometric distortion can have large radiometric differences and include locally nonlinear changes. In this paper, we first introduce an adaptive orthogonal integral image, which is an improved version of an orthogonal integral image. After that, based on matching by tone mapping and the adaptive orthogonal integral image, we propose a robust and accurate matching cost function that can tolerate locally nonlinear intensity distortion. By using the adaptive orthogonal integral image, the proposed matching cost function can adaptively construct different support regions of arbitrary shapes and sizes for different pixels in the reference image, so it can operate robustly within object boundaries. Furthermore, we develop techniques to automatically estimate the values of the parameters of our proposed function. We conduct experiments using the proposed matching cost function and compare it with functions employing the census transform, supporting local binary pattern, and adaptive normalized cross correlation, as well as a mutual information-based matching cost function using different stereo data sets. By using the adaptive orthogonal integral image, the proposed matching cost function reduces the error from 21.51% to 15.73% in the Middlebury data set, and from 15.9% to 10.85% in the Kitti data set, as compared with using the orthogonal integral image. The experimental results indicate that the proposed matching cost function is superior to the state-of-the-art matching cost functions under radiometric variation.

  11. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    NASA Astrophysics Data System (ADS)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

  12. Robust model reference adaptive control for a two-dimensional piezo-driven micro-displacement scanning platform based on the asymmetrical Bouc-Wen model

    NASA Astrophysics Data System (ADS)

    Yang, Haigen; Zhu, Wei; Fu, Xiao

    2016-11-01

    The hysteresis characteristics resulted from piezoelectric actuators (PAs) and the residual vibration in the rapid positioning of a two-dimensional piezo-driven micro-displacement scanning platform (2D-PDMDSP) will greatly affect the positioning accuracy and speed. In this paper, in order to improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP, firstly, Utilizing an online hysteresis observer based on the asymmetrical Bouc-Wen model, the PA with the hysteresis characteristics is feedforward linearized and can be used as a linear actuator; secondly, zero vibration and derivative shaping (ZVDS) technique is used to eliminate the residual vibration of the 2D-PDMDSP; lastly, the robust model reference adaptive (RMRA) control for the 2D-PDMDSP is proposed and explored. The rapid control prototype of the RMRA controller combining the proposed feedforward linearization and ZVDS control for the 2D-PDMDSP with rapid control prototyping technique based on the real-time simulation system is established and experimentally tested, and the corresponding controlled results are compared with those by the PID control method. The experimental results show that the proposed RMRA control method can significantly improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP.

  13. Robust, integrated computational control of NMR experiments to achieve optimal assignment by ADAPT-NMR.

    PubMed

    Bahrami, Arash; Tonelli, Marco; Sahu, Sarata C; Singarapu, Kiran K; Eghbalnia, Hamid R; Markley, John L

    2012-01-01

    ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

  14. Robust Wave-front Correction in a Small Scale Adaptive Optics System Using a Membrane Deformable Mirror

    NASA Astrophysics Data System (ADS)

    Choi, Y.; Park, S.; Baik, S.; Jung, J.; Lee, S.; Yoo, J.

    A small scale laboratory adaptive optics system using a Shack-Hartmann wave-front sensor (WFS) and a membrane deformable mirror (DM) has been built for robust image acquisition. In this study, an adaptive limited control technique is adopted to maintain the long-term correction stability of an adaptive optics system. To prevent the waste of dynamic correction range for correcting small residual wave-front distortions which are inefficient to correct, the built system tries to limit wave-front correction when a similar small difference wave-front pattern is repeatedly generated. Also, the effect of mechanical distortion in an adaptive optics system is studied and a pre-recognition method for the distortion is devised to prevent low-performance system operation. A confirmation process for a balanced work assignment among deformable mirror (DM) actuators is adopted for the pre-recognition. The corrected experimental results obtained by using a built small scale adaptive optics system are described in this paper.

  15. Adaptive Modulation Approach for Robust MPEG-4 AAC Encoded Audio Transmission

    DTIC Science & Technology

    2011-11-01

    to switch to a higher source rate at a given channel bandwidth, which is not possible using single (non-adaptive) modulation, such as 4- QAM for all...case of QPSK/4- QAM , again at high Eb/No (negligible BER), the source rate can be switched to 128kbps (ignoring other transmission overhead) thus...adaptive scheme uses the 4- QAM modulation, whereas the adaptive modulation scheme employs the 4, 8, and 16 QAM for ESC1, ESC2 and ESC3, respectively

  16. SU-F-BRB-07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online-Adaptive Radiotherapy

    SciTech Connect

    Hill, P; Labby, Z; Bayliss, R A; Geurts, M; Bayouth, J

    2015-06-15

    Purpose: To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online-adaptive radiotherapy plans using similarity metrics. Methods: The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam-on time), the tool computes and presents histograms of derived metrics (e.g. step-and-shoot segment field sizes, segment average leaf gaps). Such metrics were investigated for their ability to predict that an online-adapted plan reasonably similar to a baseline plan where deliverability has already been established. Results: In the realm of online-adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re-optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online-adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements. Conclusion: The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online-adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to

  17. 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.

  18. A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

    NASA Technical Reports Server (NTRS)

    Wen, John T.; Kreutz, Kenneth; Bayard, David S.

    1988-01-01

    A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

  19. Final Progress Report on Robust and/or Adaptive Filtering by Neural Networks

    DTIC Science & Technology

    2007-11-02

    Transactions on Automatic Control , November 2002 (with Thomas Wanner). Existence and uniqueness of conditional expectations and thus minimum-variance estimates...are guaranteed by the Radon-Nikodym theorem in measure theory . Existence and uniqueness issues of robust estimates with respect to the risk-sensitive...sensitive estimates, i.e., exhibiting an extremely high level of nonuniqueness . • Recurrent Multilayer Perceptrons for Discrete-Time Dynamic System

  20. Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

    PubMed

    Whitacre, James M; Bender, Axel

    2010-06-15

    A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

  1. 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.

  2. HIFI-C: a robust and fast method for determining NMR couplings from adaptive 3D to 2D projections.

    PubMed

    Cornilescu, Gabriel; Bahrami, Arash; Tonelli, Marco; Markley, John L; Eghbalnia, Hamid R

    2007-08-01

    We describe a novel method for the robust, rapid, and reliable determination of J couplings in multi-dimensional NMR coupling data, including small couplings from larger proteins. The method, "High-resolution Iterative Frequency Identification of Couplings" (HIFI-C) is an extension of the adaptive and intelligent data collection approach introduced earlier in HIFI-NMR. HIFI-C collects one or more optimally tilted two-dimensional (2D) planes of a 3D experiment, identifies peaks, and determines couplings with high resolution and precision. The HIFI-C approach, demonstrated here for the 3D quantitative J method, offers vital features that advance the goal of rapid and robust collection of NMR coupling data. (1) Tilted plane residual dipolar couplings (RDC) data are collected adaptively in order to offer an intelligent trade off between data collection time and accuracy. (2) Data from independent planes can provide a statistical measure of reliability for each measured coupling. (3) Fast data collection enables measurements in cases where sample stability is a limiting factor (for example in the presence of an orienting medium required for residual dipolar coupling measurements). (4) For samples that are stable, or in experiments involving relatively stronger couplings, robust data collection enables more reliable determinations of couplings in shorter time, particularly for larger biomolecules. As a proof of principle, we have applied the HIFI-C approach to the 3D quantitative J experiment to determine N-C' RDC values for three proteins ranging from 56 to 159 residues (including a homodimer with 111 residues in each subunit). A number of factors influence the robustness and speed of data collection. These factors include the size of the protein, the experimental set up, and the coupling being measured, among others. To exhibit a lower bound on robustness and the potential for time saving, the measurement of dipolar couplings for the N-C' vector represents a realistic

  3. Robustness of Adaptive Control Algorithms in the Presence of Unmodeled Dynamics,

    DTIC Science & Technology

    1982-09-01

    result, two possible noch - tt (t (3a) anisms of instability are isolated and discussed. It is argued, that the destabilizing effects in the presence L t [J...to Modeling Errors, Ph.D. Thesis, Dept. of Elec. Eng., Univ. of Illinois at 2. A. uer mad A.S. Norse, *Adaptive Control of Urbana -ahampaign, Report

  4. A robust face recognition algorithm under varying illumination using adaptive retina modeling

    NASA Astrophysics Data System (ADS)

    Cheong, Yuen Kiat; Yap, Vooi Voon; Nisar, Humaira

    2013-10-01

    Variation in illumination has a drastic effect on the appearance of a face image. This may hinder the automatic face recognition process. This paper presents a novel approach for face recognition under varying lighting conditions. The proposed algorithm uses adaptive retina modeling based illumination normalization. In the proposed approach, retina modeling is employed along with histogram remapping following normal distribution. Retina modeling is an approach that combines two adaptive nonlinear equations and a difference of Gaussians filter. Two databases: extended Yale B database and CMU PIE database are used to verify the proposed algorithm. For face recognition Gabor Kernel Fisher Analysis method is used. Experimental results show that the recognition rate for the face images with different illumination conditions has improved by the proposed approach. Average recognition rate for Extended Yale B database is 99.16%. Whereas, the recognition rate for CMU-PIE database is 99.64%.

  5. 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.

  6. Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators

    PubMed Central

    Nogueira, Samuel L.; Pazelli, Tatiana F. P. A. T.; Siqueira, Adriano A. G.; Terra, Marco H.

    2013-01-01

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear ℋ∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose. PMID:23598503

  7. 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.

  8. Experimental investigation on adaptive robust controller designs applied to constrained manipulators.

    PubMed

    Nogueira, Samuel L; Pazelli, Tatiana F P A T; Siqueira, Adriano A G; Terra, Marco H

    2013-04-18

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear H∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose.

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

    PubMed

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

    2015-11-01

    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.

  10. 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.

  11. 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.

  12. 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.

  13. Sensitive on-chip quantitative real-time PCR performed on an adaptable and robust platform.

    PubMed

    Lund-Olesen, Torsten; Dufva, Martin; Dahl, John Arne; Collas, Philippe; Hansen, Mikkel Fougt

    2008-12-01

    A robust, flexible and efficient system for performing high sensitivity quantitative on-chip real-time PCR for research purposes is presented. The chips used consist of microchannels etched in silicon. The surface in the channels is a thermally grown silicon dioxide and the channel is sealed by a glass lid. The chips contain four PCR chambers but this number can be increased for further multiplexing. Contrary to PCR chips with oil covered open chambers, these channel-like chambers are easily integrated in lab-on-a-chip devices. The temperature is controlled by a Peltier element and the fluorochrome detector system is a commercially available fluorescence stereo microscope equipped with a CCD camera. The setup shows an excellent signal-to-noise ratio of about 400 compared to that of about 150 obtained in a commercial real time PCR machine. A detection limit of a few copies of target molecules is found, which is 100 to 100,000-fold better than other on-chip real-time PCR systems presented in the literature. This demonstrates that the PCR system can be used for critical applications. We also demonstrate that high quality melting curves can be obtained. Such curves are important in lab-on-a-chip systems for identification of amplified product. The usability of the system is validated by performing quantitative on-chip measurements of the amount of specific gene sequences co-immunoprecipitated with various posttranslationally modified histone proteins. Similar results are obtained from on-chip experiments and experiments carried out in a commercial system on larger sample volumes.

  14. Robust and adaptive techniques for numerical simulation of nonlinear partial differential equations of fractional order

    NASA Astrophysics Data System (ADS)

    Owolabi, Kolade M.

    2017-03-01

    In this paper, some nonlinear space-fractional order reaction-diffusion equations (SFORDE) on a finite but large spatial domain x ∈ [0, L], x = x(x , y , z) and t ∈ [0, T] are considered. Also in this work, the standard reaction-diffusion system with boundary conditions is generalized by replacing the second-order spatial derivatives with Riemann-Liouville space-fractional derivatives of order α, for 0 < α < 2. Fourier spectral method is introduced as a better alternative to existing low order schemes for the integration of fractional in space reaction-diffusion problems in conjunction with an adaptive exponential time differencing method, and solve a range of one-, two- and three-components SFORDE numerically to obtain patterns in one- and two-dimensions with a straight forward extension to three spatial dimensions in a sub-diffusive (0 < α < 1) and super-diffusive (1 < α < 2) scenarios. It is observed that computer simulations of SFORDE give enough evidence that pattern formation in fractional medium at certain parameter value is practically the same as in the standard reaction-diffusion case. With application to models in biology and physics, different spatiotemporal dynamics are observed and displayed.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Robust Adaptive Control.

    DTIC Science & Technology

    1985-09-19

    C conltrolliN toI e iibit si -, nil t pCi Isil - CI’S!’’. , l0 i5 dh I ’.,I hJ1Cd On1 lk the .f L Sn: IOf it fitted manx e vi~adion an-Isa lI\\ 11.\\Jh M...8217t C\\1CI. LtlI\\ 111iC SI S( C.i’l- %%ill he r ~[ ( considel ed hCi C t0 redukc the coflple\\tat of the (I.% 0 G=k 1 01 1𔃻 7a I deC11114-1 el kie and... sis the oupen-Iu" p interconneionwf mtatrix %%hose element-, are proper rational functions. (To eCt) = H,(%0) i~r). (19) simplif\\ notation Ae %iill

  5. Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles

    NASA Astrophysics Data System (ADS)

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-08-01

    A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

  6. 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.

  7. 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

  8. 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.

  9. Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

    PubMed

    Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

    2014-09-01

    This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations.

  10. (Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

    PubMed Central

    2013-01-01

    Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and

  11. 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.

  12. 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.

  13. Noise-Robust Spectral Signature Classification in Non-resolved Object Detection using Feedback Controlled Adaptive Learning

    NASA Astrophysics Data System (ADS)

    Schmalz, M.; Key, G.

    2012-09-01

    Accurate spectral signature classification is key to reliable nonresolved detection and recognition of spaceborne objects. In classical signature-based recognition applications, classification accuracy has been shown to depend on accurate spectral endmember discrimination. Unfortunately, signatures are corrupted by noise and clutter that can be nonergodic in astronomical imaging practice. In previous work, we have shown that object class separation and classifier refinement results can be severely corrupted by input noise, leading to suboptimal classification. We have also shown that computed pattern recognition, like its human counterpart, can benefit from processes such as learning or forgetting, which in spectral signature classification can support adaptive tracking of input nonergodicities. In this paper, we model learning as the acquisition or insertion of a new pattern into a classifier's knowledge base. For example, in neural nets (NNs), this insertion process could correspond to the superposition of a new pattern onto the NN weight matrix. Similarly, we model forgetting as the deletion of a pattern currently stored in the classifier knowledge base, for example, as a pattern deletion operation on the NN weight matrix, which is a difficult goal with classical neural nets (CNNs). In particular, this paper discusses the implementation of feedback control for pattern insertion and deletion in lattice associative memories (LAMs) and dynamically adaptive statistical data fusion (DASDAF) paradigms, in support of signature classification. It is shown that adaptive classifiers based on LNN or DASDAF technology can achieve accurate signature classification in the presence of nonergodic Gaussian and non-Gaussian noise, at low signal-to-noise ratio (SNR). Demonstration involves classification of multiple closely spaced, noise corrupted signatures from a NASA database of space material signatures at SNR > 0.1:1.

  14. 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.

  15. Investigation of whether in-room CT-based adaptive intracavitary brachytherapy for uterine cervical cancer is robust against interfractional location variations of organs and/or applicators

    PubMed Central

    Oku, Yoshifumi; Arimura, Hidetaka; Nguyen, Tran Thi Thao; Hiraki, Yoshiyuki; Toyota, Masahiko; Saigo, Yasumasa; Yoshiura, Takashi; Hirata, Hideki

    2016-01-01

    This study investigates whether in-room computed tomography (CT)-based adaptive treatment planning (ATP) is robust against interfractional location variations, namely, interfractional organ motions and/or applicator displacements, in 3D intracavitary brachytherapy (ICBT) for uterine cervical cancer. In ATP, the radiation treatment plans, which have been designed based on planning CT images (and/or MR images) acquired just before the treatments, are adaptively applied for each fraction, taking into account the interfractional location variations. 2D and 3D plans with ATP for 14 patients were simulated for 56 fractions at a prescribed dose of 600 cGy per fraction. The standard deviations (SDs) of location displacements (interfractional location variations) of the target and organs at risk (OARs) with 3D ATP were significantly smaller than those with 2D ATP (P < 0.05). The homogeneity index (HI), conformity index (CI) and tumor control probability (TCP) in 3D ATP were significantly higher for high-risk clinical target volumes than those in 2D ATP. The SDs of the HI, CI, TCP, bladder and rectum D2cc, and the bladder and rectum normal tissue complication probability (NTCP) in 3D ATP were significantly smaller than those in 2D ATP. The results of this study suggest that the interfractional location variations give smaller impacts on the planning evaluation indices in 3D ATP than in 2D ATP. Therefore, the 3D plans with ATP are expected to be robust against interfractional location variations in each treatment fraction. PMID:27296250

  16. A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ushaq, Muhammad; Fang, Jiancheng

    2013-10-01

    Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be

  17. 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.

  18. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  19. 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

  20. The Balance Super Learner: A robust adaptation of the Super Learner to improve estimation of the average treatment effect in the treated based on propensity score matching.

    PubMed

    Pirracchio, Romain; Carone, Marco

    2016-01-01

    Consistency of the propensity score estimators rely on correct specification of the propensity score model. The propensity score is frequently estimated using a main effect logistic regression. It has recently been shown that the use of ensemble machine learning algorithms, such as the Super Learner, could improve covariate balance and reduce bias in a meaningful manner in the case of serious model misspecification for treatment assignment. However, the loss functions normally used by the Super Learner may not be appropriate for propensity score estimation since the goal in this problem is not to optimize propensity score prediction but rather to achieve the best possible balance in the covariate distribution between treatment groups. In a simulation study, we evaluated the benefit of a modification of the Super Learner by propensity score estimation geared toward achieving covariate balance between the treated and untreated after matching on the propensity score. Our simulation study included six different scenarios characterized by various degrees of deviation from the usual main term logistic model for the true propensity score and outcome as well as the presence (or not) of instrumental variables. Our results suggest that the use of this adapted Super Learner to estimate the propensity score can further improve the robustness of propensity score matching estimators.

  1. Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

  2. 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.

  3. An observer-based compensator for distributed delays in integrated control systems

    NASA Technical Reports Server (NTRS)

    Luck, Rogelio; Ray, Asok

    1989-01-01

    This paper presents an algorithm for compensation of delays that are distributed within a control loop. The observer-based algorithm is especially suitable for compensating network-induced delays that are likely to occur in integrated control systems of the future generation aircraft. The robustness of the algorithm relative to uncertainties in the plant model have been examined.

  4. Engineering robust intelligent robots

    NASA Astrophysics Data System (ADS)

    Hall, E. L.; Ali, S. M. Alhaj; Ghaffari, M.; Liao, X.; Cao, M.

    2010-01-01

    The purpose of this paper is to discuss the challenge of engineering robust intelligent robots. Robust intelligent robots may be considered as ones that not only work in one environment but rather in all types of situations and conditions. Our past work has described sensors for intelligent robots that permit adaptation to changes in the environment. We have also described the combination of these sensors with a "creative controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment. However, the emphasis of this paper is on engineering solutions which are designed for robust operations and worst case situations such as day night cameras or rain and snow solutions. This ideal model may be compared to various approaches that have been implemented on "production vehicles and equipment" using Ethernet, CAN Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Many prototype intelligent robots have been developed and demonstrated in terms of scientific feasibility but few have reached the stage of a robust engineering solution. Continual innovation and improvement are still required. The significance of this comparison is that it provides some insights that may be useful in designing future robots for various manufacturing, medical, and defense applications where robust and reliable performance is essential.

  5. 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.

  6. Robustness in bacterial chemotaxis

    NASA Astrophysics Data System (ADS)

    Alon, U.; Surette, M. G.; Barkai, N.; Leibler, S.

    1999-01-01

    Networks of interacting proteins orchestrate the responses of living cells to a variety of external stimuli, but how sensitive is the functioning of these protein networks to variations in theirbiochemical parameters? One possibility is that to achieve appropriate function, the reaction rate constants and enzyme concentrations need to be adjusted in a precise manner, and any deviation from these `fine-tuned' values ruins the network's performance. An alternative possibility is that key properties of biochemical networks are robust; that is, they are insensitive to the precise values of the biochemical parameters. Here we address this issue in experiments using chemotaxis of Escherichia coli, one of the best-characterized sensory systems,. We focus on how response and adaptation to attractant signals vary with systematic changes in the intracellular concentration of the components of the chemotaxis network. We find that some properties, such as steady-state behaviour and adaptation time, show strong variations in response to varying protein concentrations. In contrast, the precision of adaptation is robust and does not vary with the protein concentrations. This is consistent with a recently proposed molecular mechanism for exact adaptation, where robustness is a direct consequence of the network's architecture.

  7. An Observer-Based Foundation of Geometry

    NASA Astrophysics Data System (ADS)

    Bahreyni, Newshaw; Knuth, Kevin H.

    2012-02-01

    The fact that some events influence other events enables one to define a partially ordered set (poset) of events, often referred to as a causal set. A chain of events, called observer chain, can be quantified by labeling its events numerically. Other events in a poset may be quantified with respect to an observer chain/chains by projecting them onto the chain, resulting in a pair of numbers. Similarly, pairs of events, called intervals, can be quantified with four numbers. Under certain conditions, this leads to the Minkowski metric, Lorentz transformations and the mathematics of special relativity (Bahreyni & Knuth, APS March Meeting 2011). We exploit the same techniques to demonstrate that geometric concepts can be derived from order-theoretic concepts. We show how chains in a poset can be used to define points and line segments. Subsequent quantification results in the Pythagorean Theorem and the inner product as well as other geometric concepts and measures. Thus the geometry of space, which is assumed to be fundamental, emerges as a result of quantifying a partially ordered set. More importantly, this proposed foundation of geometry is entirely observer-based, which may provide a natural way toward integration with quantum mechanics.

  8. 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

  9. Assessing the robustness of adaptation decisions in river flood defences to uncertainty in climate impact analysis: A case study on the River Suir, Ireland

    NASA Astrophysics Data System (ADS)

    Murphy, N.; Murphy, C.

    2009-12-01

    Climate change presents a challenging environment for policy makers and planners as future climate projections are fraught with uncertainty. From the formulation of emissions scenarios, through to the output from Global Climate Models to the regional and then the local scale, uncertainty propagates and increases leading to a cascade of uncertainty (Jones, 2001). The level of flood defences for rivers in Ireland has been built to withstand the 1 in 100 year event based on the historic record. However, stream flow due to climate change is likely to increase by 20% in winter by mid century. The Office of Public Works has therefore revised their projections by adding 20% to the 1 in 100 year event as a design feature of their new flood defences. This poster presents a sensitivity analysis of how various aspects of the climate impact assessment affect the revised level of the 1 in 100 year flood. The River Suir is used as a case study. This poster aims to quantify how different aspects of climate impact assessment uncertainty (GCM, Emissions scenario, impact model) affect the revised level of the 1 in 100 year flood and evaluates if the design of flood defences remains robust to the this uncertainty. Authors. Nuala Murphy Conor Murphy

  10. Real-time detection of small and dim moving objects in IR video sequences using a robust background estimator and a noise-adaptive double thresholding

    NASA Astrophysics Data System (ADS)

    Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

    2016-10-01

    We developed an algorithm for automatically detecting small and poorly contrasted (dim) moving objects in real-time, within video sequences acquired through a steady infrared camera. The algorithm is suitable for different situations since it is independent of the background characteristics and of changes in illumination. Unlike other solutions, small objects of any size (up to single-pixel), either hotter or colder than the background, can be successfully detected. The algorithm is based on accurately estimating the background at the pixel level and then rejecting it. A novel approach permits background estimation to be robust to changes in the scene illumination and to noise, and not to be biased by the transit of moving objects. Care was taken in avoiding computationally costly procedures, in order to ensure the real-time performance even using low-cost hardware. The algorithm was tested on a dataset of 12 video sequences acquired in different conditions, providing promising results in terms of detection rate and false alarm rate, independently of background and objects characteristics. In addition, the detection map was produced frame by frame in real-time, using cheap commercial hardware. The algorithm is particularly suitable for applications in the fields of video-surveillance and computer vision. Its reliability and speed permit it to be used also in critical situations, like in search and rescue, defence and disaster monitoring.

  11. 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.

  12. Robust synchronization of a class of chaotic systems with disturbance estimation

    NASA Astrophysics Data System (ADS)

    Xiang, Wei; Chen, Fangqi

    2011-08-01

    This paper investigates the robust synchronization problem for a class of chaotic systems with external disturbances. By using disturbance-observer-based control (DOBC) and LMI approach, the disturbance observers are developed to ensure the boundedness of the disturbance error dynamical. Then, by employing the sliding mode control technique, an adaptive control law is established to eliminate the effect of disturbance error to realize synchronization between the master and slave systems. Finally, the corresponding numerical simulations are demonstrated to verify the effectiveness of proposed method.

  13. 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.

  14. Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

    SciTech Connect

    Schmidt, Matthew Grzetic, Shelby; Lo, Joseph Y.; Lutzky, Carly; Brizel, David M.; Das, Shiva K.

    2015-08-15

    Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention

  15. 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

  16. 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.

  17. Adaptive and Robust Resource Allocation and Scheduling

    DTIC Science & Technology

    2010-05-03

    HOK nvjrnocn OT. vvunr. uim l NUMDUI /. rtni-unminiu UHUHNUA I IUN NMivttis) HNU Muuneosicoi Brown University Office of Research...telecommunication technologies which enables entreprises and organizations to track their operations in real-time us- ing technologies such as GPS...RFIDs, sensors, and high- performance networks. The ubiquity of telecommunication technologies led to a paradigm shift in business processes

  18. Robust Adaptive Control of Multivariable Nonlinear Systems

    DTIC Science & Technology

    2011-03-28

    Systems: Challenge Problem Integration and NASA s Integrated Resilient Aircraft Control . We also revealed some similarities with the disturbance ... observer (DOB) controllers and identified the main features in the difference between them. The key feature of this difference is that the estimation loop

  19. 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.

  20. Analysis and Synthesis of Robust Data Structures

    DTIC Science & Technology

    1990-08-01

    1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into

  1. Observer-based beamforming algorithm for acoustic array signal processing.

    PubMed

    Bai, Long; Huang, Xun

    2011-12-01

    In the field of noise identification with microphone arrays, conventional delay-and-sum (DAS) beamforming is the most popular signal processing technique. However, acoustic imaging results that are generated by DAS beamforming are easily influenced by background noise, particularly for in situ wind tunnel tests. Even when arithmetic averaging is used to statistically remove the interference from the background noise, the results are far from perfect because the interference from the coherent background noise is still present. In addition, DAS beamforming based on arithmetic averaging fails to deliver real-time computational capability. An observer-based approach is introduced in this paper. This so-called observer-based beamforming method has a recursive form similar to the state observer in classical control theory, thus holds a real-time computational capability. In addition, coherent background noise can be gradually rejected in iterations. Theoretical derivations of the observer-based beamforming algorithm are carefully developed in this paper. Two numerical simulations demonstrate the good coherent background noise rejection and real-time computational capability of the observer-based beamforming, which therefore can be regarded as an attractive algorithm for acoustic array signal processing.

  2. Advances in Adaptive Control Methods

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2009-01-01

    This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Robust coding over noisy overcomplete channels.

    PubMed

    Doi, Eizaburo; Balcan, Doru C; Lewicki, Michael S

    2007-02-01

    We address the problem of robust coding in which the signal information should be preserved in spite of intrinsic noise in the representation. We present a theoretical analysis for 1- and 2-D cases and characterize the optimal linear encoder and decoder in the mean-squared error sense. Our analysis allows for an arbitrary number of coding units, thus including both under- and over-complete representations, and provides insights into optimal coding strategies. In particular, we show how the form of the code adapts to the number of coding units and to different data and noise conditions in order to achieve robustness. We also present numerical solutions of robust coding for high-dimensional image data, demonstrating that these codes are substantially more robust than other linear image coding methods such as PCA, ICA, and wavelets.

  8. Robust Critical Point Detection

    SciTech Connect

    Bhatia, Harsh

    2016-07-28

    Robust Critical Point Detection is a software to compute critical points in a 2D or 3D vector field robustly. The software was developed as a part of the author's work at the lab as a Phd student under Livermore Scholar Program (now called Livermore Graduate Scholar Program).

  9. 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…

  10. Robust stability and performance of time-delay control systems.

    PubMed

    Keviczky, L; Bányász, Cs

    2007-04-01

    Most of the optimal and adaptive regulators assume an a priori known time delay. The time-delay mismatch can cause unwanted instability. Influence of this uncertainty is investigated in connection with the required performance and robustness.

  11. Robustness with observers. [linear optimal feedback control systems

    NASA Technical Reports Server (NTRS)

    Doyle, J. C.; Stein, G.

    1979-01-01

    The paper describes an adjustment procedure for observer-based linear control systems which asymptotically achieves the same loop transfer functions (and hence the same relative stability, robustness, and disturbance rejection properties) as full-state feedback control implementations. Full-state loop-transfer properties can be recovered asymptotically if the plant is minimum phase; this occurs at the expense of noise performance.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Robustness. [in space systems

    NASA Technical Reports Server (NTRS)

    Ryan, Robert

    1993-01-01

    The concept of rubustness includes design simplicity, component and path redundancy, desensitization to the parameter and environment variations, control of parameter variations, and punctual operations. These characteristics must be traded with functional concepts, materials, and fabrication approach against the criteria of performance, cost, and reliability. The paper describes the robustness design process, which includes the following seven major coherent steps: translation of vision into requirements, definition of the robustness characteristics desired, criteria formulation of required robustness, concept selection, detail design, manufacturing and verification, operations.

  17. Observer-based lag synchronization between two different complex networks

    NASA Astrophysics Data System (ADS)

    Zhao, M.; Zhang, H. G.; Wang, Z. L.; Liang, H. J.

    2014-06-01

    In this paper, some new criteria for lag synchronization between two or more complex networks are proposed based on the theory of state observer. Some adaptive controllers are designed to make the drive and response systems achieve lag synchronization, no matter whether the nodes in the two systems are with the same dynamical character or the coupling configuration matrices are nonidentical. In addition, based on the output coupling, the amount of coupling variables between two connected nodes is flexible, which can save a lot of channel resources, simplify the network topology and has more significant meanings in engineering applications. At last, the effects of the lag synchronization criteria are verified through some simulation experiments.

  18. A one-step method of designing an observer-based modified repetitive-control system

    NASA Astrophysics Data System (ADS)

    Zhou, Lan; She, Jinhua; Wu, Min

    2015-10-01

    A method of designing a robust observer-based modified repetitive-control system for a class of strictly proper linear plants with periodic uncertainties has been developed. These plants have no direct path from the input to the output. First, the periodicity and continuity of repetitive control are exploited to construct a continuous-discrete two-dimensional (2D) model that allows the preferential adjustment of control and learning through regulation of the 2D feedback gains. Next, Lyapunov stability theory and the singular-value decomposition of the output matrix are used to establish two stability conditions. The conditions convert (a) the problem of designing the maximum cut-off angular frequency of the low-pass filter into a standard generalised eigenvalue optimisation problem, and (b) the problem of independently designing a state observer and a stabilising controller into a feasibility problem for linear matrix inequalities (LMIs). Two tuning parameters in one of the LMIs determine the selection of the 2D feedback gains. Then, the combination of two design conditions yields an iterative algorithm that simultaneously optimises the maximum cut-off angular frequency of the low-pass filter and the gains of the stabilising controller. It solves the trade-off problem between stability and tracking performance. Finally, a simulation example demonstrates the validity of the method.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Robust Control Systems.

    DTIC Science & Technology

    1981-12-01

    106 A. 13 XSU ......................................... 108 A.14 DDTCON...................................... 108 A.15 DKFTR...operation is preserved. Although some papers (Refs 6 and 13 ) deal with robustness only in regard to parameter variations within the basic controlled...since these can ofter be neglected in actual implementation, a constant-gain time 13 ........................................ invariant solution with

  4. Robustness of spatial micronetworks.

    PubMed

    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.

  5. Robustness analysis of stochastic biochemical systems.

    PubMed

    Ceska, Milan; Safránek, David; Dražan, Sven; Brim, Luboš

    2014-01-01

    We propose a new framework for rigorous robustness analysis of stochastic biochemical systems that is based on probabilistic model checking techniques. We adapt the general definition of robustness introduced by Kitano to the class of stochastic systems modelled as continuous time Markov Chains in order to extensively analyse and compare robustness of biological models with uncertain parameters. The framework utilises novel computational methods that enable to effectively evaluate the robustness of models with respect to quantitative temporal properties and parameters such as reaction rate constants and initial conditions. We have applied the framework to gene regulation as an example of a central biological mechanism where intrinsic and extrinsic stochasticity plays crucial role due to low numbers of DNA and RNA molecules. Using our methods we have obtained a comprehensive and precise analysis of stochastic dynamics under parameter uncertainty. Furthermore, we apply our framework to compare several variants of two-component signalling networks from the perspective of robustness with respect to intrinsic noise caused by low populations of signalling components. We have successfully extended previous studies performed on deterministic models (ODE) and showed that stochasticity may significantly affect obtained predictions. Our case studies demonstrate that the framework can provide deeper insight into the role of key parameters in maintaining the system functionality and thus it significantly contributes to formal methods in computational systems biology.

  6. Survival and innovation: The role of mutational robustness in evolution.

    PubMed

    Fares, Mario A

    2015-12-01

    Biological systems are resistant to perturbations caused by the environment and by the intrinsic noise of the system. Robustness to mutations is a particular aspect of robustness in which the phenotype is resistant to genotypic variation. Mutational robustness has been linked to the ability of the system to generate heritable genetic variation (a property known as evolvability). It is known that greater robustness leads to increased evolvability. Therefore, mechanisms that increase mutational robustness fuel evolvability. Two such mechanisms, molecular chaperones and gene duplication, have been credited with enormous importance in generating functional diversity through the increase of system's robustness to mutational insults. However, the way in which such mechanisms regulate robustness remains largely uncharacterized. In this review, I provide evidence in support of the role of molecular chaperones and gene duplication in innovation. Specifically, I present evidence that these mechanisms regulate robustness allowing unstable systems to survive long periods of time, and thus they provide opportunity for other mutations to compensate the destabilizing effects of functionally innovative mutations. The findings reported in this study set new questions with regards to the synergy between robustness mechanisms and how this synergy can alter the adaptive landscape of proteins. The ideas proposed in this article set the ground for future research in the understanding of the role of robustness in evolution.

  7. Adaptive control of linearizable systems

    NASA Technical Reports Server (NTRS)

    Sastry, S. Shankar; Isidori, Alberto

    1989-01-01

    Initial results are reported regarding the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious.

  8. Comparing dependent robust correlations.

    PubMed

    Wilcox, Rand R

    2016-11-01

    Let r1 and r2 be two dependent estimates of Pearson's correlation. There is a substantial literature on testing H0  : ρ1  = ρ2 , the hypothesis that the population correlation coefficients are equal. However, it is well known that Pearson's correlation is not robust. Even a single outlier can have a substantial impact on Pearson's correlation, resulting in a misleading understanding about the strength of the association among the bulk of the points. A way of mitigating this concern is to use a correlation coefficient that guards against outliers, many of which have been proposed. But apparently there are no results on how to compare dependent robust correlation coefficients when there is heteroscedasicity. Extant results suggest that a basic percentile bootstrap will perform reasonably well. This paper reports simulation results indicating the extent to which this is true when using Spearman's rho, a Winsorized correlation or a skipped correlation.

  9. Robust verification analysis

    NASA Astrophysics Data System (ADS)

    Rider, William; Witkowski, Walt; Kamm, James R.; Wildey, Tim

    2016-02-01

    We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification. Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations.

  10. Robust verification analysis

    SciTech Connect

    Rider, William; Witkowski, Walt; Kamm, James R.; Wildey, Tim

    2016-02-15

    We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification. Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations.

  11. Robustness of metabolic networks

    NASA Astrophysics Data System (ADS)

    Jeong, Hawoong

    2009-03-01

    We investigated the robustness of cellular metabolism by simulating the system-level computational models, and also performed the corresponding experiments to validate our predictions. We address the cellular robustness from the ``metabolite''-framework by using the novel concept of ``flux-sum,'' which is the sum of all incoming or outgoing fluxes (they are the same under the pseudo-steady state assumption). By estimating the changes of the flux-sum under various genetic and environmental perturbations, we were able to clearly decipher the metabolic robustness; the flux-sum around an essential metabolite does not change much under various perturbations. We also identified the list of the metabolites essential to cell survival, and then ``acclimator'' metabolites that can control the cell growth were discovered. Furthermore, this concept of ``metabolite essentiality'' should be useful in developing new metabolic engineering strategies for improved production of various bioproducts and designing new drugs that can fight against multi-antibiotic resistant superbacteria by knocking-down the enzyme activities around an essential metabolite. Finally, we combined a regulatory network with the metabolic network to investigate its effect on dynamic properties of cellular metabolism.

  12. Robustness of Interdependent Networks

    NASA Astrophysics Data System (ADS)

    Havlin, Shlomo

    2011-03-01

    In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of many interdependent networks. We will present a framework for understanding the robustness of interacting networks subject to such cascading failures and provide a basic analytic approach that may be useful in future studies. We present exact analytical solutions for the critical fraction of nodes that upon removal will lead to a failure cascade and to a complete fragmentation of two interdependent networks in a first order transition. Surprisingly, analyzing complex systems as a set of interdependent networks may alter a basic assumption that network theory has relied on: while for a single network a broader degree distribution of the network nodes results in the network being more robust to random failures, for interdependent networks, the broader the distribution is, the more vulnerable the networks become to random failure. We also show that reducing the coupling between the networks leads to a change from a first order percolation phase transition to a second order percolation transition at a critical point. These findings pose a significant challenge to the future design of robust networks that need to consider the unique properties of interdependent networks.

  13. 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.

  14. Robust speech coding using microphone arrays

    NASA Astrophysics Data System (ADS)

    Li, Zhao

    1998-09-01

    To achieve robustness and efficiency for voice communication in noise, the noise suppression and bandwidth compression processes are combined to form a joint process using input from an array of microphones. An adaptive beamforming technique with a set of robust linear constraints and a single quadratic inequality constraint is used to preserve desired signal and to cancel directional plus ambient noise in a small room environment. This robustly constrained array processor is found to be effective in limiting signal cancelation over a wide range of input SNRs (-10 dB to +10 dB). The resulting intelligibility gains (8-10 dB) provide significant improvement to subsequent CELP coding. In addition, the desired speech activity is detected by estimating Target-to-Jammer Ratios (TJR) using subband correlations between different microphone inputs or using signals within the Generalized Sidelobe Canceler directly. These two novel techniques of speech activity detection for coding are studied thoroughly in this dissertation. Each is subsequently incorporated with the adaptive array and a 4.8 kbps CELP coder to form a Variable Bit Kate (VBR) coder with noise canceling and Spatial Voice Activity Detection (SVAD) capabilities. This joint noise suppression and bandwidth compression system demonstrates large improvements in desired speech quality after coding, accurate desired speech activity detection in various types of interference, and a reduction in the information bits required to code the speech.

  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 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.

  17. 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.

  18. Complexity and robustness

    PubMed Central

    Carlson, J. M.; Doyle, John

    2002-01-01

    Highly optimized tolerance (HOT) was recently introduced as a conceptual framework to study fundamental aspects of complexity. HOT is motivated primarily by systems from biology and engineering and emphasizes, (i) highly structured, nongeneric, self-dissimilar internal configurations, and (ii) robust yet fragile external behavior. HOT claims these are the most important features of complexity and not accidents of evolution or artifices of engineering design but are inevitably intertwined and mutually reinforcing. In the spirit of this collection, our paper contrasts HOT with alternative perspectives on complexity, drawing on real-world examples and also model systems, particularly those from self-organized criticality. PMID:11875207

  19. Robustness of Cantor diffractals.

    PubMed

    Verma, Rupesh; Sharma, Manoj Kumar; Banerjee, Varsha; Senthilkumaran, Paramasivam

    2013-04-08

    Diffractals are electromagnetic waves diffracted by a fractal aperture. In an earlier paper, we reported an important property of Cantor diffractals, that of redundancy [R. Verma et. al., Opt. Express 20, 8250 (2012)]. In this paper, we report another important property, that of robustness. The question we address is: How much disorder in the Cantor grating can be accommodated by diffractals to continue to yield faithfully its fractal dimension and generator? This answer is of consequence in a number of physical problems involving fractal architecture.

  20. Robust control algorithms for Mars aerobraking

    NASA Astrophysics Data System (ADS)

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

    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.

  1. Robust photometric stereo using structural light sources

    NASA Astrophysics Data System (ADS)

    Han, Tian-Qi; Cheng, Yue; Shen, Hui-Liang; Du, Xin

    2014-05-01

    We propose a robust photometric stereo method by using structural arrangement of light sources. In the arrangement, light sources are positioned on a planar grid and form a set of collinear combinations. The shadow pixels are detected by adaptive thresholding. The specular highlight and diffuse pixels are distinguished according to their intensity deviations of the collinear combinations, thanks to the special arrangement of light sources. The highlight detection problem is cast as a pattern classification problem and is solved using support vector machine classifiers. Considering the possible misclassification of highlight pixels, the ℓ1 regularization is further employed in normal map estimation. Experimental results on both synthetic and real-world scenes verify that the proposed method can robustly recover the surface normal maps in the case of heavy specular reflection and outperforms the state-of-the-art techniques.

  2. 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

  3. 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

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

    PubMed

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

    2012-05-08

    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.

  5. 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

  6. ANN-implemented robust vision model

    NASA Astrophysics Data System (ADS)

    Teng, Chungte; Ligomenides, Panos A.

    1991-02-01

    A robust vision model has been developed and implemented with a self-organizing/unsupervised artificial neural network (ANN) classifier-KART which is a novel hybrid model of a modified Kohonen''s feature map and the Carpenter/Grossberg''s ART architecture. The six moment invariants have been mapped onto a 7-dimensional unit hypersphere and have been applied to the KART classifier. In this paper the KART model will be presented. The non-adaptive neural implementations on the image processing and the moment invariant feature extraction will be discussed. In addition the simulation results that illustrate the capabilities of this model will also be provided. 1.

  7. 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

  8. 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!

  9. Robust Rocket Engine Concept

    NASA Technical Reports Server (NTRS)

    Lorenzo, Carl F.

    1995-01-01

    The potential for a revolutionary step in the durability of reusable rocket engines is made possible by the combination of several emerging technologies. The recent creation and analytical demonstration of life extending (or damage mitigating) control technology enables rapid rocket engine transients with minimum fatigue and creep damage. This technology has been further enhanced by the formulation of very simple but conservative continuum damage models. These new ideas when combined with recent advances in multidisciplinary optimization provide the potential for a large (revolutionary) step in reusable rocket engine durability. This concept has been named the robust rocket engine concept (RREC) and is the basic contribution of this paper. The concept also includes consideration of design innovations to minimize critical point damage.

  10. 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

  11. Robust Nonnegative Patch Alignment for Dimensionality Reduction.

    PubMed

    You, Xinge; Ou, Weihua; Chen, Chun Lung Philip; Li, Qiang; Zhu, Ziqi; Tang, Yuanyan

    2015-11-01

    Dimensionality reduction is an important method to analyze high-dimensional data and has many applications in pattern recognition and computer vision. In this paper, we propose a robust nonnegative patch alignment for dimensionality reduction, which includes a reconstruction error term and a whole alignment term. We use correntropy-induced metric to measure the reconstruction error, in which the weight is learned adaptively for each entry. For the whole alignment, we propose locality-preserving robust nonnegative patch alignment (LP-RNA) and sparsity-preserviing robust nonnegative patch alignment (SP-RNA), which are unsupervised and supervised, respectively. In the LP-RNA, we propose a locally sparse graph to encode the local geometric structure of the manifold embedded in high-dimensional space. In particular, we select large p -nearest neighbors for each sample, then obtain the sparse representation with respect to these neighbors. The sparse representation is used to build a graph, which simultaneously enjoys locality, sparseness, and robustness. In the SP-RNA, we simultaneously use local geometric structure and discriminative information, in which the sparse reconstruction coefficient is used to characterize the local geometric structure and weighted distance is used to measure the separability of different classes. For the induced nonconvex objective function, we formulate it into a weighted nonnegative matrix factorization based on half-quadratic optimization. We propose a multiplicative update rule to solve this function and show that the objective function converges to a local optimum. Several experimental results on synthetic and real data sets demonstrate that the learned representation is more discriminative and robust than most existing dimensionality reduction methods.

  12. Disturbance Observer-Based Fuzzy Control of Uncertain MIMO Mechanical Systems With Input Nonlinearities and its Application to Robotic Exoskeleton.

    PubMed

    Chen, Ziting; Li, Zhijun; Chen, C L Philip

    2016-03-16

    We develop a novel disturbance observer-based adaptive fuzzy control approach in this paper for a class of uncertain multi-input-multi-output mechanical systems possessing unknown input nonlinearities, i.e., deadzone and saturation and time-varying external disturbance. It is shown that the input nonlinearities can be represented by a nominal part and a nonlinear disturbance term. High-dimensional integral-type Lyapunov function is used to construct the controller. Fuzzy logic system is employed to cancel model uncertainties, and disturbance observer is also integrated into control design to compensate the fuzzy approximation error, external disturbance, and nonlinear disturbance caused by the unknown input nonlinearities. Semiglobally uniformly ultimately boundness of the closed-loop control system is guaranteed with tracking errors keeping bounded. Experimental studies on a robotic exoskeleton using the proposed control demonstrate the effectiveness of the approach.

  13. Robust Image Estimation in Signal-Dependent Noise.

    NASA Astrophysics Data System (ADS)

    Chen, Sin-Horng

    Conventional image estimates in signal-dependent noise lack robustness for variations in a priori assumptions. In this work, the min-max robustness problem of image estimation in a signal-dependent noise model is explored. The criterion of robustness is the mean square error (MSE). Three cases which correspond to variations in the a priori signal distribution, in the a priori noise distribution and in a parameter of the model are investigated. For variations in the a priori signal (noise) distribution, the signal (noise) distribution is modeled as (epsilon)-contaminated normal. Due to the signal-dependence of noise, the robustness problem is too complicated to be solved analytically. A numerical direct searching algorithm is therefore proposed. In solving this robustness problem, we construct min-max robust estimators based on a number of criteria. For point estimation, these criteria include minimum mean square error (MMSE), minimum mean square error plus mean square bias error (MEB); we also discuss a simple two-step method and an adaptive two -step method. For multiple parameter estimation, we consider only the last two estimation procedures. Also the min -max robust estimator based on minimizing a mean square transformed error is explored. This transformation incorporates knowledge of the nonlinear sensitivity of human eyes to light intensity. Estimation methods based on maximum entropy and on smoothing splines are also briefly discussed. Finally, the restorations of images on a computer are presented to demonstrate the performance of these robust estimators relative to their nonrobust counterparts.

  14. Dynamics robustness of cascading systems.

    PubMed

    Young, Jonathan T; Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

    2017-03-01

    A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a

  15. Dynamics robustness of cascading systems

    PubMed Central

    Kaneko, Kunihiko

    2017-01-01

    A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade’s kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a

  16. Robust relativistic bit commitment

    NASA Astrophysics Data System (ADS)

    Chakraborty, Kaushik; Chailloux, André; Leverrier, Anthony

    2016-12-01

    Relativistic cryptography exploits the fact that no information can travel faster than the speed of light in order to obtain security guarantees that cannot be achieved from the laws of quantum mechanics alone. Recently, Lunghi et al. [Phys. Rev. Lett. 115, 030502 (2015), 10.1103/PhysRevLett.115.030502] presented a bit-commitment scheme where each party uses two agents that exchange classical information in a synchronized fashion, and that is both hiding and binding. A caveat is that the commitment time is intrinsically limited by the spatial configuration of the players, and increasing this time requires the agents to exchange messages during the whole duration of the protocol. While such a solution remains computationally attractive, its practicality is severely limited in realistic settings since all communication must remain perfectly synchronized at all times. In this work, we introduce a robust protocol for relativistic bit commitment that tolerates failures of the classical communication network. This is done by adding a third agent to both parties. Our scheme provides a quadratic improvement in terms of expected sustain time compared with the original protocol, while retaining the same level of security.

  17. 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.

  18. Robust Weak Measurements

    NASA Astrophysics Data System (ADS)

    Tollaksen, Jeff; Aharonov, Yakir

    2006-03-01

    We introduce a new type of weak measurement which yields a quantum average of weak values that is robust, outside the range of eigenvalues, extends the valid regime for weak measurements, and for which the probability of obtaining the pre- and post-selected ensemble is not exponentially rare. This result extends the applicability of weak values, shifts the statistical interpretation previously attributed to weak values and suggests that the weak value is a property of every pre- and post-selected ensemble. We then apply this new weak measurement to Hardy's paradox. Usually the paradox is dismissed on grounds of counterfactuality, i.e., because the paradoxical effects appear only when one considers results of experiments which do not actually take place. We suggest a new set of measurements in connection with Hardy's scheme, and show that when they are actually performed, they yield strange and surprising outcomes. More generally, we claim that counterfactual paradoxes point to a deeper structure inherent to quantum mechanics characterized by weak values (Aharonov Y, Botero A, Popescu S, Reznik B, Tollaksen J, Physics Letters A, 301 (3-4): 130-138, 2002).

  19. Robust Control Feedback and Learning

    DTIC Science & Technology

    2002-11-30

    98-1-0026 5b. GRANT NUMBER Robust Control, Feedback and Learning F49620-98-1-0026 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Michael G...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 Final Report: ROBUST CONTROL FEEDBACK AND LEARNING AFOSR Grant F49620-98-1-0026 October 1...Philadelphia, PA, 2000. [16] M. G. Safonov. Recent advances in robust control, feedback and learning . In S. 0. R. Moheimani, editor, Perspectives in Robust

  20. Robustness surfaces of complex networks

    NASA Astrophysics Data System (ADS)

    Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis

    2014-09-01

    Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.

  1. Robust Object Tracking Using Valid Fragments Selection

    PubMed Central

    Li, Bo; Tian, Peng; Luo, Gang

    2016-01-01

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios. PMID:27430036

  2. Adaptive and Robust Control for Thermal Management Systems

    DTIC Science & Technology

    2006-01-01

    descriptions were developed to describe the smart cooling system components. Henry et al. (2001) developed a simulation model of powertrain cooling...proposed control strategies have been verified by simulation and validated by experimental testing. In Section 2, the cooling system model is presented to...of energy transferred to the system is controlled by the main valve mounted on the heat exchanger. The mass flow rate of condensate is proportional

  3. 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.

  4. Robust and Adaptive Guidance and Control Laws for Missile Systems

    DTIC Science & Technology

    1994-06-26

    Englewood Cliffs, NJ: Prentice-Hall, 1988. positive real lemma are developed in Sections II and HI using optimal [111 R. S. Varga . Matrix Iterative...testing certain Math, 1987. square matrices for positive definiteness related to the generalized [14] F. Alvarado , "Parallel solution of transient

  5. Adaptive Intra Refresh for Robust H.264/AVC Transmission

    NASA Astrophysics Data System (ADS)

    Song, Bin; Qin, Hao; Jiang, Xiaobing; Ma, Linhua

    An intra refresh matrix, which models the importance of each macroblock, is first created. This matrix can be used to decide the coding mode of the macroblocks. The proposed technique can greatly improve the decoded video quality over the variable and error-prone channel with high packet loss rate.

  6. 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.

  7. Robust cascade control for the horizontal motion of a vehicle with single-wheel actuators

    NASA Astrophysics Data System (ADS)

    Moseberg, Jan-Erik; Roppenecker, Günter

    2015-12-01

    The article presents a cascade control for the horizontal motion of a vehicle with single-wheel actuators. The outer control loop for the longitudinal and lateral accelerations and the yaw rate ensures a desired vehicle motion. By a combination of state feedback control and observer-based disturbance feedforward the inner control loop robustly stabilises the rotating and steering motions of the wheels in spite of unknown frictions between tyres and ground. Since the three degrees of freedom of the horizontal motion are affected by eight tyre forces, the vehicle considered is an over-actuated system. Thus additional control objectives can be realised besides the desired motion trajectory as, for example, a maximum in driving safety. The corresponding analytical tyre force allocation also guarantees real-time capability because of its relatively low computational effort. Provided suitable fault detection and isolation are available, the proposed cascade control has the potential of fault-tolerance, because the force allocation is adaptable. Another benefit results from the modular control structure, because it allows a stepwise implementation. Besides, it only requires a small number of measurements for control purposes. These measurements are the rotational speeds and steering angles of the wheels, the longitudinal and lateral acceleration and the yaw rate of the vehicle.

  8. 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…

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Visual Adaptation

    PubMed Central

    Webster, Michael A.

    2015-01-01

    Sensory systems continuously mold themselves to the widely varying contexts in which they must operate. Studies of these adaptations have played a long and central role in vision science. In part this is because the specific adaptations remain a powerful tool for dissecting vision, by exposing the mechanisms that are adapting. That is, “if it adapts, it's there.” Many insights about vision have come from using adaptation in this way, as a method. A second important trend has been the realization that the processes of adaptation are themselves essential to how vision works, and thus are likely to operate at all levels. That is, “if it's there, it adapts.” This has focused interest on the mechanisms of adaptation as the target rather than the probe. Together both approaches have led to an emerging insight of adaptation as a fundamental and ubiquitous coding strategy impacting all aspects of how we see. PMID:26858985

  14. 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.

  15. Robust Mean and Covariance Structure Analysis through Iteratively Reweighted Least Squares.

    ERIC Educational Resources Information Center

    Yuan, Ke-Hai; Bentler, Peter M.

    2000-01-01

    Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)

  16. Finite-Time Control by Observer-Based Output Feedback for Linear Discrete-Time Systems

    NASA Astrophysics Data System (ADS)

    Ichihara, Hiroyuki; Katayama, Hitoshi

    In this paper we consider finite-time stabilization and finite-time boundedness control problems for time-varying discrete-time systems. We give a set of sufficient conditions, in terms of difference LMIs, for the existence of observer-based output feedback controllers that make the system finite-time stable and finite-time bounded. We then reduce the obtained results to the ones for time-invariant discrete-time systems and derive numerically tractable sufficient conditions given by LMIs. We also show numerical examples to illustrate the design methods of observer-based output feedback controllers.

  17. Coordination of multi-agent systems under switching topologies via disturbance observer-based approach

    NASA Astrophysics Data System (ADS)

    Tang, Yutao

    2016-12-01

    In this paper, a leader-following coordination problem of heterogeneous multi-agent systems is considered under switching topologies where each agent is subject to some local (unbounded) disturbances. While these unknown disturbances may disrupt the performance of agents, a disturbance observer-based approach is employed to estimate and reject them. Varying communication topologies are also taken into consideration, and their byproduct difficulties are overcome by using common Lyapunov function techniques. According to the available information in difference cases, two disturbance observer-based protocols are proposed to solve this problem. Their effectiveness is verified by simulations.

  18. 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.

  19. Simple Robust Fixed Lag Smoothing

    DTIC Science & Technology

    1988-12-02

    SIMPLE ROBUST FIXED LAG SMOOTHING by ~N. D. Le R.D. Martin 4 TECHNICAL RlEPORT No. 149 December 1988 Department of Statistics, GN-22 Accesion For...frLsD1ist Special A- Z Simple Robust Fixed Lag Smoothing With Application To Radar Glint Noise * N. D. Le R. D. Martin Department of Statistics, GN...smoothers. The emphasis here is on fixed-lag smoothing , as opposed to the use of existing robust fixed interval smoothers (e.g., as in Martin, 1979

  20. 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...

  1. Hough transform for robust regression and automated detection

    NASA Astrophysics Data System (ADS)

    Ballester, P.

    1994-06-01

    The Hough transform is a robust algorithm for detecting multi-dimensional features in images and estimating their parameters. It is widely used in the domains of remote sensing and machine vision and could find number of applications in astrophysics. A general introduction to the Hough transform, its main variations and implementation techniques is provided. A Hough transform based robust regression method is discussed and analyzed. Also auto-adaptive, fast pattern recognition algorithms for the detection of echelle orders and automated arc line identification are presented.

  2. 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

  3. Robust Portfolio Optimization Using Pseudodistances.

    PubMed

    Toma, Aida; Leoni-Aubin, Samuela

    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.

  4. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Tradeoff on Phenotype Robustness in Biological Networks Part II: Ecological Networks.

    PubMed

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    In ecological networks, network robustness should be large enough to confer intrinsic robustness for tolerating intrinsic parameter fluctuations, as well as environmental robustness for resisting environmental disturbances, so that the phenotype stability of ecological networks can be maintained, thus guaranteeing phenotype robustness. However, it is difficult to analyze the network robustness of ecological systems because they are complex nonlinear partial differential stochastic systems. This paper develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance sensitivity in ecological networks. We found that the phenotype robustness criterion for ecological networks is that if intrinsic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations and environmental disturbances. These results in robust ecological networks are similar to that in robust gene regulatory networks and evolutionary networks even they have different spatial-time scales.

  5. 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.

  6. 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.

  7. Robustness Elasticity in Complex Networks

    PubMed Central

    Matisziw, Timothy C.; Grubesic, Tony H.; Guo, Junyu

    2012-01-01

    Network robustness refers to a network’s resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems. PMID:22808060

  8. Towards robust compressed-domain video watermarking for H.264

    NASA Astrophysics Data System (ADS)

    Noorkami, Maneli; Mersereau, Russell M.

    2006-02-01

    As H.264 digital video becomes more prevalent, the industry needs copyright protection and authentication methods that are appropriate for this standard. The goal of this paper is to propose a robust watermarking algorithm for H.264. To achieve this goal, we employ a human visual model adapted for a 4x4 DCT block to obtain a larger payload and a greater robustness while minimizing visual distortion. We use a key-dependent algorithm to select a subset of the coefficients with visual watermarking capacity for watermark embedding to obtain robustness to malicious attacks. Furthermore, we spread the watermark over frequencies and within blocks to avoid error pooling. The error pooling effect, introduced by Watson, has not been considered in previous perceptual watermarking algorithms. Our simulation results show that we can increase the payload and robustness without a noticeable change in perceptual quality by reducing this effect. We embed the watermark in the residuals to avoid decompressing the video, and to reduce the complexity of the watermarking algorithm. However, we extract the watermark from the decoded video sequence to make the algorithm robust to intraprediction mode changes. Our simulation results shows that we obtain robustness to filtering, 50% cropping, and requantization attacks.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Intracortical remodeling parameters are associated with measures of bone robustness.

    PubMed

    Goldman, Haviva M; Hampson, Naomi A; Guth, J Jared; Lin, David; Jepsen, Karl J

    2014-10-01

    Prior work identified a novel association between bone robustness and porosity, which may be part of a broader interaction whereby the skeletal system compensates for the natural variation in robustness (bone width relative to length) by modulating tissue-level mechanical properties to increase stiffness of slender bones and to reduce mass of robust bones. To further understand this association, we tested the hypothesis that the relationship between robustness and porosity is mediated through intracortical, BMU-based (basic multicellular unit) remodeling. We quantified cortical porosity, mineralization, and histomorphometry at two sites (38% and 66% of the length) in human cadaveric tibiae. We found significant correlations between robustness and several histomorphometric variables (e.g., % secondary tissue [R(2)  = 0.68, P < 0.004], total osteon area [R(2)  = 0.42, P < 0.04]) at the 66% site. Although these associations were weaker at the 38% site, significant correlations between histological variables were identified between the two sites indicating that both respond to the same global effects and demonstrate a similar character at the whole bone level. Thus, robust bones tended to have larger and more numerous osteons with less infilling, resulting in bigger pores and more secondary bone area. These results suggest that local regulation of BMU-based remodeling may be further modulated by a global signal associated with robustness, such that remodeling is suppressed in slender bones but not in robust bones. Elucidating this mechanism further is crucial for better understanding the complex adaptive nature of the skeleton, and how interindividual variation in remodeling differentially impacts skeletal aging and an individuals' potential response to prophylactic treatments.

  16. Robustness, flexibility, and sensitivity in a multifunctional motor control model.

    PubMed

    Lyttle, David N; Gill, Jeffrey P; Shaw, Kendrick M; Thomas, Peter J; Chiel, Hillel J

    2017-02-01

    Motor systems must adapt to perturbations and changing conditions both within and outside the body. We refer to the ability of a system to maintain performance despite perturbations as "robustness," and the ability of a system to deploy alternative strategies that improve fitness as "flexibility." Different classes of pattern-generating circuits yield dynamics with differential sensitivities to perturbations and parameter variation. Depending on the task and the type of perturbation, high sensitivity can either facilitate or hinder robustness and flexibility. Here we explore the role of multiple coexisting oscillatory modes and sensory feedback in allowing multiphasic motor pattern generation to be both robust and flexible. As a concrete example, we focus on a nominal neuromechanical model of triphasic motor patterns in the feeding apparatus of the marine mollusk Aplysia californica. We find that the model can operate within two distinct oscillatory modes and that the system exhibits bistability between the two. In the "heteroclinic mode," higher sensitivity makes the system more robust to changing mechanical loads, but less robust to internal parameter variations. In the "limit cycle mode," lower sensitivity makes the system more robust to changes in internal parameter values, but less robust to changes in mechanical load. Finally, we show that overall performance on a variable feeding task is improved when the system can flexibly transition between oscillatory modes in response to the changing demands of the task. Thus, our results suggest that the interplay of sensory feedback and multiple oscillatory modes can allow motor systems to be both robust and flexible in a variable environment.

  17. Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

    PubMed

    Chang, Yeong-Chan

    2005-12-01

    This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

  18. 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.

  19. 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.

  20. 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

  1. Robust Hitting with Dynamics Shaping

    NASA Astrophysics Data System (ADS)

    Yashima, Masahito; Yamawaki, Tasuku

    The present paper proposes the trajectory planning based on “the dynamics shaping” for a redundant robotic arm to hit a target robustly toward the desired direction, of which the concept is to shape the robot dynamics appropriately by changing its posture in order to achieve the robust motion. The positional error of the end-effector caused by unknown disturbances converges onto near the singular vector corresponding to its maximum singular value of the output controllability matrix of the robotic arm. Therefore, if we can control the direction of the singular vector by applying the dynamics shaping, we will be able to control the direction of the positional error of the end-effector caused by unknown disturbances. We propose a novel trajectory planning based on the dynamics shaping and verify numerically and experimentally that the robotic arm can robustly hit the target toward the desired direction with a simple open-loop control system even though the disturbance is applied.

  2. On Robust Association Testing for Quantitative Traits and Rare Variants

    PubMed Central

    Wei, Peng; Cao, Ying; Zhang, Yiwei; Xu, Zhiyuan; Kwak, Il-Youp; Boerwinkle, Eric; Pan, Wei

    2016-01-01

    With the advance of sequencing technologies, it has become a routine practice to test for association between a quantitative trait and a set of rare variants (RVs). While a number of RV association tests have been proposed, there is a dearth of studies on the robustness of RV association testing for nonnormal distributed traits, e.g., due to skewness, which is ubiquitous in cohort studies. By extensive simulations, we demonstrate that commonly used RV tests, including sequence kernel association test (SKAT) and optimal unified SKAT (SKAT-O), are not robust to heavy-tailed or right-skewed trait distributions with inflated type I error rates; in contrast, the adaptive sum of powered score (aSPU) test is much more robust. Here we further propose a robust version of the aSPU test, called aSPUr. We conduct extensive simulations to evaluate the power of the tests, finding that for a larger number of RVs, aSPU is often more powerful than SKAT and SKAT-O, owing to its high data-adaptivity. We also compare different tests by conducting association analysis of triglyceride levels using the NHLBI ESP whole-exome sequencing data. The QQ plots for SKAT and SKAT-O were severely inflated (λ = 1.89 and 1.78, respectively), while those for aSPU and aSPUr behaved normally. Due to its relatively high robustness to outliers and high power of the aSPU test, we recommend its use complementary to SKAT and SKAT-O. If there is evidence of inflated type I error rate from the aSPU test, we would recommend the use of the more robust, but less powerful, aSPUr test. PMID:27678522

  3. Robust regulation of oscillatory Min-protein patterns

    NASA Astrophysics Data System (ADS)

    Halatek, Jacob; Frey, Erwin

    2012-02-01

    Robust spatial patterning was crucial just from the beginning of cellular evolution, and is key to the development of multicellular organisms. In E. Coli, the oscillatory pole-to-pole dynamics of MinCDE proteins functionality prevent improper cell divisions apart from midcell. Min-oscillations are characterized by the remarkable robustness with which spatial patterns dynamically adapt to variations of cell geometry. Moreover, adaption, and therefore proper cell division, is independent of temperature. These observations raise fundamental questions about the underlying core mechanisms, and about the role of spatial cues. With a conceptually novel and universal approach to cellular geometries, we introduce a robust model based on experimental data, consistently explaining the mechanisms underlying pole-to-pole, striped and circular patterns, as well as the observed temperature-dependence. Contrary to prior conjectures, the model predicts that MinD and cardiolipin domains are not colocalized. The key mechanisms are transient sequestration of MinE, and highly canalized transfer of MinD between polar zones. MinD channeling enhances midcell localization and facilitates stripe formation, revealing the potential optimization process from which robust Min-oscillations originally arose.

  4. 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.

  5. 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.

  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. 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.

  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. Starfish: Robust spectroscopic inference tools

    NASA Astrophysics Data System (ADS)

    Czekala, Ian; Andrews, Sean M.; Mandel, Kaisey S.; Hogg, David W.; Green, Gregory M.

    2015-05-01

    Starfish is a set of tools used for spectroscopic inference. It robustly determines stellar parameters using high resolution spectral models and uses Markov Chain Monte Carlo (MCMC) to explore the full posterior probability distribution of the stellar parameters. Additional potential applications include other types of spectra, such as unresolved stellar clusters or supernovae spectra.

  10. Shaping robust system through evolution

    NASA Astrophysics Data System (ADS)

    Kaneko, Kunihiko

    2008-06-01

    Biological functions are generated as a result of developmental dynamics that form phenotypes governed by genotypes. The dynamical system for development is shaped through genetic evolution following natural selection based on the fitness of the phenotype. Here we study how this dynamical system is robust to noise during development and to genetic change by mutation. We adopt a simplified transcription regulation network model to govern gene expression, which gives a fitness function. Through simulations of the network that undergoes mutation and selection, we show that a certain level of noise in gene expression is required for the network to acquire both types of robustness. The results reveal how the noise that cells encounter during development shapes any network's robustness, not only to noise but also to mutations. We also establish a relationship between developmental and mutational robustness through phenotypic variances caused by genetic variation and epigenetic noise. A universal relationship between the two variances is derived, akin to the fluctuation-dissipation relationship known in physics.

  11. 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

  12. Robustness of spatial patterns in buffered reaction-diffusion systems and its reciprocity with phase plasticity

    NASA Astrophysics Data System (ADS)

    Hatakeyama, Tetsuhiro S.; Kaneko, Kunihiko

    2017-03-01

    The robustness of spatial patterns against perturbations is an indispensable property of developmental processes for organisms, which need to adapt to changing environments. Although specific mechanisms for this robustness have been extensively investigated, little is known about a general mechanism for achieving robustness in reaction-diffusion systems. Here, we propose a buffered reaction-diffusion system, in which active states of chemicals mediated by buffer molecules contribute to reactions, and demonstrate that robustness of the pattern wavelength is achieved by the dynamics of the buffer molecule. This robustness is analytically explained as a result of the scaling properties of the buffered system, which also lead to a reciprocal relationship between the wavelength's robustness and the plasticity of the spatial phase upon external perturbations. Finally, we explore the relevance of this reciprocity to biological systems.

  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. Adaptive Beamforming with Inadequate Snapshots

    NASA Astrophysics Data System (ADS)

    YU, Jing; LI, Yaan

    2017-01-01

    In array signal processing, the covariance matrix used to calculate the adaptive weights is often poor estimated when the snapshot number is inadequate. The prior environmental knowledge can be used to make the estimation more accuracy. In this paper, an alternative knowledge-aided adaptive beamforming approach that is robust to low sample support environment is proposed. In this algorithm the covariance matrix used to calculate the optimum weights is constructed by blending a sample covariance matrix and a priori structured covariance matrix. Numerical simulations demonstrate the proposed algorithm has the potential for substantial performance improvement.

  15. 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.

  16. 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.

  17. 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.

  18. META II Complexity and Adaptability

    DTIC Science & Technology

    2011-08-01

    looks for the highest peaks, Robust Design looks for the highest mesas – regions where the performance does not fall off due to small variations in...ATA 23 (Communications), ATA 24(Electrical Power), ATA 27(Flight Controls), ATA 29(Hydraulics), ATA 30(Ice and Rain Protection ),ATA 31(Indicating...though a degree of adaptation may be required. 4.5. Experimentation The experiments we have performed in the program fall into two broad categories

  19. Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

    PubMed Central

    Boutemedjet, Ayoub; Deng, Chenwei; Zhao, Baojun

    2016-01-01

    In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above. PMID:27834893

  20. Disturbance observer-based fuzzy control for flexible spacecraft combined attitude & sun tracking system

    NASA Astrophysics Data System (ADS)

    Chak, Yew-Chung; Varatharajoo, Renuganth; Razoumny, Yury

    2017-04-01

    This paper investigates the combined attitude and sun-tracking control problem in the presence of external disturbances and internal disturbances, caused by flexible appendages. A new method based on Pythagorean trigonometric identity is proposed to drive the solar arrays. Using the control input and attitude output, a disturbance observer is developed to estimate the lumped disturbances consisting of the external and internal disturbances, and then compensated by the disturbance observer-based controller via a feed-forward control. The stability analysis demonstrates that the desired attitude trajectories are followed even in the presence of external disturbance and internal flexible modes. The main features of the proposed control scheme are that it can be designed separately and incorporated into the baseline controller to form the observer-based control system, and the combined attitude and sun-tracking control is achieved without the conventional attitude actuators. The attitude and sun-tracking performance using the proposed strategy is evaluated and validated through numerical simulations. The proposed control solution can serve as a fail-safe measure in case of failure of the conventional attitude actuator, which triggered by automatic reconfiguration of the attitude control components.

  1. 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.

  2. 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.

  3. Robust background modelling in DIALS

    PubMed Central

    Parkhurst, James M.; Winter, Graeme; Waterman, David G.; Fuentes-Montero, Luis; Gildea, Richard J.; Murshudov, Garib N.; Evans, Gwyndaf

    2016-01-01

    A method for estimating the background under each reflection during integration that is robust in the presence of pixel outliers is presented. The method uses a generalized linear model approach that is more appropriate for use with Poisson distributed data than traditional approaches to pixel outlier handling in integration programs. The algorithm is most applicable to data with a very low background level where assumptions of a normal distribution are no longer valid as an approximation to the Poisson distribution. It is shown that traditional methods can result in the systematic underestimation of background values. This then results in the reflection intensities being overestimated and gives rise to a change in the overall distribution of reflection intensities in a dataset such that too few weak reflections appear to be recorded. Statistical tests performed during data reduction may mistakenly attribute this to merohedral twinning in the crystal. Application of the robust generalized linear model algorithm is shown to correct for this bias. PMID:27980508

  4. A Robust Streaming Media System

    NASA Astrophysics Data System (ADS)

    Youwei, Zhang

    Presently, application layer multicast protocols (ALM) are proposed as substitute for IP multicast and have made extraordinary achievements. Integrated with Multi-data-stream mode such as Multiple Description Coding (MDC), ALM becomes more scalable and robust in high-dynamic Internet environment compared with single data stream. Although MDC can provide a flexible data transmission style, the synchronization of different descriptions encoded from one video source is proved to be difficult due to different delay on diverse transmission paths. In this paper, an ALM system called HMDC is proposed to improve accepted video quality of streaming media, hosts can join the separate overlay trees in different layers simultaneously, then the maximum synchronized descriptions of the same layer are worked out to acquire the best video quality. Simulations implemented on Internet-like topology indicate that HMDC achieves better video quality, lower link stress, higher robustness and comparable latency compared with traditional ALM protocols.

  5. 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)

  6. Robust modular product family design

    NASA Astrophysics Data System (ADS)

    Jiang, Lan; Allada, Venkat

    2001-10-01

    This paper presents a modified Taguchi methodology to improve the robustness of modular product families against changes in customer requirements. The general research questions posed in this paper are: (1) How to effectively design a product family (PF) that is robust enough to accommodate future customer requirements. (2) How far into the future should designers look to design a robust product family? An example of a simplified vacuum product family is used to illustrate our methodology. In the example, customer requirements are selected as signal factors; future changes of customer requirements are selected as noise factors; an index called quality characteristic (QC) is set to evaluate the product vacuum family; and the module instance matrix (M) is selected as control factor. Initially a relation between the objective function (QC) and the control factor (M) is established, and then the feasible M space is systemically explored using a simplex method to determine the optimum M and the corresponding QC values. Next, various noise levels at different time points are introduced into the system. For each noise level, the optimal values of M and QC are computed and plotted on a QC-chart. The tunable time period of the control factor (the module matrix, M) is computed using the QC-chart. The tunable time period represents the maximum time for which a given control factor can be used to satisfy current and future customer needs. Finally, a robustness index is used to break up the tunable time period into suitable time periods that designers should consider while designing product families.

  7. 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.

  8. Efficient and Robust Signal Approximations

    DTIC Science & Technology

    2009-05-01

    otherwise. Remark. Permutation matrices are both orthogonal and doubly- stochastic [62]. We will now show how to further simplify the Robust Coding...reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Keywords: signal processing, image compression, independent component analysis , sparse

  9. 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.

  10. 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.

  11. Adaptation of naturally paced saccades

    PubMed Central

    Blangero, Annabelle; Herman, James P.; Wallman, Josh; Harwood, Mark R.

    2014-01-01

    In the natural environment, humans make saccades almost continuously. In many eye movement experiments, however, observers are required to fixate for unnaturally long periods of time. The resulting long and monotonous experimental sessions can become especially problematic when collecting data in a clinical setting, where time can be scarce and subjects easily fatigued. With this in mind, we tested whether the well-studied motor learning process of saccade adaptation could be induced with a dramatically shortened intertrial interval. Observers made saccades to targets that stepped left or right either ∼250 ms or ∼1,600 ms after the saccade landed. In experiment I, we tested baseline saccade parameters to four different target amplitudes (5°, 10°, 15°, and 20°) in the two timing settings. In experiments II and III, we adapted 10° saccades via 2° intrasaccadic steps either backwards or forwards, respectively. Seven subjects performed eight separate adaptation sessions (2 intertrial timings × 2 adaptation direction × 2 session trial lengths). Adaptation proceeded remarkably similarly in both timing conditions across the multiple sessions. In the faster-paced sessions, robust adaptation was achieved in under 2 min, demonstrating the efficacy of our approach to streamlining saccade adaptation experiments. Although saccade amplitudes were similar between conditions, the faster-paced condition unexpectedly resulted in significantly higher peak velocities in all subjects. This surprising finding demonstrates that the stereotyped “main sequence” relationship between saccade amplitude and peak velocity is not as fixed as originally thought. PMID:24623511

  12. 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

  13. Robust optimization model and algorithm for railway freight center location problem in uncertain environment.

    PubMed

    Liu, Xing-Cai; 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.

  14. 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.

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

    PubMed

    Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

    2015-11-20

    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.

  16. 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.

  17. A Combined Biased-Robust Estimator for Dealing with Influence and Collinearity in Regression

    DTIC Science & Technology

    1993-01-01

    Bernoulli (1777) and Bessel and Baeyer (1838). Formal rejection rules were given by Peirce (1852) and Chauvenet (1863). Thorough accounts of the early 4...1965, 1968) and Hampel (1968) formed the basis for the theory of robust estimation and extended this theory to applications such as regression. Since...Statistics, A5, 77-88. Hogg, R. V. (1974), "Adaptive Robust Procedures: A Partial Review and Some Suggestions for Future Applications and Theory

  18. 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.

  19. Measuring patient-centredness: a comparison of three observation-based instruments.

    PubMed

    Mead, N; Bower, P

    2000-01-01

    The aim of this study was to assess the reliability and validity of three different observation-based measures of patient-centredness. The three face-valid instruments were each applied to the same sample of 55 videotaped GP consultations. Associations were explored with consultation 'input' variables (e.g. patient and doctor demographic characteristics, patient health status) and 'process' variables (e.g. consultation length). The three measures demonstrated varying levels of inter-rater reliability. Reliability was proportional to training requirements. Differences in construct validity of the three measures were evident and their concurrent validity was relatively low. Researchers must exercise caution in their choice of measurement method because of differences in how the concept of 'patient-centredness' is operationalized. Greater conceptual specificity and simplification are required for meaningful, reliable measurement. The implications for research, and for assessing the quality of individual doctors' 'interpersonal' care are discussed.

  20. 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.

  1. Observer-based stabilisation of linear systems with parameter uncertainties by using enhanced LMI conditions

    NASA Astrophysics Data System (ADS)

    Kheloufi, Houria; Bedouhene, Fazia; Zemouche, Ali; Alessandri, Angelo

    2015-06-01

    This paper deals with the problem of observer-based stabilisation for linear systems with structured norm-bounded parameter uncertainties. A new design methodology is established thanks to a judicious use of some mathematical artefacts such as the well-known Young inequality and various matrix decompositions. The proposed method allows one to compute simultaneously the observer and controller gains by solving a single bilinear matrix inequality (BMI), which becomes a linear matrix inequality (LMI) by freezing some scalars. Furthermore, we show that some existing and elegant results reported in the literature can be regarded as particular cases of the stability conditions presented here. Numerical examples and evaluations of the conservatism are provided to show the effectiveness of the proposed design methodology.

  2. Disturbance observer based sliding mode control of nonlinear mismatched uncertain systems

    NASA Astrophysics Data System (ADS)

    Ginoya, Divyesh; Shendge, P. D.; Phadke, S. B.

    2015-09-01

    This paper presents a new design of multiple-surface sliding mode control for a class of nonlinear uncertain systems with mismatched uncertainties and disturbances. In the method of multiple-surface sliding mode control, it is required to compensate for the derivatives of the virtual inputs which gives rise to the so-called problem of 'explosion of terms'. In this paper a disturbance observer based multiple-surface sliding mode control is proposed to estimate the uncertainties as well as the derivative of the virtual inputs to overcome this problem. The practical stability of the overall system is proved. The effectiveness of the proposed control strategy is illustrated via simulation of a benchmark problem and comparison with other control strategies. The proposed scheme is validated by implementing it on a serial flexible joint manipulator in the laboratory.

  3. 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.

  4. 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.

  5. 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.

  6. An observer-based consensus tracking control and application to event-triggered tracking

    NASA Astrophysics Data System (ADS)

    Hu, Jiangping; Geng, Ji; Zhu, Hong

    2015-02-01

    Leader-follower mechanism provides an important framework for multi-agent consensus problems. In this paper, a consensus tracking problem is investigated for a second-order multi-agent system with a self-active leader. The input (acceleration) to the leader is assumed to be time-varying and unavailable to followers. An observer-based consensus tracking control is designed on the basis of a novel distributed velocity estimation technique. The ultimate boundedness and the stability of the tracking error system are analyzed by virtue of an Input-State-Stability (ISS) Lyapunov function approach. Then, the dynamic consensus tracking control is applied to solve an event-triggered tracking problem. Finally, some numerical simulation results are presented to demonstrate the effectiveness of the proposed consensus tracking control.

  7. 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.

  8. Inductive robust principal component analysis.

    PubMed

    Bao, Bing-Kun; Liu, Guangcan; Xu, Changsheng; Yan, Shuicheng

    2012-08-01

    In this paper we address the error correction problem that is to uncover the low-dimensional subspace structure from high-dimensional observations, which are possibly corrupted by errors. When the errors are of Gaussian distribution, Principal Component Analysis (PCA) can find the optimal (in terms of least-square-error) low-rank approximation to highdimensional data. However, the canonical PCA method is known to be extremely fragile to the presence of gross corruptions. Recently, Wright et al. established a so-called Robust Principal Component Analysis (RPCA) method, which can well handle grossly corrupted data [14]. However, RPCA is a transductive method and does not handle well the new samples which are not involved in the training procedure. Given a new datum, RPCA essentially needs to recalculate over all the data, resulting in high computational cost. So, RPCA is inappropriate for the applications that require fast online computation. To overcome this limitation, in this paper we propose an Inductive Robust Principal Component Analysis (IRPCA) method. Given a set of training data, unlike RPCA that targets on recovering the original data matrix, IRPCA aims at learning the underlying projection matrix, which can be used to efficiently remove the possible corruptions in any datum. The learning is done by solving a nuclear norm regularized minimization problem, which is convex and can be solved in polynomial time. Extensive experiments on a benchmark human face dataset and two video surveillance datasets show that IRPCA can not only be robust to gross corruptions, but also handle well the new data in an efficient way.

  9. Robust Soldier Crab Ball Gate

    NASA Astrophysics Data System (ADS)

    Gunji, Yukio-Pegio; Nishiyama, Yuta; Adamatzky, Andrew

    2011-09-01

    Based on the field observation of soldier crabs, we previously proposed a model for a swarm of soldier crabs. Here, we describe the interaction of coherent swarms in the simulation model, which is implemented in a logical gate. Because a swarm is generated by inherent perturbation, a swarm can be generated and maintained under highly perturbed conditions. Thus, the model reveals a robust logical gate rather than stable one. In addition, we show that the logical gate of swarms is also implemented by real soldier crabs (Mictyris guinotae).

  10. 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.

  11. 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

  12. 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

  13. Adaptive filters: stable but divergent

    NASA Astrophysics Data System (ADS)

    Rupp, Markus

    2015-12-01

    The pros and cons of a quadratic error measure in the context of various applications have often been discussed. In this tutorial, we argue that it is not only a suboptimal but definitely the wrong choice when describing the stability behavior of adaptive filters. We take a walk through the past and recent history of adaptive filters and present 14 canonical forms of adaptive algorithms and even more variants thereof contrasting their mean-square with their l 2-stability conditions. In particular, in safety critical applications, the convergence in the mean-square sense turns out to provide wrong results, often not leading to stability at all. Only the robustness concept with its l 2-stability conditions ensures the absence of divergence.

  14. 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.

  15. Environmentally Adaptive Reverberation Nulling

    DTIC Science & Technology

    2006-04-15

    Kim, H.C. Song, and W.A. Kuperman, “Adaptive time-reversal mirror,” J. Acoust. Soc. Am. 109(5): 1817-1825 (2001). [6] S. Kim, G. Edelmann , W.S...W.A. Kuperman, W.S. Hodgkiss, H.C. Song, G.F. Edelmann , and T. Akal, “Robust time reversal focusing in the ocean,” J. Acoust. Soc. Am. 114(1): 145-157...IEEE J. Oceanic Engr. 28(2): 246-249 (2003). [10] S. Kim, W.A. Kuperman, W.S. Hodgkiss, H.C. Spong, G.F. Edelmann , and T. Akal, “Echo-to

  16. 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.

  17. Consensus formation on adaptive networks

    NASA Astrophysics Data System (ADS)

    Kozma, Balazs; Barrat, Alain

    2008-01-01

    The structure of a network can significantly influence the properties of the dynamical processes that take place on them. While many studies have been paid to this influence, much less attention has been devoted to the interplay and feedback mechanisms between dynamical processes and network topology on adaptive networks. Adaptive rewiring of links can happen in real life systems such as acquaintance networks, where people are more likely to maintain a social connection if their views and values are similar. In our study, we consider different variants of a model for consensus formation. Our investigations reveal that the adaptation of the network topology fosters cluster formation by enhancing communication between agents of similar opinion, although it also promotes the division of these clusters. The temporal behavior is also strongly affected by adaptivity: while, on static networks, it is influenced by percolation properties, on adaptive networks, both the early and late time evolutions of the system are determined by the rewiring process. The investigation of a variant of the model reveals that the scenarios of transitions between consensus and polarized states are more robust on adaptive networks.

  18. Robust fusion with reliabilities weights

    NASA Astrophysics Data System (ADS)

    Grandin, Jean-Francois; Marques, Miguel

    2002-03-01

    The reliability is a value of the degree of trust in a given measurement. We analyze and compare: ML (Classical Maximum Likelihood), MLE (Maximum Likelihood weighted by Entropy), MLR (Maximum Likelihood weighted by Reliability), MLRE (Maximum Likelihood weighted by Reliability and Entropy), DS (Credibility Plausibility), DSR (DS weighted by reliabilities). The analysis is based on a model of a dynamical fusion process. It is composed of three sensors, which have each it's own discriminatory capacity, reliability rate, unknown bias and measurement noise. The knowledge of uncertainties is also severely corrupted, in order to analyze the robustness of the different fusion operators. Two sensor models are used: the first type of sensor is able to estimate the probability of each elementary hypothesis (probabilistic masses), the second type of sensor delivers masses on union of elementary hypotheses (DS masses). In the second case probabilistic reasoning leads to sharing the mass abusively between elementary hypotheses. Compared to the classical ML or DS which achieves just 50% of correct classification in some experiments, DSR, MLE, MLR and MLRE reveals very good performances on all experiments (more than 80% of correct classification rate). The experiment was performed with large variations of the reliability coefficients for each sensor (from 0 to 1), and with large variations on the knowledge of these coefficients (from 0 0.8). All four operators reveal good robustness, but the MLR reveals to be uniformly dominant on all the experiments in the Bayesian case and achieves the best mean performance under incomplete a priori information.

  19. Robust Inflation from fibrous strings

    SciTech Connect

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

    2016-05-13

    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 n{sub s} of the form r∝(n{sub s}−1){sup 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≲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.

  20. Bayesian robust principal component analysis.

    PubMed

    Ding, Xinghao; He, Lihan; Carin, Lawrence

    2011-12-01

    A hierarchical Bayesian model is considered for decomposing a matrix into low-rank and sparse components, assuming the observed matrix is a superposition of the two. The matrix is assumed noisy, with unknown and possibly non-stationary noise statistics. The Bayesian framework infers an approximate representation for the noise statistics while simultaneously inferring the low-rank and sparse-outlier contributions; the model is robust to a broad range of noise levels, without having to change model hyperparameter settings. In addition, the Bayesian framework allows exploitation of additional structure in the matrix. For example, in video applications each row (or column) corresponds to a video frame, and we introduce a Markov dependency between consecutive rows in the matrix (corresponding to consecutive frames in the video). The properties of this Markov process are also inferred based on the observed matrix, while simultaneously denoising and recovering the low-rank and sparse components. We compare the Bayesian model to a state-of-the-art optimization-based implementation of robust PCA; considering several examples, we demonstrate competitive performance of the proposed model.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. An asymptotic observer-based monitoring scheme for a class of plug flow reactors.

    PubMed

    Aguilar-Garnica, Efrén; García-Sandoval, Juan Paulo; Aceves-Lara, César Arturo; Escalante, Froylán Mario E

    2012-01-01

    In this paper a monitoring tool is designed for a class of plug flow reactors whose mathematical model is described by a set of first-order partial differential equations with different coefficients in the convective terms. The infinite dimensional structure of such a tool is derived according to the methodology established in the design of the well-known asymptotic observer. As a consequence, it preserves the robustness of the aforementioned observer against the lack of information of the nonlinear terms involved in the model. The original structure of the estimator is then represented as a couple of integral equations by means of the method of characteristics and its behaviour is analyzed through simulation experiments. These simulations show that the mean square observation error is 0.58 when the proposed observer is implemented in a solid-waste anaerobic digestion process to estimate the evolution of biomass concentration.

  7. 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.

  8. Adaptation of adaptive optics systems.

    NASA Astrophysics Data System (ADS)

    Xin, Yu; Zhao, Dazun; Li, Chen

    1997-10-01

    In the paper, a concept of an adaptation of adaptive optical system (AAOS) is proposed. The AAOS has certain real time optimization ability against the variation of the brightness of detected objects m, atmospheric coherence length rO and atmospheric time constant τ by means of changing subaperture number and diameter, dynamic range, and system's temporal response. The necessity of AAOS using a Hartmann-Shack wavefront sensor and some technical approaches are discussed. Scheme and simulation of an AAOS with variable subaperture ability by use of both hardware and software are presented as an example of the system.

  9. 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.

  10. 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.

  11. 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.

  12. Phase Error Correction for Approximated Observation-Based Compressed Sensing Radar Imaging

    PubMed Central

    Li, Bo; Liu, Falin; Zhou, Chongbin; Lv, Yuanhao; Hu, Jingqiu

    2017-01-01

    Defocus of the reconstructed image of synthetic aperture radar (SAR) occurs in the presence of the phase error. In this work, a phase error correction method is proposed for compressed sensing (CS) radar imaging based on approximated observation. The proposed method has better image focusing ability with much less memory cost, compared to the conventional approaches, due to the inherent low memory requirement of the approximated observation operator. The one-dimensional (1D) phase error correction for approximated observation-based CS-SAR imaging is first carried out and it can be conveniently applied to the cases of random-frequency waveform and linear frequency modulated (LFM) waveform without any a priori knowledge. The approximated observation operators are obtained by calculating the inverse of Omega-K and chirp scaling algorithms for random-frequency and LFM waveforms, respectively. Furthermore, the 1D phase error model is modified by incorporating a priori knowledge and then a weighted 1D phase error model is proposed, which is capable of correcting two-dimensional (2D) phase error in some cases, where the estimation can be simplified to a 1D problem. Simulation and experimental results validate the effectiveness of the proposed method in the presence of 1D phase error or weighted 1D phase error. PMID:28304353

  13. 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.

  14. Phase Error Correction for Approximated Observation-Based Compressed Sensing Radar Imaging.

    PubMed

    Li, Bo; Liu, Falin; Zhou, Chongbin; Lv, Yuanhao; Hu, Jingqiu

    2017-03-17

    Defocus of the reconstructed image of synthetic aperture radar (SAR) occurs in the presence of the phase error. In this work, a phase error correction method is proposed for compressed sensing (CS) radar imaging based on approximated observation. The proposed method has better image focusing ability with much less memory cost, compared to the conventional approaches, due to the inherent low memory requirement of the approximated observation operator. The one-dimensional (1D) phase error correction for approximated observation-based CS-SAR imaging is first carried out and it can be conveniently applied to the cases of random-frequency waveform and linear frequency modulated (LFM) waveform without any a priori knowledge. The approximated observation operators are obtained by calculating the inverse of Omega-K and chirp scaling algorithms for random-frequency and LFM waveforms, respectively. Furthermore, the 1D phase error model is modified by incorporating a priori knowledge and then a weighted 1D phase error model is proposed, which is capable of correcting two-dimensional (2D) phase error in some cases, where the estimation can be simplified to a 1D problem. Simulation and experimental results validate the effectiveness of the proposed method in the presence of 1D phase error or weighted 1D phase error.

  15. 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.

  16. 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.

  17. Probabilistic Reasoning for Plan Robustness

    NASA Technical Reports Server (NTRS)

    Schaffer, Steve R.; Clement, Bradley J.; Chien, Steve A.

    2005-01-01

    A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.

  18. 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.

  19. Advances in robust flight design

    NASA Technical Reports Server (NTRS)

    Wong, Kelvin K.; Dhand, Sanjeev K.

    1991-01-01

    Current launch vehicle trajectory design philosophies, generally based on maximizing payload capability, result in an expensive and time-consuming iteration in trajectory design for each mission. However, for a launch system that is not performance-driven, a flight design that is robust to variations in missions and provides single-engine-out capability can be highly cost-effective. This philosophy has led to the development of two flight design concepts to reduce recurring costs: standard trajectories and command multiplier steering. Preliminary analyses of these two concepts had proven the feasibility and showed encouraging results in applications to an Advanced Launch System vehicle. Recent progress has demonstrated the effective and efficient integration of the two concepts with minimal payload penalty.

  20. 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.

  1. Towards designing robust coupled networks.

    PubMed

    Schneider, Christian M; Yazdani, Nuri; Araújo, Nuno A M; Havlin, Shlomo; Herrmann, Hans J

    2013-01-01

    Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy.

  2. Towards designing robust coupled networks

    PubMed Central

    Schneider, Christian M.; Yazdani, Nuri; Araújo, Nuno A. M.; Havlin, Shlomo; Herrmann, Hans J.

    2013-01-01

    Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy. PMID:23752705

  3. Towards designing robust coupled networks

    NASA Astrophysics Data System (ADS)

    Schneider, Christian M.; Yazdani, Nuri; Araújo, Nuno A. M.; Havlin, Shlomo; Herrmann, Hans J.

    2013-06-01

    Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy.

  4. 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.

  5. 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.

  6. Robust stochastic mine production scheduling

    NASA Astrophysics Data System (ADS)

    Kumral, Mustafa

    2010-06-01

    The production scheduling of open pit mines aims to determine the extraction sequence of blocks such that the net present value (NPV) of a mining project is maximized under capacity and access constraints. This sequencing has significant effect on the profitability of the mining venture. However, given that the values of coefficients in the optimization procedure are obtained in a medium of sparse data and unknown future events, implementations based on deterministic models may lead to destructive consequences to the company. In this article, a robust stochastic optimization (RSO) approach is used to deal with mine production scheduling in a manner such that the solution is insensitive to changes in input data. The approach seeks a trade off between optimality and feasibility. The model is demonstrated on a case study. The findings showed that the approach can be used in mine production scheduling problems efficiently.

  7. 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.

  8. 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.

  9. Building Robust Systems with Fallible Construction (Elaboration de systemes informatiques robustes a l’architecutre faillible)

    DTIC Science & Technology

    2008-04-01

    IST-047 Building Robust Systems with Fallible Construction (Elaboration de systèmes informatiques robustes à l’architecture faillible) Final...IST-047 Building Robust Systems with Fallible Construction (Elaboration de systèmes informatiques robustes à l’architecture faillible...and cost investments. ES - 2 RTO-TR-IST-047 Elaboration de systèmes informatiques robustes à l’architecture faillible (RTO-TR-IST-047

  10. Robust mainlobe interference suppression for coherent interference environment

    NASA Astrophysics Data System (ADS)

    Wang, Yasen; Bao, Qinglong; Chen, Zengping

    2016-12-01

    A mainlobe interference suppression method is proposed in this paper, which can still work when the signal of interest (SOI) is present in the training data. In this method, the iterative adaptive approach (IAA) is applied to spatial spectrum estimation at first. Then, IAA spatial spectrum is used to reconstruct the interference-plus-noise covariance matrix (INCM). Next, the eigenvector associated with mainlobe interference in INCM is determined, and the eigen-projection matrix can be calculated to suppress the mainlobe interference. Meanwhile, the sidelobe-interference-plus-noise covariance matrix (SINCM) can be reconstructed. Finally, the adaptive weight vector is obtained. One main advantage is that the proposed method can deal with coherent mainlobe interference and sidelobe interferences simultaneously. Simulation results demonstrate the effectiveness and robustness of the proposed method.

  11. Adaptive equalization

    NASA Astrophysics Data System (ADS)

    Qureshi, S. U. H.

    1985-09-01

    Theoretical work which has been effective in improving data transmission by telephone and radio links using adaptive equalization (AE) techniques is reviewed. AE has been applied to reducing the temporal dispersion effects, such as intersymbol interference, caused by the channel accessed. Attention is given to the Nyquist telegraph transmission theory, least mean square error adaptive filtering and the theory and structure of linear receive and transmit filters for reducing error. Optimum nonlinear receiver structures are discussed in terms of optimality criteria as a function of error probability. A suboptimum receiver structure is explored in the form of a decision-feedback equalizer. Consideration is also given to quadrature amplitude modulation and transversal equalization for receivers.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. An Observational Based Assessment of In-situ Photochemical Ozone Productivity in the European Boundary Layer

    NASA Astrophysics Data System (ADS)

    Rickard, A. R.; Monks, P. S.; Jonson, J. E.

    2003-04-01

    Empirical observational-based indicator relationships have been used over the past decade in order to investigate ozone production sensitivities to different NO_x/VOC levels. If such relationships can be proven to show marked and consistently different values under different NO_x- and VOC-limited regimes over a broad variety of conditions and geographical locations, then O_3-NO_x-VOC sensitivities and ozone production trends can be determined relatively quickly and simply from measurements rather than from complex models. Such correlations would also provide invaluable measurement data to test the accuracy of model chemistry sensitivities. The tracer indicator relationships O_3/NO_z, H_2O_2/HCHO, H_2O_2/NO_z and O_3/2H_2O_2+NO_z have principally been investigated using data from the Eastern Atlantic Summer/Spring Experiments (EASE 96 and 97 respectively), which took place at Mace Head, on the west coast of Ireland. In order to study the chemistry occurring in the different air masses arriving at Mace Head, minute-averaged data were divided up into five wind sectors according to wind direction and speed. The measurements were additionally segregated using a back trajectory classification method in order to identify the pollution regimes encountered. Some of the calculated results have been compared and contrasted to those calculated from data measured under southern hemispheric "baseline" conditions, collected during the Southern Ocean Atmospheric Photochemistry EXperiment (SOAPEX 2), which took place at Cape Grim on the Tasmanian coast in the Austral summer of 1999 and from the Terrestrial Initiative in Global Environmental Research program (TIGER 95) which took place at Weybourne on the North Norfolk coast in summer 1995. Finally, the above observed indicator ratios, calculated from hourly values for EASE 97, have been compared to those calculated from model data from the EMEP-E regional model (DNMI) for May 1997.

  20. 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.

  1. 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

  2. Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

    NASA Technical Reports Server (NTRS)

    Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

    2009-01-01

    This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

  3. Relationship of cranial robusticity to cranial form, geography and climate in Homo sapiens.

    PubMed

    Baab, Karen L; Freidline, Sarah E; Wang, Steven L; Hanson, Timothy

    2010-01-01

    Variation in cranial robusticity among modern human populations is widely acknowledged but not well-understood. While the use of "robust" cranial traits in hominin systematics and phylogeny suggests that these characters are strongly heritable, this hypothesis has not been tested. Alternatively, cranial robusticity may be a response to differences in diet/mastication or it may be an adaptation to cold, harsh environments. This study quantifies the distribution of cranial robusticity in 14 geographically widespread human populations, and correlates this variation with climatic variables, neutral genetic distances, cranial size, and cranial shape. With the exception of the occipital torus region, all traits were positively correlated with each other, suggesting that they should not be treated as individual characters. While males are more robust than females within each of the populations, among the independent variables (cranial shape, size, climate, and neutral genetic distances), only shape is significantly correlated with inter-population differences in robusticity. Two-block partial least-squares analysis was used to explore the relationship between cranial shape (captured by three-dimensional landmark data) and robusticity across individuals. Weak support was found for the hypothesis that robusticity was related to mastication as the shape associated with greater robusticity was similar to that described for groups that ate harder-to-process diets. Specifically, crania with more prognathic faces, expanded glabellar and occipital regions, and (slightly) longer skulls were more robust than those with rounder vaults and more orthognathic faces. However, groups with more mechanically demanding diets (hunter-gatherers) were not always more robust than groups practicing some form of agriculture.

  4. 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

  5. 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

  6. Robustness, canalyzing functions and systems design.

    PubMed

    Rauh, Johannes; Ay, Nihat

    2014-06-01

    We study a notion of knockout robustness of a stochastic map (Markov kernel) that describes a system of several input random variables and one output random variable. Robustness requires that the behaviour of the system does not change if one or several of the input variables are knocked out. Gibbs potentials are used to give a mechanistic description of the behaviour of the system after knockouts. Robustness imposes structural constraints on these potentials. We show that robust systems can be described in terms of suitable interaction families of Gibbs potentials, which allows us to address the problem of systems design. Robustness is also characterized by conditional independence constraints on the joint distribution of input and output. The set of all probability distributions corresponding to robust systems can be decomposed into a finite union of components, and we find parametrizations of the components.

  7. A network property necessary for concentration robustness

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    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.

  8. Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

    DTIC Science & Technology

    2015-05-22

    AFRL-AFOSR-VA-TR-2015-0282 Complexity, Robustness, and Multistability in Network Systems with Switching Topologies A Hierarchical Hybrid Control ...concentrated on the development of a unified discontinuous dynamical framework for nonlinear network systems. In particular, control algorithms were... network systems, large-scale systems, adaptive control , discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF

  9. 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…

  10. Robust synchronization of chaotic Lur'e systems via delayed feedback control

    NASA Astrophysics Data System (ADS)

    Chen, Cailian; Feng, Gang; Guan, Xinping

    2004-02-01

    This Letter presents a robust synchronization method for a class of chaotic Lur'e systems based on its T-S fuzzy model and the delayed feedback control (DFC) scheme. The controlled slave system can adaptively track the master system under the circumstances of system uncertainties and external disturbances.

  11. Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in Terms of Phenotypic Variances

    NASA Astrophysics Data System (ADS)

    Kaneko, Kunihiko

    2012-09-01

    The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The relationship suggests a link between robustness to noise and to mutation, since robustness can be defined by the sharpness of the distribution of the phenotype. Next, the proportionality between the variances is demonstrated to also hold over expressions of different genes (phenotypic traits) when the system acquires robustness through the evolution. Then, evolution under environmental variation is numerically investigated and it is found that both the adaptability to a novel environment and the robustness are made compatible when a certain degree of phenotypic fluctuations exists due to noise. The highest adaptability is achieved at a certain noise level at which the gene expression dynamics are near the critical state to lose the robustness. Based on our results, we revisit Waddington's canalization and genetic assimilation with regard to the two types of phenotypic fluctuations.

  12. 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.

  13. 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.

  14. Designing for Reliability and Robustness

    NASA Technical Reports Server (NTRS)

    Svetlik, Randall G.; Moore, Cherice; Williams, Antony

    2017-01-01

    Long duration spaceflight has a negative effect on the human body, and exercise countermeasures are used on-board the International Space Station (ISS) to minimize bone and muscle loss, combatting these effects. Given the importance of these hardware systems to the health of the crew, this equipment must continue to be readily available. Designing spaceflight exercise hardware to meet high reliability and availability standards has proven to be challenging throughout the time the crewmembers have been living on ISS beginning in 2000. Furthermore, restoring operational capability after a failure is clearly time-critical, but can be problematic given the challenges of troubleshooting the problem from 220 miles away. Several best-practices have been leveraged in seeking to maximize availability of these exercise systems, including designing for robustness, implementing diagnostic instrumentation, relying on user feedback, and providing ample maintenance and sparing. These factors have enhanced the reliability of hardware systems, and therefore have contributed to keeping the crewmembers healthy upon return to Earth. This paper will review the failure history for three spaceflight exercise countermeasure systems identifying lessons learned that can help improve future systems. Specifically, the Treadmill with Vibration Isolation and Stabilization System (TVIS), Cycle Ergometer with Vibration Isolation and Stabilization System (CEVIS), and the Advanced Resistive Exercise Device (ARED) will be reviewed, analyzed, and conclusions identified so as to provide guidance for improving future exercise hardware designs. These lessons learned, paired with thorough testing, offer a path towards reduced system down-time.

  15. A Robust, Microwave Rain Gauge

    NASA Astrophysics Data System (ADS)

    Mansheim, T. J.; Niemeier, J. J.; Kruger, A.

    2008-12-01

    Researchers at The University of Iowa have developed an all-electronic rain gauge that uses microwave sensors operating at either 10 GHz or 23 GHz, and measures the Doppler shift caused by falling raindrops. It is straightforward to interface these sensors with conventional data loggers, or integrate them into a wireless sensor network. A disadvantage of these microwave rain gauges is that they consume significant power when they are operating. However, this may be partially negated by using data loggers' or sensors networks' sleep-wake-sleep mechanism. Advantages of the microwave rain gauges are that one can make them very robust, they cannot clog, they don't have mechanical parts that wear out, and they don't have to be perfectly level. Prototype microwave rain gauges were collocated with tipping-bucket rain gauges, and data were collected for two seasons. At higher rain rates, microwave rain gauge measurements compare well with tipping-bucket measurements. At lower rain rates, the microwave rain gauges provide more detailed information than tipping buckets, which quantize measurement typically in 1 tip per 0.01 inch, or 1 tip per mm of rainfall.

  16. Robust Face Sketch Style Synthesis.

    PubMed

    Shengchuan Zhang; Xinbo Gao; Nannan Wang; Jie Li

    2016-01-01

    Heterogeneous image conversion is a critical issue in many computer vision tasks, among which example-based face sketch style synthesis provides a convenient way to make artistic effects for photos. However, existing face sketch style synthesis methods generate stylistic sketches depending on many photo-sketch pairs. This requirement limits the generalization ability of these methods to produce arbitrarily stylistic sketches. To handle such a drawback, we propose a robust face sketch style synthesis method, which can convert photos to arbitrarily stylistic sketches based on only one corresponding template sketch. In the proposed method, a sparse representation-based greedy search strategy is first applied to estimate an initial sketch. Then, multi-scale features and Euclidean distance are employed to select candidate image patches from the initial estimated sketch and the template sketch. In order to further refine the obtained candidate image patches, a multi-feature-based optimization model is introduced. Finally, by assembling the refined candidate image patches, the completed face sketch is obtained. To further enhance the quality of synthesized sketches, a cascaded regression strategy is adopted. Compared with the state-of-the-art face sketch synthesis methods, experimental results on several commonly used face sketch databases and celebrity photos demonstrate the effectiveness of the proposed method.

  17. Nanotechnology Based Environmentally Robust Primers

    SciTech Connect

    Barbee, T W Jr; Gash, A E; Satcher, J H Jr; Simpson, R L

    2003-03-18

    An initiator device structure consisting of an energetic metallic nano-laminate foil coated with a sol-gel derived energetic nano-composite has been demonstrated. The device structure consists of a precision sputter deposition synthesized nano-laminate energetic foil of non-toxic and non-hazardous metals along with a ceramic-based energetic sol-gel produced coating made up of non-toxic and non-hazardous components such as ferric oxide and aluminum metal. Both the nano-laminate and sol-gel technologies are versatile commercially viable processes that allow the ''engineering'' of properties such as mechanical sensitivity and energy output. The nano-laminate serves as the mechanically sensitive precision igniter and the energetic sol-gel functions as a low-cost, non-toxic, non-hazardous booster in the ignition train. In contrast to other energetic nanotechnologies these materials can now be safely manufactured at application required levels, are structurally robust, have reproducible and engineerable properties, and have excellent aging characteristics.

  18. Fast Robust PCA on Graphs

    NASA Astrophysics Data System (ADS)

    Shahid, Nauman; Perraudin, Nathanael; Kalofolias, Vassilis; Puy, Gilles; Vandergheynst, Pierre

    2016-06-01

    Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the curse of dimensionality. However, often such methods are accompanied with three different problems: high computational complexity (usually associated with the nuclear norm minimization), non-convexity (for matrix factorization methods) and susceptibility to gross corruptions in the data. In this paper we propose a principal component analysis (PCA) based solution that overcomes these three issues and approximates a low-rank recovery method for high dimensional datasets. We target the low-rank recovery by enforcing two types of graph smoothness assumptions, one on the data samples and the other on the features by designing a convex optimization problem. The resulting algorithm is fast, efficient and scalable for huge datasets with O(nlog(n)) computational complexity in the number of data samples. It is also robust to gross corruptions in the dataset as well as to the model parameters. Clustering experiments on 7 benchmark datasets with different types of corruptions and background separation experiments on 3 video datasets show that our proposed model outperforms 10 state-of-the-art dimensionality reduction models. Our theoretical analysis proves that the proposed model is able to recover approximate low-rank representations with a bounded error for clusterable data.

  19. 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.

  20. Observation-based Estimate of Climate Sensitivity with a Scaling Climate Response Function

    NASA Astrophysics Data System (ADS)

    Hébert, Raphael; Lovejoy, Shaun

    2016-04-01

    To properly adress the anthropogenic impacts upon the earth system, an estimate of the climate sensitivity to radiative forcing is essential. Observation-based estimates of climate sensitivity are often limited by their ability to take into account the slower response of the climate system imparted mainly by the large thermal inertia of oceans, they are nevertheless essential to provide an alternative to estimates from global circulation models and increase our confidence in estimates of climate sensitivity by the multiplicity of approaches. It is straightforward to calculate the Effective Climate Sensitivity(EffCS) as the ratio of temperature change to the change in radiative forcing; the result is almost identical to the Transient Climate Response(TCR), but it underestimates the Equilibrium Climate Sensitivity(ECS). A study of global mean temperature is thus presented assuming a Scaling Climate Response Function to deterministic radiative forcing. This general form is justified as there exists a scaling symmetry respected by the dynamics, and boundary conditions, over a wide range of scales and it allows for long-range dependencies while retaining only 3 parameter which are estimated empirically. The range of memory is modulated by the scaling exponent H. We can calculate, analytically, a one-to-one relation between the scaling exponent H and the ratio of EffCS to TCR and EffCS to ECS. The scaling exponent of the power law is estimated by a regression of temperature as a function of forcing. We consider for the analysis 4 different datasets of historical global mean temperature and 100 scenario runs of the Coupled Model Intercomparison Project Phase 5 distributed among the 4 Representative Concentration Pathways(RCP) scenarios. We find that the error function for the estimate on historical temperature is very wide and thus, many scaling exponent can be used without meaningful changes in the fit residuals of historical temperatures; their response in the year 2100

  1. 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.

  2. Robust web image/video super-resolution.

    PubMed

    Xiong, Zhiwei; Sun, Xiaoyan; Wu, Feng

    2010-08-01

    This paper proposes a robust single-image super-resolution method for enlarging low quality web image/video degraded by downsampling and compression. To simultaneously improve the resolution and perceptual quality of such web image/video, we bring forward a practical solution which combines adaptive regularization and learning-based super-resolution. The contribution of this work is twofold. First, we propose to analyze the image energy change characteristics during the iterative regularization process, i.e., the energy change ratio between primitive (e.g., edges, ridges and corners) and nonprimitive fields. Based on the revealed convergence property of the energy change ratio, appropriate regularization strength can then be determined to well balance compression artifacts removal and primitive components preservation. Second, we verify that this adaptive regularization can steadily and greatly improve the pair matching accuracy in learning-based super-resolution. Consequently, their combination effectively eliminates the quantization noise and meanwhile faithfully compensates the missing high-frequency details, yielding robust super-resolution performance in the compression scenario. Experimental results demonstrate that our solution produces visually pleasing enlargements for various web images/videos.

  3. A genome wide dosage suppressor network reveals genomic robustness

    PubMed Central

    Patra, Biranchi; Kon, Yoshiko; Yadav, Gitanjali; Sevold, Anthony W.; Frumkin, Jesse P.; Vallabhajosyula, Ravishankar R.; Hintze, Arend; Østman, Bjørn; Schossau, Jory; Bhan, Ashish; Marzolf, Bruz; Tamashiro, Jenna K.; Kaur, Amardeep; Baliga, Nitin S.; Grayhack, Elizabeth J.; Adami, Christoph; Galas, David J.; Raval, Alpan; Phizicky, Eric M.; Ray, Animesh

    2017-01-01

    Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures. PMID:27899637

  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. 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.

  6. 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.

  7. 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

  8. Animal density and track counts: understanding the nature of observations based on animal movements.

    PubMed

    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

  9. Recursive architecture for large-scale adaptive system

    NASA Astrophysics Data System (ADS)

    Hanahara, Kazuyuki; Sugiyama, Yoshihiko

    1994-09-01

    'Large scale' is one of major trends in the research and development of recent engineering, especially in the field of aerospace structural system. This term expresses the large scale of an artifact in general, however, it also implies the large number of the components which make up the artifact in usual. Considering a large scale system which is especially used in remote space or deep-sea, such a system should be adaptive as well as robust by itself, because its control as well as maintenance by human operators are not easy due to the remoteness. An approach to realizing this large scale, adaptive and robust system is to build the system as an assemblage of components which are respectively adaptive by themselves. In this case, the robustness of the system can be achieved by using a large number of such components and suitable adaptation as well as maintenance strategies. Such a system gathers many research's interest and their studies such as decentralized motion control, configurating algorithm and characteristics of structural elements are reported. In this article, a recursive architecture concept is developed and discussed towards the realization of large scale system which consists of a number of uniform adaptive components. We propose an adaptation strategy based on the architecture and its implementation by means of hierarchically connected processing units. The robustness and the restoration from degeneration of the processing unit are also discussed. Two- and three-dimensional adaptive truss structures are conceptually designed based on the recursive architecture.

  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. 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.

  13. 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.

  14. Noise and robustness in phyllotaxis.

    PubMed

    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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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…

  1. Robust Controller Design for Hemispherical Resonator Gyroscope

    DTIC Science & Technology

    2011-11-01

    f v Figure 1. Operating principle of HRG Robust Controller Design for Hemispherical Resonator Gyroscope Chul Hyun1), Byung ...Petersburg, Russia.: 26-34 4) Chul Hyun. 2011. Design of Robust Digital Controller for Hemispherical Resonator Gyroscopes, Ph.D. dissertation, Seoul

  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.

  3. 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.

  4. Robust GPS carrier tracking under ionospheric scintillation

    NASA Astrophysics Data System (ADS)

    Susi, M.; Andreotti, M.; Aquino, M. H.; Dodson, A.

    2013-12-01

    Small scale irregularities present in the ionosphere can induce fast and unpredictable fluctuations of Radio Frequency (RF) signal phase and amplitude. This phenomenon, known as scintillation, can degrade the performance of a GPS receiver leading to cycle slips, increasing the tracking error and also producing a complete loss of lock. In the most severe scenarios, if the tracking of multiple satellites links is prevented, outages in the GPS service can also occur. In order to render a GPS receiver more robust under scintillation, particular attention should be dedicated to the design of the carrier tracking stage, that is the receiver's part most sensitive to these types of phenomenon. This paper exploits the reconfigurability and flexibility of a GPS software receiver to develop a tracking algorithm that is more robust under ionospheric scintillation. For this purpose, first of all, the scintillation level is monitored in real time. Indeed the carrier phase and the post correlation terms obtained by the PLL (Phase Locked Loop) are used to estimate phi60 and S4 [1], the scintillation indices traditionally used to quantify the level of phase and amplitude scintillations, as well as p and T, the spectral parameters of the fluctuations PSD. The effectiveness of the scintillation parameter computation is confirmed by comparing the values obtained by the software receiver and the ones provided by a commercial scintillation monitoring, i.e. the Septentrio PolarxS receiver [2]. Then the above scintillation parameters and the signal carrier to noise density are exploited to tune the carrier tracking algorithm. In case of very weak signals the FLL (Frequency Locked Loop) scheme is selected in order to maintain the signal lock. Otherwise an adaptive bandwidth Phase Locked Loop (PLL) scheme is adopted. The optimum bandwidth for the specific scintillation scenario is evaluated in real time by exploiting the Conker formula [1] for the tracking jitter estimation. The performance

  5. Stochastic Satbility and Performance Robustness of Linear Multivariable Systems

    NASA Technical Reports Server (NTRS)

    Ryan, Laurie E.; Stengel, Robert F.

    1990-01-01

    Stochastic robustness, a simple technique used to estimate the robustness of linear, time invariant systems, is applied to a single-link robot arm control system. Concepts behind stochastic stability robustness are extended to systems with estimators and to stochastic performance robustness. Stochastic performance robustness measures based on classical design specifications are introduced, and the relationship between stochastic robustness measures and control system design parameters are discussed. The application of stochastic performance robustness, and the relationship between performance objectives and design parameters are demonstrated by means of example. The results prove stochastic robustness to be a good overall robustness analysis method that can relate robustness characteristics to control system design parameters.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. A robust myoelectric pattern recognition using online sequential extreme learning machine for finger movement classification.

    PubMed

    Anam, Khairul; Al-Jumaily, Adel

    2015-01-01

    A robust myoelectric pattern-recognition-system requires a system that should work in the real application as good as in the laboratory. However, this demand should be handled properly and rigorously to achieve a robust myoelectric system. Electrode shift is an issue that usually emerges when dealing with robustness issue. In daily life, the placement of electrodes becomes a significant issue that can downgrade the performance of the system. This paper proposed a new way to overcome the robustness issue by conducting an update to the system to anticipate changes in the future such as electrode shift, improvement in muscle strength or any other issue. Such update will be used to generate an adaptation. The adaptation is done according to the user's need by employing an online sequential extreme learning (OS-ELM) to learn the training data chunk by chunk. OS-ELM enables the myoelectric system to learn from a small number of data to avoid cumbersome training process. The day-to-day experiment shows that the proposed system can maintain its performance on average accuracy around 85% whereas the non-adaptive system could not.

  12. Adaptive tracking of narrowband HF channel response

    NASA Astrophysics Data System (ADS)

    Arikan, F.; Arikan, O.

    2003-12-01

    Estimation of channel impulse response constitutes a first step in computation of scattering function, channel equalization, elimination of multipath, and optimum detection and identification of transmitted signals through the HF channel. Due to spatial and temporal variations, HF channel impulse response has to be estimated adaptively. Based on developed state-space and measurement models, an adaptive Kalman filter is proposed to track the HF channel variation in time. Robust methods of initialization and adaptively adjusting the noise covariance in the system dynamics are proposed. In simulated examples under good, moderate and poor ionospheric conditions, it is observed that the adaptive Kalman filter based channel estimator provides reliable channel estimates and can track the variation of the channel in time with high accuracy.

  13. 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.

  14. Cascading failure and robustness in metabolic networks.

    PubMed

    Smart, Ashley G; Amaral, Luis A N; Ottino, Julio M

    2008-09-09

    We investigate the relationship between structure and robustness in the metabolic networks of Escherichia coli, Methanosarcina barkeri, Staphylococcus aureus, and Saccharomyces cerevisiae, using a cascading failure model based on a topological flux balance criterion. We find that, compared to appropriate null models, the metabolic networks are exceptionally robust. Furthermore, by decomposing each network into rigid clusters and branched metabolites, we demonstrate that the enhanced robustness is related to the organization of branched metabolites, as rigid cluster formations in the metabolic networks appear to be consistent with null model behavior. Finally, we show that cascading in the metabolic networks can be described as a percolation process.

  15. Modeling and robust control of wind turbine

    NASA Astrophysics Data System (ADS)

    Gilev, Bogdan

    2016-12-01

    In this paper a model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. This model is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model and robust control theory is developed a robust controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and robust controller

  16. 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

  17. Redundancy relations and robust failure detection

    NASA Technical Reports Server (NTRS)

    Chow, E. Y.; Lou, X. C.; Verghese, G. C.; Willsky, A. S.

    1984-01-01

    All failure detection methods are based on the use of redundancy, that is on (possible dynamic) relations among the measured variables. Consequently the robustness of the failure detection process depends to a great degree on the reliability of the redundancy relations given the inevitable presence of model uncertainties. The problem of determining redundancy relations which are optimally robust in a sense which includes the major issues of importance in practical failure detection is addressed. A significant amount of intuition concerning the geometry of robust failure detection is provided.

  18. 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

  19. 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.

  20. Object localization using adaptive feature selection

    NASA Astrophysics Data System (ADS)

    Hwang, S. Youngkyoo; Kim, Jungbae; Lee, Seongdeok

    2009-01-01

    'Fast and robust' are the most beautiful keywords in computer vision. Unfortunately they are in trade-off relationship. We present a method to have one's cake and eat it using adaptive feature selections. Our chief insight is that it compares reference patterns to query patterns, so that it selects smartly more important and useful features to find target. The probabilities of pixels in the query to belong to the target are calculated from importancy of features. Our framework has three distinct advantages: 1 - It saves computational cost dramatically to the conventional approach. This framework makes it possible to find location of an object in real-time. 2 - It can smartly select robust features of a reference pattern as adapting to a query pattern. 3- It has high flexibility on any feature. It doesn't matter which feature you may use. Lots of color space, texture, motion features and other features can fit perfectly only if the features meet histogram criteria.

  1. 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.

  2. 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.

  3. Robust stabilization of the Space Station

    NASA Technical Reports Server (NTRS)

    Wie, Bong

    1991-01-01

    A robust H-infinity control design methodology and its application to a Space Station Freedom (SSF) attitude and momentum control problem are presented. This approach incorporates nonlinear multi-parameter variations in the state-space formulation of H-infinity control theory. An application of this robust H-infinity control synthesis technique to the SSF control problem yields remarkable results in stability robustness with respect to moments of inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this robust H-infinity controller for the SSF are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.

  4. 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.

  5. 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.

  6. Robust views on plasticity and biodiversity

    PubMed Central

    Theißen, Günter; Melzer, Rainer

    2016-01-01

    Background How the diversity of life on our planet originated is not completely understood and many questions are still open. Especially, the role of developmental robustness in evolution is an often neglected topic. Scope Considering diverse groups of plants and animals, and employing different concepts and approaches, the authors of articles in this Special Issue try to understand better the impact of developmental robustness, phenotypic plasticity and variance on species diversity, evolution and morphological disparity. Conclusions Several lines of theoretical considerations as well as case studies show that developmental robustness supports rather than prevents the evolution of species diversity, at least under certain circumstances. Among the possible mechanisms is the scenario that developmental robustness facilitates the synorganization of body parts, which may enable the origin of complex novelties; this then may set the ground for species radiation.

  7. 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.

  8. Robust Synchronization Schemes for Dynamic Channel Environments

    NASA Technical Reports Server (NTRS)

    Xiong, Fugin

    2003-01-01

    Professor Xiong will investigate robust synchronization schemes for dynamic channel environment. A sliding window will be investigated for symbol timing synchronizer and an open loop carrier estimator for carrier synchronization. Matlab/Simulink will be used for modeling and simulations.

  9. 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.

  10. Dual-thread parallel control strategy for ophthalmic adaptive optics.

    PubMed

    Yu, Yongxin; Zhang, Yuhua

    To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a closed loop updating frequency up to 110 Hz, and demonstrated robust compensation for ocular wave aberration up to 50 Hz in an adaptive optics scanning laser ophthalmoscope.

  11. Robust Multimodal Cognitive Load Measurement II

    DTIC Science & Technology

    2015-06-24

    and GSR values. 15. SUBJECT TERMS Behavioural Science, Cognitive Psychology 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...Final 3. DATES COVERED (From - To) 26 June 2014 – 25 June 2015 4. TITLE AND SUBTITLE (134144) Robust Multimodal Cognitive Load...research accomplishments out of the Robust Multimodal Cognitive Load Measurement II (RMCLM) project in the past one-year period. The objective of this

  12. QuEST: Robust Quantum Gadgets

    DTIC Science & Technology

    2013-02-28

    AFRL-OSR-VA-TR-2013-0170 QuEST: Robust Quantum Gadgets Aram Harrow University of Washington Computer Science & Engineering Box 352350 Seattle, WA...REPORT TYPE Final Progress Report 3. DATES COVERED (From - To) 12/01/11 - 11/30/12 4. TITLE AND SUBTITLE QuEST: Robust Quantum Gadgets 5a...computer. Among the threads in our approach are the construction of small scale gadgets for energetic protection of quantum information, the construction

  13. 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.

  14. 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.

  15. Robust control of nonlinear MAGLEV suspension system with mismatched uncertainties via DOBC approach.

    PubMed

    Yang, Jun; Zolotas, Argyrios; Chen, Wen-Hua; Michail, Konstantinos; Li, Shihua

    2011-07-01

    Robust control of a class of uncertain systems that have disturbances and uncertainties not satisfying "matching" condition is investigated in this paper via a disturbance observer based control (DOBC) approach. In the context of this paper, "matched" disturbances/uncertainties stand for the disturbances/uncertainties entering the system through the same channels as control inputs. By properly designing a disturbance compensation gain, a novel composite controller is proposed to counteract the "mismatched" lumped disturbances from the output channels. The proposed method significantly extends the applicability of the DOBC methods. Rigorous stability analysis of the closed-loop system with the proposed method is established under mild assumptions. The proposed method is applied to a nonlinear MAGnetic LEViation (MAGLEV) suspension system. Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.

  16. Adaptive Control Techniques for Large Space Structures

    DTIC Science & Technology

    1987-12-23

    2500 Mizssion. CoV~ege Boulevard Sar-ta Clara, Califorr-Iia 950541-1215 P--epared for: AFOSR, O irectcorate of Aerospace Sciences Bolling Air Force...formulated in late 1982 in re- sponse to the increasing concern that performance robustness of Air Force LSS type system would be inadequate to meet...Reducing the effects of on-board disturbance rejection) is particularly important for planned Air Force missions. For these cases, adaptive control

  17. Adaptive Control of Nonlinear Flexible Systems

    DTIC Science & Technology

    1993-01-18

    disturbances. The following example illustrates the need for a robust state-feedback law and the sensi- tivity of the exact - linearization based control law... exact linearization , one can bring an input-output approach to a particular case of certainty- equivalence based adaptive control design. We now...are available for this model, exact linearization can be performed. Let C(s) be the compensator that is being used so far in the previous three

  18. 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.

  19. 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.

  20. RKF-PCA: robust kernel fuzzy PCA.

    PubMed

    Heo, Gyeongyong; Gader, Paul; Frigui, Hichem

    2009-01-01

    Principal component analysis (PCA) is a mathematical method that reduces the dimensionality of the data while retaining most of the variation in the data. Although PCA has been applied in many areas successfully, it suffers from sensitivity to noise and is limited to linear principal components. The noise sensitivity problem comes from the least-squares measure used in PCA and the limitation to linear components originates from the fact that PCA uses an affine transform defined by eigenvectors of the covariance matrix and the mean of the data. In this paper, a robust kernel PCA method that extends the kernel PCA and uses fuzzy memberships is introduced to tackle the two problems simultaneously. We first introduce an iterative method to find robust principal components, called Robust Fuzzy PCA (RF-PCA), which has a connection with robust statistics and entropy regularization. The RF-PCA method is then extended to a non-linear one, Robust Kernel Fuzzy PCA (RKF-PCA), using kernels. The modified kernel used in the RKF-PCA satisfies the Mercer's condition, which means that the derivation of the K-PCA is also valid for the RKF-PCA. Formal analyses and experimental results suggest that the RKF-PCA is an efficient non-linear dimension reduction method and is more noise-robust than the original kernel PCA.